TY - JOUR AU - Saban, L. Karen AU - Joyce, Cara AU - Nyembwe, Alexandria AU - Janusek, Linda AU - Tell, Dina AU - de la Pena, Paula AU - Motley, Darnell AU - Shawahin, Lamise AU - Prescott, Laura AU - Potts-Thompson, Stephanie AU - Taylor, Y. Jacquelyn PY - 2025/4/18 TI - The Effectiveness of a Race-Based Stress Reduction Intervention on Improving Stress-Related Symptoms and Inflammation in African American Women at Risk for Cardiometabolic Disease: Protocol for Recruitment and Intervention for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e65649 VL - 14 KW - cardiometabolic disease KW - stress KW - Resilience, Stress, and Ethnicity KW - RiSE intervention KW - health of minoritized groups N2 - Background: In recent years, the prevalence of cardiometabolic disease (CMD) in African American women has risen; the risk also increases with age, in comparison to men. Evidence demonstrates that stressful life events, including experiences of racism and perceived discrimination, contribute substantially to inflammatory diseases, such as CMD. Despite this evidence, few evidence-based interventions are available to assist individuals from minoritized communities in coping with the chronic stress related to their racial or ethnic identity. Objective: Our proposed randomized controlled trial will test a novel, race-based intervention tailored to African American women, called Resilience, Stress, and Ethnicity (RiSE). Methods: In this randomized controlled trial, we will randomize participants 1:1 to the 8-week, group-based RiSE program (intervention) or a health education program (active control group). Both programs will consist of synchronous classes on Zoom and will be led by experts. The primary end point will be stress at 6 months after the intervention, and the efficacy of RiSE will be evaluated for improving stress-related symptoms (current perceived stress, depressive symptoms, fatigue, and sleep disturbance), improving coping strategies, and reducing inflammatory burden in African American women at risk for CMD. Validated survey measures and inflammatory biomarkers will be assessed at baseline, midintervention, intervention completion, and 6 months after the intervention, and differences over time by intervention will be evaluated using mixed effects models. Results: This study was funded by the National Institute on Aging on March 30, 2023, with recruitment and enrollment beginning in October 2023. The study is underway, with 120 participants enrolled as of March 2025. Conclusions: This study will be one of the first to examine a race-based stress reduction intervention in African American women and has the potential to improve the health of minoritized groups faced with chronic stress associated with experiencing racism and discrimination. We anticipate that RiSE will reduce stress-related symptoms, enhance adaptive coping, and reduce inflammation. Trial Registration: ClinicalTrials.gov NCT05902741; https://www.clinicaltrials.gov/study/NCT05902741 UR - https://www.researchprotocols.org/2025/1/e65649 UR - http://dx.doi.org/10.2196/65649 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/65649 ER - TY - JOUR AU - Conner, Reagan AU - Porter, Cynthia AU - Lutrick, Karen AU - Beitel, C. Shawn AU - Hollister, James AU - Healy, Olivia AU - Kern, J. Krystal AU - Wardenaar, Floris AU - Gulotta, J. John AU - Jack, Kepra AU - Huentelman, Matthew AU - Burgess, L. Jefferey AU - Furlong, Melissa PY - 2025/4/16 TI - Interventions to Reduce Serum Per- and Poly-Fluoroalkyl Substances Levels, Improve Cardiovascular Risk Profiles, and Improve Epigenetic Age Acceleration in US Firefighters: Protocol for Randomized Controlled Trial JO - JMIR Res Protoc SP - e67120 VL - 14 KW - firefighters KW - PFAS KW - epigenetics KW - phenotype KW - heart disease KW - cardiovascular disease KW - CVD KW - atherosclerosis KW - occupational health KW - RCT KW - cardiovascular KW - fasting KW - exercise N2 - Background: Occupational cancer and acute cardiac events are the leading causes of death among firefighters. Increased exposure to toxicants on the fire ground, such as polycyclic aromatic hydrocarbons, benzene, and per- and poly-fluoroalkyl substances (PFAS), has been linked to certain cancers, cardiovascular disease, accelerated epigenetic aging, and other adverse health effects. PFAS are a major concern because they are persistent, can bioaccumulate, and are present in several firefighting tools. Compared to the general population, firefighters have elevated serum levels of some types of PFAS. A randomized clinical trial in Australian firefighters found that routine blood and plasma donation for 1 year led to decreased serum PFAS levels, although health outcomes were not directly measured in that study. Objective: In collaboration with fire service leadership in Arizona, the Firefighter Collaborative Research Project (FCRP) was established to evaluate the effectiveness of 3 interventions in a randomized controlled trial design to reduce serum PFAS levels, reduce cancer and cardiovascular risk, and improve overall health and wellness in US firefighters. Methods: This study aimed to recruit and enroll up to 1500 active firefighters between August 2023 and October 2024. Between August 2023 and October 2024, active firefighters were recruited and randomized into a study arm based on their eligibility, including serum PFOS levels, for the specific arms. The trial arms include (1) blood and plasma donation, (2) zone 2 physical activity, and (3) intermittent fasting. FCRP outcomes include serum PFAS reduction (arm 1), epigenetic age acceleration (all arms), cardiovascular conditioning (arm 2) and cognitive outcomes (all arms), mental health (all arms), and overall disease risk (all arms). Each study arm includes an intervention and a control group. At enrollment and end of the study, participants provide blood and urine samples and complete a comprehensive questionnaire on their occupational and health history, exposures, and lifestyle behaviors. At the end of the study, participants also participated in a cognitive evaluation. Depending on the study arm, participants may additionally complete a cardiopulmonary exercise test at baseline and follow-up, a mid-study survey, and a mid-study blood and urine collection. Results: Participant activities and data collection will conclude by December 2025. Conclusions: The FCRP is a randomized controlled trial that aims to test the effectiveness of fire service?selected interventions in reducing serum PFAS levels. Study results will contribute to potential interventions that could be used to reduce serum PFAS levels in firefighters. Trial Registration: ClinicalTrials.gov NCT05869747; https://clinicaltrials.gov/study/NCT05869747 International Registered Report Identifier (IRRID): DERR1-10.2196/67120 UR - https://www.researchprotocols.org/2025/1/e67120 UR - http://dx.doi.org/10.2196/67120 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/67120 ER - TY - JOUR AU - Font, Marta AU - Davoody, Nadia PY - 2025/4/15 TI - Optimizing an Electronic Health Record System Used to Help Health Care Professionals Comply With a Standardized Care Pathway for Heart Failure During the Transition From Hospital To Chronic Care: Qualitative Semistructured Interview Study JO - JMIR Med Inform SP - e63665 VL - 13 KW - care pathway KW - heart failure KW - electronic health record KW - sociotechnical system KW - health care professional N2 - Background: In Spain, the prevalence of heart failure is twice the European average, partly due to inadequate patient management. To address this issue, a standardized care model, the Care Model for Patients with Heart Failure (Modelos Asistenciales de Atención al Paciente con Insuficiencia Cardíaca), was developed. This model emphasizes the importance of sequential visits from hospital discharge until the patient transitions to chronic care to prevent rehospitalization. The standardized care pathway has been implemented in certain areas of the Andalusia Health Service. However, there is uncertainty about whether the region?s electronic health record system, Diraya, can effectively support this model. If not properly integrated, it could lead to data inaccuracies and noncompliance with the standardized care pathway. Objective: This study aimed to explore how to improve Diraya to better support health care professionals in adhering to the transition standardized care model for patients with heart failure as they move from hospital care to chronic care. Methods: In total, 16 semistructured interviews were conducted with nurses and physicians from both hospital and primary care settings. Thematic analysis was used to analyze the data and recommendations for improvements that were developed based on the findings. These recommendations were further supported by existing literature and validated through additional interviews. Results: In total, 65 codes, 23 subthemes, and 8 themes were identified. The main themes included optimizing medical data management for enhanced clinical workflow, agreement on standardization and enhancement of the discharge report, enhancing clinical decision support through updated guidelines and automated tools, optimizing interoperability as a solution for better management of patients with heart failure, and encouraging communication based on digital tools and personal connection. In total, 15 improvements were proposed, such as standardizing technology across Andalusia Health Service facilities and offering targeted training programs. These measures aim to enhance interoperability, streamline communication between different health care settings, and reduce the administrative burden for health care professionals. Conclusions: Diraya currently does not adequately support the transition standardized care model, placing a significant administrative burden on health care professionals, often with ethically concerning implications. To ensure effective implementation of the standardized care model, major updates are necessary for Diraya?s clinical information management, system functionality, and organizational structure within the Andalusia Health Service. UR - https://medinform.jmir.org/2025/1/e63665 UR - http://dx.doi.org/10.2196/63665 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/63665 ER - TY - JOUR AU - Su, Jing Jing AU - Lin, Rose AU - Batalik, Ladislav AU - Wong, Ching Arkers Kwan AU - Grace, L. Sherry PY - 2025/4/7 TI - Psychological eHealth Interventions for Patients With Cardiovascular Diseases: Systematic Review and Meta-Analysis JO - J Med Internet Res SP - e57368 VL - 27 KW - cardiovascular diseases KW - eHealth KW - digital health KW - iCBT KW - mental health KW - psychological intervention KW - cognitive behavioral therapy KW - CBT KW - depression KW - heart KW - cardiology KW - psychological KW - anxiety KW - high-risk KW - systematic review KW - meta-analysis KW - CVD KW - evidence-based KW - psychosocial KW - GRADE approach KW - Cochrane Risk of Bias Tool KW - internet-based KW - psychological therapy KW - psychotherapy N2 - Background: Psychological distress is recognized as an independent risk factor for cardiovascular diseases (CVDs), contributing to increased morbidity and mortality. While eHealth is increasingly used to deliver psychological interventions, their effectiveness for patients with CVDs remains unclear. Objective: This meta-analysis aimed to evaluate the effects of eHealth psychological interventions for patients with CVDs. Methods: Eligible studies were retrieved from 5 databases (Embase, Medline, PubMed, CINAHL, and Cochrane Library), covering the period from database inception to December 2024. Randomized controlled trials (RCTs) investigating the effect of evidence-based psychological eHealth interventions to improve psychosocial well-being and cardiovascular outcomes for people with CVDs were included. The Cochrane Risk of Bias tool (version 2) was used to judge the methodological quality of reviewed studies. RevMan (version 5.3) was used for meta-analysis. Results: A total of 12 RCTs, comprising 2319 participants from 10 countries, were included in the review. The results demonstrated significant alleviation of depressive symptoms for patients receiving psychological eHealth intervention compared to controls (number of paper included in that particular analysis, n=7; standardized mean difference=?0.30, 95% CI ?0.47 to ?0.14; I2=57%; P<.001). More specifically, in 6 trials where internet-based cognitive behavioral therapy was delivered, a significant alleviation of depressive symptoms was achieved (standardized mean difference=?0.39, 95% CI ?0.56 to ?0.21; I2=53%; P<.001). There was no significant change in anxiety or quality of life. Synthesis without meta-analysis regarding stress, adverse events, and cardiovascular events showed inconclusive findings. Conclusions: Psychological eHealth interventions, particularly internet-based cognitive behavioral therapy, can significantly reduce depressive symptoms among patients with CVDs. A multidisciplinary approach is crucial for comprehensively improving psychological and cardiovascular outcomes. Future studies should explore integrating persuasive design features into eHealth and involving mental health professionals for intervention delivery. Trial Registration: PROSPERO CRD42023452276; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023452276 UR - https://www.jmir.org/2025/1/e57368 UR - http://dx.doi.org/10.2196/57368 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/57368 ER - TY - JOUR AU - Zhang, Xinyue PY - 2025/3/28 TI - Authors? Reply: The SCeiP Model for Remote Rehabilitation in Homebound Patients With Coronary Heart Disease JO - J Med Internet Res SP - e70247 VL - 27 KW - exercise rehabilitation KW - coronary heart disease KW - promotion strategy KW - home rehabilitation UR - https://www.jmir.org/2025/1/e70247 UR - http://dx.doi.org/10.2196/70247 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/70247 ER - TY - JOUR AU - Zhang, Siqi AU - Chen, Tielong PY - 2025/3/28 TI - The SCeiP Model for Remote Rehabilitation in Homebound Patients With Coronary Heart Disease JO - J Med Internet Res SP - e69927 VL - 27 KW - remote exercise rehabilitation KW - SCeiP model KW - coronary heart disease KW - promotion strategy KW - home rehabilitation UR - https://www.jmir.org/2025/1/e69927 UR - http://dx.doi.org/10.2196/69927 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/69927 ER - TY - JOUR AU - Ullrich, Greta AU - Bäuerle, Alexander AU - Vogt, Hannah AU - Mahabadi, Abbas Amir AU - Paldán, Katrin AU - Messiha, Daniel AU - Jahre, Maria Lisa AU - Rammos, Christos AU - Rassaf, Tienush AU - Lortz, Julia PY - 2025/3/19 TI - Digital Health Literacy and Attitudes Toward eHealth Technologies Among Patients With Cardiovascular Disease and Their Implications for Secondary Prevention: Survey Study JO - JMIR Form Res SP - e63057 VL - 9 KW - cardiovascular diseases KW - telemedicine KW - eHealth KW - patient-centered approach KW - digital health literacy KW - digital health KW - cardiovascular disease KW - mortality KW - artery disease KW - ischemic KW - heart disease KW - diabetes mellitus KW - obesity KW - patient education KW - eHealth literacy KW - mobile phone N2 - Background: Cardiovascular disease is the major cause of death worldwide, leading to a significant socioeconomic burden. Although secondary prevention is a cornerstone in chronic disease management, adherence to guideline recommendations in this regard often falters, leading to suboptimal outcomes. While eHealth technologies are promising for improving treatment adherence, they also represent a new approach to secondary prevention. However, a common critique is that extensive digitalization may not adequately address the needs of older adults with chronic medical conditions. Objective: This study aims to analyze eHealth literacy, digital use patterns, and general attitudes toward digital technologies in a collective of patients with cardiovascular disease to identify potential obstacles in implementing mobile health technologies in secondary preventive therapy. Methods: This survey-based study was a part of the baseline examination of the PreventiPlaque trial. It involved 240 participants with known coronary artery disease. The assessment evaluated their current understanding of the general use of digital devices. The questionnaire covered aspects such as the duration of daily use, personal attitudes, and the perceived burden associated with digital media. eHealth literacy was assessed within the target population and general demographic data were gathered, focusing on cardiovascular comorbidities and risk factors. Results: The analysis revealed an average age of 61.9 (SD 8.9) years, with 59.9% (n=144) of the participants being male. Overall, 37.3% (n=90) of the participants had previous knowledge of digital health interventions, while only 17.8% (n=41) had used them. Despite the generally low practical application within this study population, there was a high level of confidence in handling digital devices, with 61.9% (n=149) expressing themselves as either rather confident or very confident. Regarding the levels of eHealth literacy among the participants, 71.2% (n=170) claimed to be familiar with locating health information on the internet, and 64% (n=153) of participants felt capable of critically evaluating its quality. These levels of digital confidence were consistent across all age groups. Moreover, internet use rates remained high even among the older participants, with 80% (n=192) of those participants older than 75 years using the internet for 1-3 hours a day. Conclusions: The study unveiled a notable confidence level among participants regarding the use of digital devices, coupled with a favorable attitude toward digital media evident across all age brackets. Remarkably, internet use rates remained high, even among older participants. The actual utilization of digital health interventions was relatively low, potentially stemming from challenges in locating reliable sources. These findings emphasize the prospect of future eHealth interventions customized to the distinct needs and preferences of patients in cardiovascular disease management. Recognizing the incongruity between confidence in device use and the restricted adoption of digital health tools can guide the development of focused interventions to narrow this divide. Trial Registration: ClinicalTrials.gov NCT05096637; https://clinicaltrials.gov/study/NCT05096637 UR - https://formative.jmir.org/2025/1/e63057 UR - http://dx.doi.org/10.2196/63057 ID - info:doi/10.2196/63057 ER - TY - JOUR AU - Karamchand, Sumanth AU - Chipamaunga, Tsungai AU - Naidoo, Poobalan AU - Naidoo, Kiolan AU - Rambiritch, Virendra AU - Ho, Kevin AU - Chilton, Robert AU - McMahon, Kyle AU - Leisegang, Rory AU - Weich, Hellmuth AU - Hassan, Karim PY - 2025/3/10 TI - Novel Versus Conventional Sequencing of ?-Blockers, Sodium/Glucose Cotransportor 2 Inhibitors, Angiotensin Receptor-Neprilysin Inhibitors, and Mineralocorticoid Receptor Antagonists in Stable Patients With Heart Failure With Reduced Ejection Fraction (NovCon Sequencing Study): Protocol for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e44027 VL - 14 KW - heart failure KW - SGLT2i KW - sodium/glucose cotransporter 2 inhibitors KW - ARNi KW - angiotensin receptor-neprilysin inhibitors KW - HFrEF KW - heart failure with reduced ejection fraction KW - idiopathic dilated cardiomyopathy KW - heart KW - chronic heart failure KW - patient KW - control KW - clinical KW - adult KW - cardiomyopathy KW - therapy N2 - Background: Chronic heart failure has high morbidity and mortality, with approximately half of the patients dying within 5 years of diagnosis. Recent additions to the armamentarium of anti?heart failure therapies include angiotensin receptor-neprilysin inhibitors (ARNIs) and sodium/glucose cotransporter 2 inhibitors (SGLT2is). Both classes have demonstrated mortality and morbidity benefits. Although these new therapies have morbidity and mortality benefits, it is not known whether rapid initiation is beneficial when compared with the conventional, slower-stepped approach. Many clinicians have been taught that starting with low-dose therapies and gradually increasing the dose is a safe way of intensifying treatment regimens. Pharmacologically, it is rational to use a combination of drugs that target multiple pathological mechanisms, as there is potential synergism and better therapeutic outcomes. Theoretically, the quicker the right combinations are used, the more likely the beneficial effects will be experienced. However, rapid up-titration must be balanced with patient safety and tolerability. Objective: This study aims to determine if early addition of ARNIs, SGLT2is, ?-blockers, and mineralocorticoid receptor antagonists (within 4 weeks), when compared with the same therapies initiated slower (within 6 months), will reduce all-cause mortality and hospitalizations for heart failure in patients with stable heart failure with reduced ejection fraction. Methods: This is a single-center, randomized controlled, double-arm, assessor-blinded, active control, and pragmatic clinical trial. Adults with stable heart failure with reduced ejection fraction and idiopathic dilated cardiomyopathy will be randomized to conventional sequencing (the control arm; over 6 months) of anti?heart failure therapies, and a second arm will receive rapid sequencing (over 4 weeks). Study participants will be followed for 5 years to assess the safety, efficacy, and tolerability of the 2 types of sequencing. Posttrial access and care will be provided to all study participants throughout their lifespan. Results: We are currently in the process of obtaining ethical clearance and funding. Conclusions: We envisage that this study will help support evidence-based medicine and inform clinical practice guidelines on the optimal rate of sequencing of anti?heart failure therapies. A third placebo arm was considered, but costs would be too much and not providing study participants with therapies with known morbidity and mortality benefits may be unethical, in our opinion. Given the post?COVID-19 economic downturn and posttrial access to interventions, a major challenge will be acquiring funding for this study. International Registered Report Identifier (IRRID): PRR1-10.2196/44027 UR - https://www.researchprotocols.org/2025/1/e44027 UR - http://dx.doi.org/10.2196/44027 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/44027 ER - TY - JOUR AU - Lee, Yugyung AU - Shelke, Sushil AU - Lee, Chi PY - 2025/3/8 TI - Cardiac Repair and Regeneration via Advanced Technology: Narrative Literature Review JO - JMIR Biomed Eng SP - e65366 VL - 10 KW - advanced technologies KW - genetics KW - biomaterials KW - bioengineering KW - medical devices KW - implantable devices KW - wearables KW - cardiovascular repair and regeneration KW - cardiac care KW - cardiovascular disease N2 - Background: Cardiovascular diseases (CVDs) are the leading cause of death globally, and almost one-half of all adults in the United States have at least one form of heart disease. This review focused on advanced technologies, genetic variables in CVD, and biomaterials used for organ-independent cardiovascular repair systems. Objective: A variety of implantable and wearable devices, including biosensor-equipped cardiovascular stents and biocompatible cardiac patches, have been developed and evaluated. The incorporation of those strategies will hold a bright future in the management of CVD in advanced clinical practice. Methods: This study employed widely used academic search systems, such as Google Scholar, PubMed, and Web of Science. Recent progress in diagnostic and treatment methods against CVD, as described in the content, are extensively examined. The innovative bioengineering, gene delivery, cell biology, and artificial intelligence?based technologies that will continuously revolutionize biomedical devices for cardiovascular repair and regeneration are also discussed. The novel, balanced, contemporary, query-based method adapted in this manuscript defined the extent to which an updated literature review could efficiently provide research on the evidence-based, comprehensive applicability of cardiovascular devices for clinical treatment against CVD. Results: Advanced technologies along with artificial intelligence?based telehealth will be essential to create efficient implantable biomedical devices, including cardiovascular stents. The proper statistical approaches along with results from clinical studies including model-based risk probability prediction from genetic and physiological variables are integral for monitoring and treatment of CVD risk. Conclusions: To overcome the current obstacles in cardiac repair and regeneration and achieve successful therapeutic applications, future interdisciplinary collaborative work is essential. Novel cardiovascular devices and their targeted treatments will accomplish enhanced health care delivery and improved therapeutic efficacy against CVD. As the review articles contain comprehensive sources for state-of-the-art evidence for clinicians, these high-quality reviews will serve as a first outline of the updated progress on cardiovascular devices before undertaking clinical studies. UR - https://biomedeng.jmir.org/2025/1/e65366 UR - http://dx.doi.org/10.2196/65366 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/65366 ER - TY - JOUR AU - Miao, Shumei AU - Ji, Pei AU - Zhu, Yongqian AU - Meng, Haoyu AU - Jing, Mang AU - Sheng, Rongrong AU - Zhang, Xiaoliang AU - Ding, Hailong AU - Guo, Jianjun AU - Gao, Wen AU - Yang, Guanyu AU - Liu, Yun PY - 2025/3/3 TI - The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study JO - JMIR Med Inform SP - e63186 VL - 13 KW - CVD KW - CDSS KW - multimodel data KW - knowledge engine KW - development KW - cardiovascular disease KW - clinical decision support system N2 - Background: Due to the acceleration of the aging population and the prevalence of unhealthy lifestyles, the incidence of cardiovascular diseases (CVDs) in China continues to grow. However, due to the uneven distribution of medical resources across regions and significant disparities in diagnostic and treatment levels, the diagnosis and management of CVDs face considerable challenges. Objective: The purpose of this study is to build a cardiovascular diagnosis and treatment knowledge base by using new technology, form an auxiliary decision support system, and integrate it into the doctor?s workstation, to improve the assessment rate and treatment standardization rate. This study offers new ideas for the prevention and management of CVDs. Methods: This study designed a clinical decision support system (CDSS) with data, learning, knowledge, and application layers. It integrates multimodal data from hospital laboratory information systems, hospital information systems, electronic medical records, electrocardiography, nursing, and other systems to build a knowledge model. The unstructured data were segmented using natural language processing technology, and medical entity words and entity combination relationships were extracted using IDCNN (iterated dilated convolutional neural network) and TextCNN (text convolutional neural network). The CDSS refers to global CVD assessment indicators to design quality control strategies and an intelligent treatment plan recommendation engine map, establishing a big data analysis platform to achieve multidimensional, visualized data statistics for management decision support. Results: The CDSS system is embedded and interfaced with the physician workstation, triggering in real-time during the clinical diagnosis and treatment process. It establishes a 3-tier assessment control through pop-up windows and screen domination operations. Based on the intelligent diagnostic and treatment reminders of the CDSS, patients are given intervention treatments. The important risk assessment and diagnosis rate indicators significantly improved after the system came into use, and gradually increased within 2 years. The indicators of mandatory control, directly became 100% after the CDSS was online. The CDSS enhanced the standardization of clinical diagnosis and treatment. Conclusions: This study establishes a specialized knowledge base for CVDs, combined with clinical multimodal information, to intelligently assess and stratify cardiovascular patients. It automatically recommends intervention treatments based on assessments and clinical characterizations, proving to be an effective exploration of using a CDSS to build a disease-specific intelligent system. UR - https://medinform.jmir.org/2025/1/e63186 UR - http://dx.doi.org/10.2196/63186 ID - info:doi/10.2196/63186 ER - TY - JOUR AU - Ramesh, Harini Shri AU - Jull, Darwin AU - Fournier, Hélène AU - Rajabiyazdi, Fateme PY - 2025/2/21 TI - Exploring Barriers to Patients? Progression in the Cardiac Rehabilitation Journey From Health Care Providers? Perspectives: Qualitative Study JO - Interact J Med Res SP - e66164 VL - 14 KW - cardiac rehabilitation KW - health care providers KW - CR patient journey KW - qualitative study KW - barriers KW - technology N2 - Background: Cardiovascular diseases are one of the leading causes of mortality globally. Cardiac rehabilitation (CR) programs are crucial for patients recovering from cardiac events, as they help reduce the risk of recurrent events and support patient recovery. The patient?s journey in CR spans the stages before, during, and after the program. Patients have to progress through each stage of CR programs successfully to complete the entire CR journey and get the full benefits of CR programs, but numerous barriers within this journey can hinder patient progression. Objective: This study aims to explore the barriers to progression at all stages of the CR patient journey from the perspectives of health care providers involved in CR care. Methods: This qualitative study involved semistructured interviews with health care providers involved in CR care from July 2023 to January 2024. A purposive maximal variation sampling method was used to target providers with diverse demographics and specialties. Snowball sampling was used to recruit participants, leveraging the existing networks of participants. Each interview lasted between 30 and 45 minutes. Interviews were recorded, transcribed verbatim, and analyzed using an inductive thematic analysis approach. Data analysis was conducted from August 2023 to February 2024. Results: Ten health care providers, comprising 7 females and 3 males, were interviewed. Their roles included physician, program director, nurse manager, clinical manager, nurse coordinator, nurse, physiotherapist, and kinesiologist. The analysis identified four overarching themes related to barriers to progression in the CR journey: (1) patients not being referred to CR programs, (2) patients not enrolling in CR programs, (3) patients dropping out of CR programs, and (4) patients? lack of adherence to lifestyle changes post-CR programs. Conclusions: In light of the growing interest in technological interventions in CR programs, we proposed 4 potential technological solutions to address the barriers to progression identified in our analysis. These solutions aim to provide a foundation for future research to guide the development of effective technologies and enhance patient progression within the CR journey. UR - https://www.i-jmr.org/2025/1/e66164 UR - http://dx.doi.org/10.2196/66164 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/66164 ER - TY - JOUR AU - Dinesen, Birthe AU - Albertsen, Eie Andi AU - Joensen, Ragnvaldsdóttir Elisabet Dortea AU - Spindler, Helle AU - Jensen, Møller Katja AU - Kidholm, Kristian AU - Frost, Lars AU - Dittman, Lars AU - Gunasegaram, Mathushan AU - Johnsen, Paaske Søren AU - Jochumsen, Rovsing Mads AU - Svenstrup, Dorthe PY - 2025/2/18 TI - Future Patient?Telerehabilitation of Patients With Atrial Fibrillation: Protocol for a Multicenter, Mixed Methods, Randomized Controlled Trial JO - JMIR Res Protoc SP - e64259 VL - 14 KW - atrial fibrillation KW - telerehabilitation KW - quality of life KW - research design KW - patient education KW - co-creation KW - randomized controlled trial KW - chronic KW - cardiovascular disease KW - adult KW - aging KW - prevalence KW - comorbidity KW - Future Patient KW - patient engagement KW - primary outcome KW - cost-effectiveness KW - monitoring KW - health care professional KW - digital health KW - remote therapy KW - telehealth N2 - Background: Atrial fibrillation (AF) is a chronic cardiovascular condition with a lifetime risk of 1 in 3 and a prevalence of 3% among adults. AF?s prevalence is predicted to more than double during the next 20 years due to better detection, increasing comorbidities, and an aging population. Due to increased AF prevalence, telerehabilitation has been developed to enhance patient engagement, health care accessibility, and compliance through digital technologies. A telerehabilitation program called ?Future Patient?telerehabilitation of patients with AF (FP-AF)? has been developed to enhance rehabilitation for AF. The FP-AF program comprises two modules: (1) an education and monitoring module using telerehabilitation technologies (4 months) and (2) a follow-up module, where patients can measure steps and access a data and knowledge-sharing portal, HeartPortal, using their digital devices. Those patients in the FP-AF program measure their heart rhythm, pulse, blood pressure, weight, steps, and sleep. Patients also complete web-based questionnaires regarding their well-being and coping with AF. All recorded data are transmitted to the HeartPortal, accessible to patients, relatives, and health care professionals. Objective: This paper aims to describe the research design, outcome measures, and data collection techniques in a clinical trial of the FP-AF program for patients with AF. Methods: This is a multicenter, mixed methods, randomized controlled trial. Patients are recruited from AF clinics serving the North Jutland region of Denmark. The telerehabilitation group will participate in the FP-AF program, while the control group will follow the conventional care regime based on physical visits to the AF clinic. The primary outcome measure is AF-specific health-related quality of life, to be assessed using the Atrial Fibrillation Effect on Quality-of-Life Questionnaire. Secondary outcomes are knowledge of AF; measurement of vital parameters; level of anxiety and depression; degree of motivation; burden of AF; use of the HeartPortal; qualitative exploration of patients?, relatives?, and health care professionals? experiences of participating in the FP-AF program; cost-effectiveness evaluation of the program; and analysis of multiparametric monitoring data. Outcomes are assessed through data from digital technologies, interviews, and questionnaires. Results: Patient enrollment began in January 2023 and will be completed by December 2024, with a total of 208 patients enrolled. Qualitative interviews conducted in spring 2024 will be analyzed and published in peer-reviewed journals in 2025. Data from questionnaires and digital technologies will be analyzed upon study completion and presented at international conferences and published in peer-reviewed journals by the fall of 2025. Conclusions: Results from the FP-AF study will determine whether the FP-AF program can increase quality of life for patients with AF and increase their knowledge of symptoms and living with AF in everyday life compared to conventional AF care. The cost-effectiveness evaluation will determine whether telerehabilitation can be a viable alternative for rehabilitation of patients with AF. Trial Registration: ClinicalTrials.gov NCT06101485; https://clinicaltrials.gov/study/NCT06101485 International Registered Report Identifier (IRRID): DERR1-10.2196/64259 UR - https://www.researchprotocols.org/2025/1/e64259 UR - http://dx.doi.org/10.2196/64259 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/64259 ER - TY - JOUR AU - He, Jinyu AU - Li, Yanjun AU - Zeng, Huatang AU - Sun, Haoran AU - Wu, Liqun AU - Zhu, Zhenzhen AU - Zhang, Ning AU - Liang, Wannian PY - 2025/2/10 TI - Health Equity of Hypertension Management Between Local Residents and Internal Migrants in Shenzhen, China: Cross-Sectional Study JO - JMIR Public Health Surveill SP - e65548 VL - 11 KW - health equity KW - hypertension management KW - immigrant population KW - hypertension KW - China KW - global health KW - public health KW - health disparities KW - medical record KW - community health care KW - native population KW - immigrant KW - socioeconomic KW - disease burden KW - well-being KW - chronic disease KW - community health center N2 - Background: With hypertension emerging as a global public health concern, taking measures to alleviate its burden is urgently needed. The hypertension management program (HMP) in China is a standardized policy to help people with hypertension to improve their health levels and reduce health inequalities. However, studies focusing on details regarding participation in this program remain scarce. Objective: This study aims to investigate the participation rates in HMPs in China and examine the health disparities in hypertension management between local residents and internal migrants in Shenzhen. Methods: This study used the medical record of Shenzhen, Guangdong, China. We included adults with new-onset diagnosis of hypertension after 2017 and focused on patients who have a record in the community health center. We described the basic characteristics of people diagnosed with hypertension, including age, gender, marital status, occupation, education level, and health insurance type. Enrolled rate, follow-up rate, and adherence rate were used to measure the engagement with this program at the city, district, and community levels. Results: Of the 1,160,214 hypertensive patients, 29.70% (344,526/1,160,214) were local residents, while 70.3% (815,688/1,160,214) were internal migrants. In addition, 55.36% (642,250/1,160,214) were enrolled in the HMP. Of those, 57.52% (369,439/642,25) were followed up. In addition, 62.59% (231,217/369,439) of followed up individuals were adherents. Internal migrants demonstrated a significantly higher participation in the HMP, especially for the enrolled rate (local residents: 156,085/344,526, 45.30% vs internal migrants: 486,165/815,688, 59.60%) and adherence rate (local residents: 44,044/84,635, 52.04% vs internal migrants: 187,173/284,804, 65.72%). Apart from that, local, single, and younger individuals had lower rates compared to their counterparts. There also existed within-district and within-community variation among enrolled, follow-up, and adherence rates. Conclusions: Based on our research, individuals with different demographic and socioeconomic characteristics and in different regions had different enrolled, follow-up, and adherence rates. Internal migrants in Shenzhen showed a significantly higher participation in the HMP. Given these findings, there exists the potential to enhance the outreach and engagement of local, single, and younger populations through targeted promotional strategies. UR - https://publichealth.jmir.org/2025/1/e65548 UR - http://dx.doi.org/10.2196/65548 ID - info:doi/10.2196/65548 ER - TY - JOUR AU - Wei, Feiran AU - Ge, You AU - Li, Han AU - Liu, Yuan PY - 2025/2/6 TI - Impact of the National Essential Public Health Service Package on Blood Pressure Control in Chinese People With Hypertension: Retrospective Population-Based Longitudinal Study JO - JMIR Public Health Surveill SP - e65783 VL - 11 KW - hypertension KW - primary care KW - public health KW - blood pressure control KW - cardiovascular disease N2 - Background: The National Essential Public Health Service Package (NEPHSP) was launched in 2009 to tackle poor blood pressure control in Chinese people with hypertension; however, it?s effect is still unclear. Objective: In a retrospective population-based longitudinal study, we aimed to evaluate effect of the NEPHSP on blood pressure control. Methods: A total of 516,777 patients registered in the NEPHSP were included. The blood pressure control data were assessed based on the Residence Health Record System dataset. We longitudinally evaluated the effects of the NEPHSP on blood pressure control by analyzing changes in blood pressure at quarterly follow-ups. Both the degree and trend of the blood pressure changes were analyzed. We conducted stratified analysis to explore effects of the NEPHSP on blood pressure control among subgroups of participants with specific characteristics. Results: The mean baseline systolic blood pressure (SBP) and diastolic blood pressure (DBP) were 147.12 (SD 19.88) mm Hg and 85.11 (SD 11.79) mm Hg, respectively. The control rates of baseline SBP and DBP were 39.79% (205,630/516,777) and 69.21% (357,685/516,777). Compared to baseline, the mean SBP decreased in each quarter by 5.06 mm Hg (95% CI ?5.11 to ?5.00; P<.001), 6.69 mm Hg (95% CI; ?6.74 to ?6.63; P<.001), 10.30 mm Hg (95% CI ?10.34 to ?10.23; P<.001), and 6.63 mm Hg (95% CI ?6.68 to ?6.57; P<.001). The SBP control rates increased in each quarter to 53.12% (274,493/516,777; ? coefficient=0.60, 95% CI 0.59-0.61; P<.001), 56.61% (292,537/516,777; ? coefficient=0.76, 95% CI 0.75-0.77; P<.001), 63.4% (327,648/516,777; ? coefficient=1.08, 95% CI 1.07-1.09; P<.001), and 55.09% (284,711/516,777; ? coefficient=0.69, 95% CI 0.68-0.70; P<.001). Compared to baseline, the mean DBP decreased in each quarter by 1.75 mm Hg (95% CI ?1.79 to ?1.72; P<.001), 2.64 mm Hg (95% CI ?2.68 to ?2.61; P<.001), 4.20 mm Hg (95% CI ?4.23 to ?4.16; P<.001), and 2.64 mm Hg (95% CI ?2.68 to ?2.61; P<.001). DBP control rates increased in each quarter to 78.11% (403,641/516,777; ? coefficient=0.52, 95% CI 0.51-0.53; P<.001), 80.32% (415,062/516,777; ? coefficient=0.67, 95% CI 0.66-0.68; P<.001), 83.17% (429,829/516,777; ? coefficient=0.89, 95% CI 0.88-0.90; P<.001), and 79.47% (410,662/516,777; ? coefficient=0.61, 95% CI 0.60-0.62; P<.001). The older age group had a larger decrease in their mean SBP (? coefficient=0.87, 95% CI 0.85-0.90; P<.001) and a larger increase in SBP control rates (? coefficient=0.054, 95% CI 0.051-0.058; P<.001). The participants with cardiovascular disease (CVD) had a smaller decrease in their mean SBP (? coefficient=?0.38, 95% CI ?0.41 to ?0.35; P<.001) and smaller increase in SBP control rates (? coefficient=?0.041, 95% CI ?0.045 to ?0.037; P<.001) compared to the blood pressure of participants without CVD. Conclusions: The NEPHSP was effective in improving blood pressure control of Chinese people with hypertension. Blood pressure control of older individuals and those with CVD need to be intensified. UR - https://publichealth.jmir.org/2025/1/e65783 UR - http://dx.doi.org/10.2196/65783 ID - info:doi/10.2196/65783 ER - TY - JOUR AU - Chin, Wei-Chih AU - Chu, Pao-Hsien AU - Wu, Lung-Sheng AU - Lee, Kuang-Tso AU - Lin, Chen AU - Ho, Chien-Te AU - Yang, Wei-Sheng AU - Chung, I-Hang AU - Huang, Yu-Shu PY - 2025/2/4 TI - The Prognostic Significance of Sleep and Circadian Rhythm for Myocardial Infarction Outcomes: Case-Control Study JO - J Med Internet Res SP - e63897 VL - 27 KW - myocardial infarction KW - circadian rhythm KW - actigraphy KW - nonparametric analysis KW - prognosis KW - sleep KW - heart rate variability KW - activity N2 - Background: Myocardial infarction (MI) is a medical emergency resulting from coronary artery occlusion. Patients with acute MI often experience disturbed sleep and circadian rhythm. Most previous studies assessed the premorbid sleep and circadian rhythm of patients with MI and their correlations with cardiovascular disease. However, little is known about post-MI sleep and circadian rhythm and their impacts on prognosis. The use of actigraphy with different algorithms to evaluate sleep and circadian rhythm after acute MI has the potential for predicting outcomes and preventing future disease progression. Objective: We aimed to evaluate how sleep patterns and disrupted circadian rhythm affect the prognosis of MI, using actigraphy and heart rate variability (HRV). Nonparametric analysis of actigraphy data was performed to examine the circadian rhythm of patients. Methods: Patients with MI in the intensive care unit (ICU) were enrolled alongside age- and gender-matched healthy controls. Actigraphy was used to evaluate sleep and circadian rhythm, while HRV was monitored for 24 hours to assess autonomic nerve function. Nonparametric indicators were calculated to quantify the active-rest patterns, including interdaily stability, intradaily variability, the most active 10 consecutive hours (M10), the least active 5 consecutive hours (L5), the relative amplitude, and the actigraphic dichotomy index. Follow-ups were conducted at 3 and 6 months after discharge to evaluate prognosis, including the duration of current admission, the number and duration of readmission and ICU admission, and catheterization. Independent sample t tests and analysis of covariance were used to compare group differences. Pearson correlation tests were used to explore the correlations of the parameters of actigraphy and HRV with prognosis. Results: The study included 34 patients with MI (mean age 57.65, SD 9.03 years) and 17 age- and gender-matched controls. MI patients had significantly more wake after sleep onset, an increased number of awakenings, and a lower sleep efficiency than controls. Circadian rhythm analysis revealed significantly lower daytime activity in MI patients. Moreover, these patients had a lower relative amplitude and dichotomy index and a higher intradaily variability and midpoint of M10, suggesting less sleep and wake activity changes, more fragmentation of the rest-activity patterns, and a more delayed circadian rhythm. Furthermore, significant correlations were found between the parameters of circadian rhythm analysis, including nighttime activity, time of M10 and L5, and daytime and nighttime activitySD, and patient prognosis. Conclusions: Patients with acute MI experienced significantly worse sleep and disturbed circadian rhythm compared with healthy controls. Our actigraphy-based analysis revealed a disturbed circadian rhythm, including reduced daytime activities, greater fluctuation in hourly activities, and a weak rest-activity rhythm, which were correlated with prognosis. The evaluation of sleep and circadian rhythm in patients with acute MI can serve as a valuable indicator for prognosis and should be further studied. UR - https://www.jmir.org/2025/1/e63897 UR - http://dx.doi.org/10.2196/63897 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/63897 ER - TY - JOUR AU - Jiang, Yiqun AU - Li, Qing AU - Huang, Yu-Li AU - Zhang, Wenli PY - 2025/1/29 TI - Urgency Prediction for Medical Laboratory Tests Through Optimal Sparse Decision Tree: Case Study With Echocardiograms JO - JMIR AI SP - e64188 VL - 4 KW - interpretable machine learning KW - urgency prediction KW - appointment scheduling KW - echocardiogram KW - health care management N2 - Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care. For example, an echocardiogram is a type of laboratory test that is extremely important and not easily accessible. The increasing demand for echocardiograms underscores the imperative for more efficient scheduling protocols. Despite this pressing need, limited research has been conducted in this area. Objective: The study aims to develop an interpretable machine learning model for determining the urgency of patients requiring echocardiograms, thereby aiding in the prioritization of scheduling procedures. Furthermore, this study aims to glean insights into the pivotal attributes influencing the prioritization of echocardiogram appointments, leveraging the high interpretability of the machine learning model. Methods: Empirical and predictive analyses have been conducted to assess the urgency of patients based on a large real-world echocardiogram appointment dataset (ie, 34,293 appointments) sourced from electronic health records encompassing administrative information, referral diagnosis, and underlying patient conditions. We used a state-of-the-art interpretable machine learning algorithm, the optimal sparse decision tree (OSDT), renowned for its high accuracy and interpretability, to investigate the attributes pertinent to echocardiogram appointments. Results: The method demonstrated satisfactory performance (F1-score=36.18% with an improvement of 1.7% and F2-score=28.18% with an improvement of 0.79% by the best-performing baseline model) in comparison to the best-performing baseline model. Moreover, due to its high interpretability, the results provide valuable medical insights regarding the identification of urgent patients for tests through the extraction of decision rules from the OSDT model. Conclusions: The method demonstrated state-of-the-art predictive performance, affirming its effectiveness. Furthermore, we validate the decision rules derived from the OSDT model by comparing them with established medical knowledge. These interpretable results (eg, attribute importance and decision rules from the OSDT model) underscore the potential of our approach in prioritizing patient urgency for echocardiogram appointments and can be extended to prioritize other laboratory test appointments using electronic health record data. UR - https://ai.jmir.org/2025/1/e64188 UR - http://dx.doi.org/10.2196/64188 UR - http://www.ncbi.nlm.nih.gov/pubmed/39879091 ID - info:doi/10.2196/64188 ER - TY - JOUR AU - Brown, Joan AU - De-Oliveira, Sophia AU - Mitchell, Christopher AU - Cesar, Carmen Rachel AU - Ding, Li AU - Fix, Melissa AU - Stemen, Daniel AU - Yacharn, Krisda AU - Wong, Fum Se AU - Dhillon, Anahat PY - 2025/1/24 TI - Barriers to and Facilitators of Implementing Team-Based Extracorporeal Membrane Oxygenation Simulation Study: Exploratory Analysis JO - JMIR Med Educ SP - e57424 VL - 11 KW - intensive care unit KW - ICU KW - teamwork in the ICU KW - team dynamics KW - collaboration KW - interprofessional collaboration KW - simulation KW - simulation training KW - ECMO KW - extracorporeal membrane oxygenation KW - life support KW - cardiorespiratory dysfunction KW - cardiorespiratory KW - cardiology KW - respiratory KW - heart KW - lungs N2 - Introduction: Extracorporeal membrane oxygenation (ECMO) is a critical tool in the care of severe cardiorespiratory dysfunction. Simulation training for ECMO has become standard practice. Therefore, Keck Medicine of the University of California (USC) holds simulation-training sessions to reinforce and improve providers knowledge. Objective: This study aimed to understand the impact of simulation training approaches on interprofessional collaboration. We believed simulation-based ECMO training would improve interprofessional collaboration through increased communication and enhance teamwork. Methods: This was a single-center, mixed methods study of the Cardiac and Vascular Institute Intensive Care Unit at Keck Medicine of USC conducted from September 2021 to April 2023. Simulation training was offered for 1 hour monthly to the clinical team focused on the collaboration and decision-making needed to evaluate the initiation of ECMO therapy. Electronic surveys were distributed before, after, and 3 months post training. The survey evaluated teamwork and the effectiveness of training, and focus groups were held to understand social environment factors. Additionally, trainee and peer evaluation focus groups were held to understand socioenvironmental factors. Results: In total, 37 trainees attended the training simulation from August 2021 to August 2022. Using 27 records for exploratory factor analysis, the standardized Cronbach ? was 0.717. The survey results descriptively demonstrated a positive shift in teamwork ability. Qualitative themes identified improved confidence and decision-making. Conclusions: The study design was flawed, indicating improvement opportunities for future research on simulation training in the clinical setting. The paper outlines what to avoid when designing and implementing studies that assess an educational intervention in a complex clinical setting. The hypothesis deserves further exploration and is supported by the results of this study. UR - https://mededu.jmir.org/2025/1/e57424 UR - http://dx.doi.org/10.2196/57424 ID - info:doi/10.2196/57424 ER - TY - JOUR AU - Gong, Ke AU - Chen, Yifan AU - Song, Xinyue AU - Fu, Zhizhong AU - Ding, Xiaorong PY - 2025/1/23 TI - Causal Inference for Hypertension Prediction With Wearable Electrocardiogram and Photoplethysmogram Signals: Feasibility Study JO - JMIR Cardio SP - e60238 VL - 9 KW - hypertension KW - causal inference KW - wearable physiological signals KW - electrocardiogram KW - photoplethysmogram N2 - Background: Hypertension is a leading cause of cardiovascular disease and premature death worldwide, and it puts a heavy burden on the health care system. Therefore, it is very important to detect and evaluate hypertension and related cardiovascular events to enable early prevention, detection, and management. Hypertension can be detected in a timely manner with cardiac signals, such as through an electrocardiogram (ECG) and photoplethysmogram (PPG), which can be observed via wearable sensors. Most previous studies predicted hypertension from ECG and PPG signals with extracted features that are correlated with hypertension. However, correlation is sometimes unreliable and may be affected by confounding factors. Objective: The aim of this study was to investigate the feasibility of predicting the risk of hypertension by exploring features that are causally related to hypertension via causal inference methods. Additionally, we paid special attention to and verified the reliability and effectiveness of causality compared to correlation. Methods: We used a large public dataset from the Aurora Project, which was conducted by Microsoft Research. The dataset included diverse individuals who were balanced in terms of gender, age, and the condition of hypertension, with their ECG and PPG signals simultaneously acquired with wrist-worn wearable devices. We first extracted 205 features from the ECG and PPG signals, calculated 6 statistical metrics for these 205 features, and selected some valuable features out of the 205 features under each statistical metric. Then, 6 causal graphs of the selected features for each kind of statistical metric and hypertension were constructed with the equivalent greedy search algorithm. We further fused the 6 causal graphs into 1 causal graph and identified features that were causally related to hypertension from the causal graph. Finally, we used these features to detect hypertension via machine learning algorithms. Results: We validated the proposed method on 405 subjects. We identified 24 causal features that were associated with hypertension. The causal features could detect hypertension with an accuracy of 89%, precision of 92%, and recall of 82%, which outperformed detection with correlation features (accuracy of 85%, precision of 88%, and recall of 77%). Conclusions: The results indicated that the causal inference?based approach can potentially clarify the mechanism of hypertension detection with noninvasive signals and effectively detect hypertension. It also revealed that causality can be more reliable and effective than correlation for hypertension detection and other application scenarios. UR - https://cardio.jmir.org/2025/1/e60238 UR - http://dx.doi.org/10.2196/60238 ID - info:doi/10.2196/60238 ER - TY - JOUR AU - Scholes, Shaun AU - Mindell, S. Jennifer AU - Toomse-Smith, Mari AU - Cois, Annibale AU - Adjaye-Gbewonyo, Kafui PY - 2025/1/20 TI - Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) Study: Repeated Cross-Sectional Study JO - JMIR Cardio SP - e64893 VL - 9 KW - data harmonization KW - cardiovascular disease KW - CVD KW - CVD risk scores KW - trends KW - cross-country comparisons KW - public health KW - England KW - South Africa N2 - Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. Demographic, behavioral, socioeconomic, health care, and psychosocial variables considered risk factors for CVD are routinely measured in population health surveys, providing opportunities to examine health transitions. Studying the drivers of health transitions in countries where multiple burdens of disease persist (eg, South Africa), compared with countries regarded as models of ?epidemiologic transition? (eg, England), can provide knowledge on where best to intervene and direct resources to reduce the disease burden. Objective: The EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) study analyzes microlevel data collected from multiple nationally representative population health surveys conducted in these 2 countries between 1998 and 2017. Creating a harmonized dataset by pooling repeated cross-sectional surveys to model trends in CVD risk is challenging due to changes in aspects such as survey content, question wording, inclusion of boost samples, weighting, measuring equipment, and guidelines for data protection. This study aimed to create a harmonized dataset based on the annual Health Surveys for England to estimate trends in mean predicted 10-year CVD risk (primary outcome) and its individual risk components (secondary outcome). Methods: We compiled a harmonized dataset to estimate trends between 1998 and 2017 in the English adult population, including the primary and secondary outcomes, and potential drivers of those trends. Laboratory- and non?laboratory-based World Health Organization (WHO) and Globorisk algorithms were used to calculate the predicted 10-year total (fatal and nonfatal) CVD risk. Sex-specific estimates of the mean 10-year CVD risk and its components by survey year were calculated, accounting for the complex survey design. Results: Laboratory- and non?laboratory-based 10-year CVD risk scores were calculated for 33,628 and 61,629 participants aged 40 to 74 years, respectively. The absolute predicted 10-year risk of CVD declined significantly on average over the last 2 decades in both sexes (for linear trend; all P<.001). In men, the mean of the laboratory-based WHO risk score was 10.1% (SE 0.2%) and 8.4% (SE 0.2%) in 1998 and 2017, respectively; corresponding figures in women were 5.6% (SE 0.1%) and 4.5% (SE 0.1%). In men, the mean of the non?laboratory-based WHO risk score was 9.6% (SE 0.1%) and 8.9% (SE 0.2%) in 1998 and 2017, respectively; corresponding figures in women were 5.8% (SE 0.1%) and 4.8% (SE 0.1%). Predicted CVD risk using the Globorisk algorithms was lower on average in absolute terms, but the pattern of change was very similar. Trends in the individual risk components showed a complex pattern. Conclusions: Harmonized data from repeated cross-sectional health surveys can be used to quantify the drivers of recent changes in CVD risk at the population level. UR - https://cardio.jmir.org/2025/1/e64893 UR - http://dx.doi.org/10.2196/64893 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/64893 ER - TY - JOUR AU - Seringa, Joana AU - Hirata, Anna AU - Pedro, Rita Ana AU - Santana, Rui AU - Magalhães, Teresa PY - 2025/1/20 TI - Health Care Professionals and Data Scientists? Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study JO - J Med Internet Res SP - e54990 VL - 27 KW - heart failure KW - machine learning system KW - decompensation KW - qualitative research KW - cardiovascular diseases KW - heart failure management KW - interview N2 - Background: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantial health care costs related to this condition. Objective: This study aimed to explore the perspectives of health care professionals and data scientists regarding the relevance, challenges, and potential benefits of using machine learning (ML) models to predict decompensation from patients with HF. Methods: A total of 13 individual, semistructured, qualitative interviews were conducted in Portugal between October 31, 2022, and June 23, 2023. Participants represented different health care specialties and were selected from different contexts and regions of the country to ensure a comprehensive understanding of the topic. Data saturation was determined as the point at which no new themes emerged from participants? perspectives, ensuring a sufficient sample size for analysis. The interviews were audio recorded, transcribed, and analyzed using MAXQDA (VERBI Software GmbH) through a reflexive thematic analysis. Two researchers (JS and AH) coded the interviews to ensure the consistency of the codes. Ethical approval was granted by the NOVA National School of Public Health ethics committee (CEENSP 14/2022), and informed consent was obtained from all participants. Results: The participants recognized the potential benefits of ML models for early detection, risk stratification, and personalized care of patients with HF. The importance of selecting appropriate variables for model development, such as rapid weight gain and symptoms, was emphasized. The use of wearables for recording vital signs was considered necessary, although challenges related to adoption among older patients were identified. Risk stratification emerged as a crucial aspect, with the model needing to identify patients at high-, medium-, and low-risk levels. Participants emphasized the need for a response model involving health care professionals to validate ML-generated alerts and determine appropriate interventions. Conclusions: The study?s findings highlight ML models? potential benefits and challenges for predicting HF decompensation. The relevance of ML models for improving patient outcomes, reducing health care costs, and promoting patient engagement in disease management is highlighted. Adequate variable selection, risk stratification, and response models were identified as essential components for the effective implementation of ML models in health care. In addition, the study identified technical, regulatory and ethical, and adoption and acceptance challenges that need to be overcome for the successful integration of ML models into clinical workflows. Interpretation of the findings suggests that future research should focus on more extensive and diverse samples, incorporate the patient perspective, and explore the impact of ML models on patient outcomes and personalized care in HF management. Incorporation of this study?s findings into practice is expected to contribute to developing and implementing ML-based predictive models that positively impact HF management. UR - https://www.jmir.org/2025/1/e54990 UR - http://dx.doi.org/10.2196/54990 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/54990 ER - TY - JOUR AU - Kirkham, M. Aidan AU - Fergusson, A. Dean AU - Presseau, Justin AU - McIsaac, I. Daniel AU - Shorr, Risa AU - Roberts, J. Derek PY - 2025/1/16 TI - Strategies to Improve Health Care Provider Prescription of and Patient Adherence to Guideline-Recommended Cardiovascular Medications for Atherosclerotic Occlusive Disease: Protocol for Two Systematic Reviews and Meta-Analyses of Randomized Controlled Trials JO - JMIR Res Protoc SP - e60326 VL - 14 KW - coronary artery disease KW - cerebrovascular disease KW - peripheral artery disease KW - polyvascular disease KW - underprescription KW - nonadherence KW - implementation strategy KW - adherence-supporting strategy KW - statins KW - antiplatelets KW - antihypertensives KW - guideline-recommended medications KW - implementation KW - atherosclerosis KW - patient adherence KW - RCT KW - randomized controlled trials KW - PRISMA N2 - Background: In patients with atherosclerotic occlusive diseases, systematic reviews and meta-analyses of randomized controlled trials (RCTs) report that antiplatelets, statins, and antihypertensives reduce the risk of major adverse cardiac events, need for revascularization procedures, mortality, and health care resource use. However, evidence suggests that these patients are not prescribed these medications adequately or do not adhere to them once prescribed. Objective: We aim to systematically review and meta-analyze RCTs examining the effectiveness of implementation or adherence-supporting strategies for improving health care provider prescription of, or patient adherence to, guideline-recommended cardiovascular medications in patients with atherosclerotic occlusive disease. Methods: We designed and reported the protocol according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis-Protocols) statement. We will search MEDLINE, Embase, The Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL from their inception. RCTs examining implementation or adherence-supporting strategies for improving prescription of, or adherence to, guideline-recommended cardiovascular medications in adults with cerebrovascular disease, coronary artery disease, peripheral artery disease, or polyvascular disease (>1 of these diseases) will be included. Two investigators will independently review identified titles/abstracts and full-text studies, extract data, assess the risk of bias (using the Cochrane tool), and classify implementation or adherence-supporting strategies using the refined Cochrane Effective Practice and Organization of Care (EPOC) taxonomy (for strategies aimed at improving prescription) and Behavior Change Wheel (BCW; for adherence-supporting strategies). We will narratively synthesize data describing which implementation or adherence-supporting strategies have been evaluated across RCTs, and their reported effectiveness at improving prescription of, or adherence to, guideline-recommended cardiovascular medications (primary outcomes) and patient-important outcomes and health care resource use (secondary outcomes) within refined EPOC taxonomy levels and BCW interventions and policies. Where limited clinical heterogeneity exists between RCTs, estimates describing the effectiveness of implementation or adherence-supporting strategies within different refined EPOC taxonomy levels and BCW interventions and policies will be pooled using random-effects models. Stratified meta-analyses and meta-regressions will assess if strategy effectiveness varies by recruited patient populations, prescriber types, clinical practice settings, and study design characteristics. GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) will be used to communicate evidence certainty. Results: The search was completed on June 6, 2023. Database searches and the PubMed ?related articles? feature identified 4319 unique citations for title/abstract screening. We are currently screening titles/abstracts. Conclusions: These studies will identify which implementation and adherence-supporting strategies are being used (and in which combinations) across RCTs for improving the prescription of, or adherence to, guideline-recommended cardiovascular medications in adults with atherosclerotic occlusive diseases. They will also determine the effectiveness of currently trialed implementation and adherence-supporting strategies, and whether effectiveness varies by patient, prescriber, or clinical practice setting traits. Trial Registration: PROSPERO CRD42023461317; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=461317; PROSPERO CRD42023461299; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=461299 UR - https://www.researchprotocols.org/2025/1/e60326 UR - http://dx.doi.org/10.2196/60326 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60326 ER - TY - JOUR AU - You, Yuzi AU - Liang, Wei AU - Zhao, Yajie PY - 2025/1/15 TI - Development and Validation of a Predictive Model Based on Serum Silent Information Regulator 6 Levels in Chinese Older Adult Patients: Cross-Sectional Descriptive Study JO - JMIR Aging SP - e64374 VL - 8 KW - aging KW - coronary artery disease KW - nomogram KW - SIRT6 KW - TyG index KW - silent information regulator 6 KW - triglyceride glucose index N2 - Background: Serum levels of silent information regulator 6 (SIRT6), a key biomarker of aging, were identified as a predictor of coronary artery disease (CAD), but whether SIRT6 can distinguish severity of coronary artery lesions in older adult patients is unknown. Objectives: This study developed a nomogram to demonstrate the functionality of SIRT6 in assessing severity of coronary artery atherosclerosis. Methods: Patients aged 60 years and older with angina pectoris were screened for this single-center clinical study between October 1, 2022, and March 31, 2023. Serum specimens of eligible patients were collected for SIRT6 detection by enzyme-linked immunosorbent assay. Clinical data and putative predictors, including 29 physiological characteristics, biochemical parameters, carotid artery ultrasonographic results, and complete coronary angiography findings, were evaluated, with CAD diagnosis as the primary outcome. The nomogram was derived from the Extreme Gradient Boosting (XGBoost) model, with logistic regression for variable selection. Model performance was assessed by examining discrimination, calibration, and clinical use separately. A 10-fold cross-validation technique was used to compare all models. The models? performance was further evaluated on the internal validation set to ensure that the obtained results were not due to overoptimization. Results: Eligible patients (n=222) were divided into 2 cohorts: the development cohort (n=178) and the validation cohort (n=44). Serum SIRT6 levels were identified as both an independent risk factor and a predictor for CAD in older adults. The area under the receiver operating characteristic curve (AUROC) was 0.725 (95% CI 0.653?0.797). The optimal cutoff value of SIRT6 for predicting CAD was 546.384 pg/mL. Predictors included in this nomogram were serum SIRT6 levels, triglyceride glucose (TyG) index, and apolipoprotein B. The model achieved an AUROC of 0.956 (95% CI 0.928?0.983) in the development cohort. Similarly, in the internal validation cohort, the AUROC was 0.913 (95% CI 0.828?0.999). All models demonstrated satisfactory calibration, with predicted outcomes closely aligning with actual results. Conclusions: SIRT6 shows promise in predicting CAD, with enhanced predictive abilities when combined with the TyG index. In clinical settings, monitoring fluctuations in SIRT6 and TyG may offer valuable insights for early CAD detection. The nomogram for CAD outcome prediction in older adult patients with angina pectoris may aid in clinical trial design and personalized clinical decision-making, particularly in institutions where SIRT6 is being explored as a biomarker for aging or cardiovascular health. UR - https://aging.jmir.org/2025/1/e64374 UR - http://dx.doi.org/10.2196/64374 ID - info:doi/10.2196/64374 ER - TY - JOUR AU - Gong, Chan-Juan AU - Zhou, Xiao-Kai AU - Zhang, Zhen-Feng AU - Fang, Yin PY - 2025/1/13 TI - Impact of Preventive Intravenous Amiodarone on Reperfusion Ventricular Fibrillation in Patients With Left Ventricular Hypertrophy Undergoing Open-Heart Surgery: Randomized Controlled Clinical Trial JO - JMIR Form Res SP - e64586 VL - 9 KW - amiodarone KW - left ventricular hypertrophy KW - reperfusion ventricular fibrillation KW - open-heart surgery KW - randomized controlled trial KW - RCT KW - clinical trial KW - ventricular fibrillation KW - vicious arrhythmia KW - aortic cross-clamp KW - surgery KW - effectiveness KW - defibrillation N2 - Background: Ventricular fibrillation (VF) is a vicious arrhythmia usually generated after removal of the aortic cross-clamp (ACC) in patients undergoing open-heart surgery, which could damage cardiomyocytes, especially in patients with left ventricular hypertrophy (LVH). Amiodarone has the prominent properties of converting VF and restoring sinus rhythm. However, few studies concentrated on the effect of amiodarone before ACC release on reducing VF in patients with LVH. Objective: The study was designed to explore the effectiveness of prophylactic intravenous amiodarone in reducing VF after the release of the ACC in patients with LVH. Methods: A total of 54 patients with LVH scheduled for open-heart surgery were enrolled and randomly divided (1:1) into 2 groups?group A (amiodarone group) and group P (placebo-controlled group). Thirty minutes before removal of the ACC, the trial drugs were administered intravenously. In group A, 150 mg of amiodarone was pumped in 15 minutes. In group P, the same volume of normal saline was pumped in 15 minutes. The primary outcome was the incidence of VF 10 minutes after removal of the ACC. Results: The incidence of VF was lower in group A than in group P (30% vs 70%, P=.003). The duration of VF, the number of defibrillations, and the defibrillation energy were also lower in group A than in group P (P<.001, P=.002, and P=.002, respectively). After the end of cardiopulmonary bypass, the heart rate and mean arterial pressure were lower in group A, and the mean pulmonary arterial pressure and the dose of vasoactive drugs were higher than those in group P (P<.001, P<.001, P=.04, and P=.02, respectively). However, there were no significant differences in the use of vasoactive-inotropic agents and hemodynamic status between the 2 groups before the end of surgery. Conclusions: In patients with LVH who undergo open-heart surgery, amiodarone can be safely used to reduce the incidence of VF, the duration of VF, the frequency of defibrillation, and the energy of defibrillation after ACC removal. Trial Registration: Chinese Clinical Trial Registry ChiCTR2000035057; https://www.chictr.org.cn/showprojEN.html?proj=57145 UR - https://formative.jmir.org/2025/1/e64586 UR - http://dx.doi.org/10.2196/64586 ID - info:doi/10.2196/64586 ER - TY - JOUR AU - Yang, Xiaomeng AU - Li, Zeyan AU - Lei, Lei AU - Shi, Xiaoyu AU - Zhang, Dingming AU - Zhou, Fei AU - Li, Wenjing AU - Xu, Tianyou AU - Liu, Xinyu AU - Wang, Songyun AU - Yuan, Quan AU - Yang, Jian AU - Wang, Xinyu AU - Zhong, Yanfei AU - Yu, Lilei PY - 2025/1/7 TI - Noninvasive Oral Hyperspectral Imaging?Driven Digital Diagnosis of Heart Failure With Preserved Ejection Fraction: Model Development and Validation Study JO - J Med Internet Res SP - e67256 VL - 27 KW - heart failure with preserved ejection fraction KW - HFpEF KW - hyperspectral imaging KW - HSI KW - diagnostic model KW - digital health KW - Shapley Additive Explanations KW - SHAP KW - machine learning KW - artificial intelligence KW - AI KW - cardiovascular disease KW - predictive modeling KW - oral health N2 - Background: Oral microenvironmental disorders are associated with an increased risk of heart failure with preserved ejection fraction (HFpEF). Hyperspectral imaging (HSI) technology enables the detection of substances that are visually indistinguishable to the human eye, providing a noninvasive approach with extensive applications in medical diagnostics. Objective: The objective of this study is to develop and validate a digital, noninvasive oral diagnostic model for patients with HFpEF using HSI combined with various machine learning algorithms. Methods: Between April 2023 and August 2023, a total of 140 patients were recruited from Renmin Hospital of Wuhan University to serve as the training and internal testing groups for this study. Subsequently, from August 2024 to September 2024, an additional 35 patients were enrolled from Three Gorges University and Yichang Central People?s Hospital to constitute the external testing group. After preprocessing to ensure image quality, spectral and textural features were extracted from the images. We extracted 25 spectral bands from each patient image and obtained 8 corresponding texture features to evaluate the performance of 28 machine learning algorithms for their ability to distinguish control participants from participants with HFpEF. The model demonstrating the optimal performance in both internal and external testing groups was selected to construct the HFpEF diagnostic model. Hyperspectral bands significant for identifying participants with HFpEF were identified for further interpretative analysis. The Shapley Additive Explanations (SHAP) model was used to provide analytical insights into feature importance. Results: Participants were divided into a training group (n=105), internal testing group (n=35), and external testing group (n=35), with consistent baseline characteristics across groups. Among the 28 algorithms tested, the random forest algorithm demonstrated superior performance with an area under the receiver operating characteristic curve (AUC) of 0.884 and an accuracy of 82.9% in the internal testing group, as well as an AUC of 0.812 and an accuracy of 85.7% in the external testing group. For model interpretation, we used the top 25 features identified by the random forest algorithm. The SHAP analysis revealed discernible distinctions between control participants and participants with HFpEF, thereby validating the diagnostic model?s capacity to accurately identify participants with HFpEF. Conclusions: This noninvasive and efficient model facilitates the identification of individuals with HFpEF, thereby promoting early detection, diagnosis, and treatment. Our research presents a clinically advanced diagnostic framework for HFpEF, validated using independent data sets and demonstrating significant potential to enhance patient care. Trial Registration: China Clinical Trial Registry ChiCTR2300078855; https://www.chictr.org.cn/showproj.html?proj=207133 UR - https://www.jmir.org/2025/1/e67256 UR - http://dx.doi.org/10.2196/67256 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/67256 ER - TY - JOUR AU - Foti, Kathryn AU - Hubbard, Demetria AU - Smith, A. Kimberly AU - Hearld, Larry AU - Richman, Joshua AU - Horton, Trudi AU - Parker, Sharon AU - Roughton, Dodey AU - Craft, Macie AU - Clarkson, A. Stephen AU - Jackson, A. Elizabeth AU - Cherrington, L. Andrea PY - 2024/12/20 TI - Improving Blood Pressure Control and Tobacco Use Cessation Intervention In Primary Care: Protocol for the Alabama Cardiovascular Cooperative Heart Health Improvement Project JO - JMIR Res Protoc SP - e63685 VL - 13 KW - hypertension KW - primary care KW - quality improvement KW - tobacco use KW - smoking cessation KW - healthcare quality KW - quality of care KW - risk modification KW - cardiovascular disease prevention N2 - Background: Alabama has the second highest rate of cardiovascular disease (CVD) mortality of any US state and a high prevalence of CVD risk factors such as hypertension, diabetes, obesity, and smoking. Within the state, there are disparities in CVD outcomes and risk factors by race or ethnicity and geography. Many primary care practices do not have the capacity for full-scale quality improvement (QI) initiatives. The Alabama Cardiovascular Cooperative (ALCC), which includes academic and community stakeholders, was formed to support primary care practices to implement QI initiatives to improve cardiovascular health. The ALCC is implementing a Heart Health Improvement Project (HHIP) in primary care practices with suboptimal rates of blood pressure (BP) control and tobacco use screening. Objective: The study aimed to support primary care practices to increase BP control among adults with hypertension and increase rates of tobacco use screening and cessation intervention. Methods: We are using a type 1 hybrid design to test the effects of the HHIP on BP control among adults with hypertension and tobacco use screening and cessation intervention, while collecting information on implementation. Primary care practices were recruited through existing practice networks and additional electronic and in-person outreach. To ensure participation from a broad range of clinics, we required at least 50% of practices to be Federally Qualified Health Centers or look-alikes and to include representation from practices in rural areas. At baseline, we collected information about practice characteristics and preintervention rates of BP control and tobacco use screening and cessation intervention. The QI intervention includes quarterly activities conducted over a 12-month period. The HHIP uses a multipronged approach to QI, including practice facilitation and technical assistance, on-site and e-learning, and improvement through data transparency. We will conduct a pre-post analysis to estimate the effects of the HHIP and whether there is an enduring change in outcomes after the 12 months of HHIP activities beyond what would be expected due to secular trends. Results: Practice recruitment took place between April 2021 and October 2022. After contacting 417 primary care practices, 51 were enrolled, including 28 Federally Qualified Health Centers or look-alikes; 47 practices implemented the HHIP. Among 45 practices that completed the baseline survey, 11 (24%) were solo practices, while 28 (62%) had 1-5 clinicians, and 6 (13%) had 6 or more clinicians. The median number of patient visits per year was 5819 (IQR 3707.3-8630.5). Practices had been in operation for a mean of 19.2 (SD 13.0) years. At baseline, the mean BP control rate was 49.6% and the rate of tobacco use screening and cessation intervention was 67.4%. Conclusions: If successful, the ALCC and HHIP may improve the implementation of evidence-based guidelines in primary care and, subsequently, cardiovascular health and health equity in the state of Alabama. International Registered Report Identifier (IRRID): DERR1-10.2196/63685 UR - https://www.researchprotocols.org/2024/1/e63685 UR - http://dx.doi.org/10.2196/63685 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/63685 ER - TY - JOUR AU - Gagnon, Marie-Pierre AU - Ouellet, Steven AU - Attisso, Eugène AU - Supper, Wilfried AU - Amil, Samira AU - Rhéaume, Caroline AU - Paquette, Jean-Sébastien AU - Chabot, Christian AU - Laferrière, Marie-Claude AU - Sasseville, Maxime PY - 2024/12/9 TI - Wearable Devices for Supporting Chronic Disease Self-Management: Scoping Review JO - Interact J Med Res SP - e55925 VL - 13 KW - chronic diseases KW - self-care KW - self-management KW - empowerment KW - mobile health KW - mHealth KW - wearable KW - devices KW - scoping KW - review KW - mobile phone KW - PRISMA N2 - Background: People with chronic diseases can benefit from wearable devices in managing their health and encouraging healthy lifestyle habits. Wearables such as activity trackers or blood glucose monitoring devices can lead to positive health impacts, including improved physical activity adherence or better management of type 2 diabetes. Few literature reviews have focused on the intersection of various chronic diseases, the wearable devices used, and the outcomes evaluated in intervention studies, particularly in the context of primary health care. Objective: This study aims to identify and describe (1) the chronic diseases represented in intervention studies, (2) the types or combinations of wearables used, and (3) the health or health care outcomes assessed and measured. Methods: We conducted a scoping review following the Joanna Briggs Institute guidelines, searching the MEDLINE and Web of Science databases for studies published between 2012 and 2022. Pairs of reviewers independently screened titles and abstracts, applied the selection criteria, and performed full-text screening. We included interventions using wearables that automatically collected and transmitted data to adult populations with at least one chronic disease. We excluded studies with participants with only a predisposition to develop a chronic disease, hospitalized patients, patients with acute diseases, patients with active cancer, and cancer survivors. We included randomized controlled trials and cohort, pretest-posttest, observational, mixed methods, and qualitative studies. Results: After the removal of 1987 duplicates, we screened 4540 titles and abstracts. Of the remaining 304 articles after exclusions, we excluded 215 (70.7%) full texts and included 89 (29.3%). Of these 89 texts, 10 (11%) were related to the same interventions as those in the included studies, resulting in 79 studies being included. We structured the results according to chronic disease clusters: (1) diabetes, (2) heart failure, (3) other cardiovascular conditions, (4) hypertension, (5) multimorbidity and other combinations of chronic conditions, (6) chronic obstructive pulmonary disease, (7) chronic pain, (8) musculoskeletal conditions, and (9) asthma. Diabetes was the most frequent health condition (18/79, 23% of the studies), and wearable activity trackers were the most used (42/79, 53% of the studies). In the 79 included studies, 74 clinical, 73 behavioral, 36 patient technology experience, 28 health care system, and 25 holistic or biopsychosocial outcomes were reported. Conclusions: This scoping review provides an overview of the wearable devices used in chronic disease self-management intervention studies, revealing disparities in both the range of chronic diseases studied and the variety of wearable devices used. These findings offer researchers valuable insights to further explore health care outcomes, validate the impact of concomitant device use, and expand their use to other chronic diseases. Trial Registration: Open Science Framework Registries (OSF) s4wfm; https://osf.io/s4wfm UR - https://www.i-jmr.org/2024/1/e55925 UR - http://dx.doi.org/10.2196/55925 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/55925 ER - TY - JOUR AU - Zheng, Yaguang AU - Adhikari, Samrachana AU - Li, Xiyue AU - Zhao, Yunan AU - Mukhopadhyay, Amrita AU - Hamo, E. Carine AU - Stokes, Tyrel AU - Blecker, Saul PY - 2024/12/5 TI - Association Between Video-Based Telemedicine Visits and Medication Adherence Among Patients With Heart Failure: Retrospective Cross-Sectional Study JO - JMIR Cardio SP - e56763 VL - 8 KW - telemedicine KW - medication adherence KW - heart failure KW - systolic dysfunction KW - medical therapy KW - telehealth KW - remote monitoring KW - self-management N2 - Background: Despite the exponential growth in telemedicine visits in clinical practice due to the COVID-19 pandemic, it remains unknown if telemedicine visits achieved similar adherence to prescribed medications as in-person office visits for patients with heart failure. Objective: Our study examined the association between telemedicine visits (vs in-person visits) and medication adherence in patients with heart failure. Methods: This was a retrospective cross-sectional study of adult patients with a diagnosis of heart failure or an ejection fraction of ?40% using data between April 1 and October 1, 2020. This period was used because New York University approved telemedicine visits for both established and new patients by April 1, 2020. The time zero window was between April 1 and October 1, 2020, then each identified patient was monitored for up to 180 days. Medication adherence was measured by the mean proportion of days covered (PDC) within 180 days, and categorized as adherent if the PDC was ?0.8. Patients were included in the telemedicine exposure group or in-person group if all encounters were video visits or in-person office visits, respectively. Poisson regression and logistic regression models were used for the analyses. Results: A total of 9521 individuals were included in this analysis (telemedicine visits only: n=830 in-person office visits only: n=8691). Overall, the mean age was 76.7 (SD 12.4) years. Most of the patients were White (n=6996, 73.5%), followed by Black (n=1060, 11.1%) and Asian (n=290, 3%). Over half of the patients were male (n=5383, 56.5%) and over half were married or living with partners (n=4914, 51.6%). Most patients? health insurance was covered by Medicare (n=7163, 75.2%), followed by commercial insurance (n=1687, 17.7%) and Medicaid (n=639, 6.7%). Overall, the average PDC was 0.81 (SD 0.286) and 71.3% (6793/9521) of patients had a PDC?0.8. There was no significant difference in mean PDC between the telemedicine and in-person office groups (mean 0.794, SD 0.294 vs mean 0.812, SD 0.285) with a rate ratio of 0.99 (95% CI 0.96-1.02; P=.09). Similarly, there was no significant difference in adherence rates between the telemedicine and in-person office groups (573/830, 69% vs 6220/8691, 71.6%), with an odds ratio of 0.94 (95% CI 0.81-1.11; P=.12). The conclusion remained the same after adjusting for covariates (eg, age, sex, race, marriage, language, and insurance). Conclusions: We found similar rates of medication adherence among patients with heart failure who were being seen via telemedicine or in-person visits. Our findings are important for clinical practice because we provide real-world evidence that telemedicine can be an approach for outpatient visits for patients with heart failure. As telemedicine is more convenient and avoids transportation issues, it may be an alternative way to maintain the same medication adherence as in-person visits for patients with heart failure. UR - https://cardio.jmir.org/2024/1/e56763 UR - http://dx.doi.org/10.2196/56763 ID - info:doi/10.2196/56763 ER - TY - JOUR AU - Mardini, T. Mamoun AU - Bai, Chen AU - Bavry, A. Anthony AU - Zaghloul, Ahmed AU - Anderson, David R. AU - Price, Crenshaw Catherine E. AU - Al-Ani, Z. Mohammad A. PY - 2024/11/27 TI - Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study JO - JMIR Aging SP - e58980 VL - 7 KW - transcatheter aortic valve replacement KW - frailty KW - cardiology KW - machine learning KW - TAVR KW - minimally invasive surgery KW - cardiac surgery KW - real-world data KW - topic modeling KW - clinical notes KW - electronic health record KW - EHR N2 - Background: Transcatheter aortic valve replacement (TAVR) is a commonly used treatment for severe aortic stenosis. As degenerative aortic stenosis is primarily a disease afflicting older adults, a frailty assessment is essential to patient selection and optimal periprocedural outcomes. Objective: This study aimed to enhance frailty assessments of TAVR candidates by integrating real-world structured and unstructured data. Methods: This study analyzed data from 14,000 patients between January 2018 and December 2019 to assess frailty in TAVR patients at the University of Florida. Frailty was identified using the Fried criteria, which includes weight loss, exhaustion, walking speed, grip strength, and physical activity. Latent Dirichlet allocation for topic modeling and Extreme Gradient Boosting for frailty prediction were applied to unstructured clinical notes and structured electronic health record (EHR) data. We also used least absolute shrinkage and selection operator regression for feature selection. Model performance was rigorously evaluated using nested cross-validation, ensuring the generalizability of the findings. Results: Model performance was significantly improved by combining unstructured clinical notes with structured EHR data, achieving an area under the receiver operating characteristic curve of 0.82 (SD 0.07), which surpassed the EHR-only model?s area under the receiver operating characteristic curve of 0.64 (SD 0.08). The Shapley Additive Explanations analysis found that congestive heart failure management, back problems, and atrial fibrillation were the top frailty predictors. Additionally, the latent Dirichlet allocation topic modeling identified 7 key topics, highlighting the role of specific medical treatments in predicting frailty. Conclusions: Integrating unstructured clinical notes and structured EHR data led to a notable enhancement in predicting frailty. This method shows great potential for standardizing frailty assessments using real-world data and improving patient selection for TAVR. UR - https://aging.jmir.org/2024/1/e58980 UR - http://dx.doi.org/10.2196/58980 ID - info:doi/10.2196/58980 ER - TY - JOUR AU - Cavero-Redondo, Iván AU - Martinez-Rodrigo, Arturo AU - Saz-Lara, Alicia AU - Moreno-Herraiz, Nerea AU - Casado-Vicente, Veronica AU - Gomez-Sanchez, Leticia AU - Garcia-Ortiz, Luis AU - Gomez-Marcos, A. Manuel AU - PY - 2024/11/25 TI - Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning?Based Multicohort (RIGIPREV) Study JO - J Med Internet Res SP - e54357 VL - 26 KW - antihypertensive KW - drugs KW - models KW - patients KW - pulse wave velocity KW - recommendations KW - hypertension KW - machine learning KW - drug recommendations KW - arterial stiffness KW - RIGIPREV N2 - Background: High systolic blood pressure is one of the leading global risk factors for mortality, contributing significantly to cardiovascular diseases. Despite advances in treatment, a large proportion of patients with hypertension do not achieve optimal blood pressure control. Arterial stiffness (AS), measured by pulse wave velocity (PWV), is an independent predictor of cardiovascular events and overall mortality. Various antihypertensive drugs exhibit differential effects on PWV, but the extent to which these effects vary depending on individual patient characteristics is not well understood. Given the complexity of selecting the most appropriate antihypertensive medication for reducing PWV, machine learning (ML) techniques offer an opportunity to improve personalized treatment recommendations. Objective: This study aims to develop an ML model that provides personalized recommendations for antihypertensive medications aimed at reducing PWV. The model considers individual patient characteristics, such as demographic factors, clinical data, and cardiovascular measurements, to identify the most suitable antihypertensive agent for improving AS. Methods: This study, known as the RIGIPREV study, used data from the EVA, LOD-DIABETES, and EVIDENT studies involving individuals with hypertension with baseline and follow-up measurements. Antihypertensive drugs were grouped into classes such as angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), ?-blockers, diuretics, and combinations of diuretics with ACEIs or ARBs. The primary outcomes were carotid-femoral and brachial-ankle PWV, while the secondary outcomes included various cardiovascular, anthropometric, and biochemical parameters. A multioutput regressor using 6 random forest models was used to predict the impact of each antihypertensive class on PWV reduction. Model performance was evaluated using the coefficient of determination (R2) and mean squared error. Results: The random forest models exhibited strong predictive capabilities, with internal validation yielding R2 values between 0.61 and 0.74, while external validation showed a range of 0.26 to 0.46. The mean squared values ranged from 0.08 to 0.22 for internal validation and from 0.29 to 0.45 for external validation. Variable importance analysis revealed that glycated hemoglobin and weight were the most critical predictors for ACEIs, while carotid-femoral PWV and total cholesterol were key variables for ARBs. The decision tree model achieved an accuracy of 84.02% in identifying the most suitable antihypertensive drug based on individual patient characteristics. Furthermore, the system?s recommendations for ARBs matched 55.3% of patients? original prescriptions. Conclusions: This study demonstrates the utility of ML techniques in providing personalized treatment recommendations for antihypertensive therapy. By accounting for individual patient characteristics, the model improves the selection of drugs that control blood pressure and reduce AS. These findings could significantly aid clinicians in optimizing hypertension management and reducing cardiovascular risk. However, further studies with larger and more diverse populations are necessary to validate these results and extend the model?s applicability. UR - https://www.jmir.org/2024/1/e54357 UR - http://dx.doi.org/10.2196/54357 UR - http://www.ncbi.nlm.nih.gov/pubmed/39585738 ID - info:doi/10.2196/54357 ER - TY - JOUR AU - Yu, Bin AU - Kravchenko, Julia AU - Yashkin, Arseniy AU - Akushevich, Igor PY - 2024/11/20 TI - Decomposition of Heart Failure Prevalence and Mortality Among Older Adults in the United States: Medicare-Based Partitioning Analysis JO - JMIR Public Health Surveill SP - e51989 VL - 10 KW - heart failure KW - prevalence KW - mortality KW - partitioning KW - time trends KW - epidemiologic determinants N2 - Background: Heart failure (HF) is a challenging clinical and public health problem characterized by high prevalence and mortality among US older adults, along with a recent decline in HF prevalence and increase in mortality. The changes of prevalence can be decomposed into pre-existing disease prevalence, disease incidence, and respective survival, while the changes of mortality can be decomposed into mortality in the general population independent from HF, pre-existing HF prevalence, incidence, and respective survival. These epidemiological components may contribute differently to the changes in prevalence and mortality. Objective: We aimed to investigate and compare the relative contributions of epidemiologic determinants in HF prevalence and mortality trends. Methods: This study was a secondary data analysis of 5% of Medicare claims data for 1992?2017 in the United States. Medicare is a federal health insurance program for older adults aged 65+ years as well as people with specific disabilities and end-stage renal disease. Age-adjusted prevalence and incidence-based mortality (IBM; all-cause mortality that occurred in patients with HF) were partitioned into their respective epidemiologic determinants using the partitioning analysis approach. Results: The age-adjusted HF prevalence (1/100 person-years) increased from 11 in 1994 to 14.6 in 2005, followed by a decline to 12.6 in 2017, and the age-adjusted HF IBM (1/100,000) increased from 2220.8 in 1994 to 2563.7 in 2000, then declined to 2075.9 in 2016, followed by an increase to 2094.7 in 2017. The HF incidence (1/1000 person-years) declined from 29.4 in 1992 to 19.9 in 2017. The 1-, 3-, and 5-year survival trend showed declines in recent years. Partitioning of HF prevalence showed three phases: (1) decelerated increasing prevalence (1994?2006), (2) accelerated declining prevalence (2007?2014), and (3) decelerated declining prevalence (2015?2017). During the whole period, the decreasing HF incidence contributed to the declines in prevalence, overpowering prevalence increases contributed from survival. Likewise, partitioning of HF IBM showed three phases: (1) decelerated increasing mortality (1994?2001), (2) accelerated declining mortality (2002?2012), and (3) decelerated declining mortality (2013?2017). The decreasing HF incidence in 1994?2017 and increasing survival in 2002?2006 contributed to the declines in mortality, while the decreasing survival in 2007?2017 contributed to the mortality increase. Conclusions: Decade-long declines in HF prevalence and mortality mainly reflected decreasing incidence, while the most recent increase of mortality was predominantly due to the declining survival. If current trends persist, HF prevalence and mortality are forecasted to grow substantially in the next decade. Prevention strategies should continue the prevention of HF risk factors as well as improvement of treatment and management of HF after diagnosis. UR - https://publichealth.jmir.org/2024/1/e51989 UR - http://dx.doi.org/10.2196/51989 ID - info:doi/10.2196/51989 ER - TY - JOUR AU - Zhang, Xiaoyun AU - Wang, Siyu AU - Yang, Qianqian AU - Zheng, Ruizhi AU - Wang, Long AU - Lin, Hong AU - Wang, Shuangyuan AU - Li, Mian AU - Wang, Tiange AU - Zhao, Zhiyun AU - Lu, Jieli AU - Xu, Min AU - Chen, Yuhong AU - Zheng, Jie AU - Dai, Meng AU - Zhang, Di AU - Wang, Weiqing AU - Ning, Guang AU - Bi, Yufang AU - Xu, Yu PY - 2024/11/20 TI - Sex Difference and Socioeconomic Inequity in Chinese People With Hypertension: National Cross-Sectional Survey Study JO - JMIR Public Health Surveill SP - e63144 VL - 10 KW - sex difference KW - socioeconomic inequity KW - blood pressure KW - hypertension KW - cross-sectional survey N2 - Background: Sex differences in blood pressure (BP) levels and hypertension are important and the role of socioeconomic status (SES) in sex differences in hypertension remains unclear. Objective: This study aimed to evaluate the impact of SES on sex differences of hypertension in a nationally representative survey study. Methods: A total of 98,658 participants aged ?18 years who have lived in their current residence for ?6 months were recruited from 162 study sites across mainland China. Sex was self-reported. Individual-level SES included the highest level of education and annual household income. Area-level SES included economic development status, urban/rural residency, and north/south location. Outcomes included levels of systolic and diastolic BP, and hypertension. Linear and Cox regression models were used to examine the associations between sex (women vs men) and BP characteristics stratified by individual or combined SES indicators. Results: Systolic and diastolic BP levels and the prevalence of hypertension were higher in men than in women. This sex difference was found across categories of SES with widened sex disparities in participants having more favorable SES. Significant multiplicative interaction effects of SES on the association of sex with BP characteristics were found. Women with improving SES were associated with lower BP and hypertension prevalence compared to men. For combined SES, a 9% (prevalence ratio 0.91, 95% CI 0.83-0.98) and a 30% lower probability (prevalence ratio 0.70, 95% CI 0.63-0.78) of having hypertension were found in women with an overall intermediate SES and high SES, respectively, compared to those with low SES, while no significant reduction was found in men. Conclusions: There are significant sex differences in BP characteristics and SES has a potent impact on the disparities. Sex-specific public health policies to alleviate socioeconomic inequalities, especially in women are important for the prevention of hypertension. UR - https://publichealth.jmir.org/2024/1/e63144 UR - http://dx.doi.org/10.2196/63144 ID - info:doi/10.2196/63144 ER - TY - JOUR AU - Farooq, Munawar AU - Al Jufaili, Mahmood AU - Hanjra, K. Faisal AU - Ahmad, Shabbir AU - Dababneh, Hanna Emad AU - Al Nahhas, Omar AU - Bashir, Khalid PY - 2024/11/12 TI - Bystander Response and Out-of-Hospital Cardiac Arrest Outcomes (Bro. Study) in 3 Gulf Countries: Protocol for a Prospective, Observational, International Collaboration Study JO - JMIR Res Protoc SP - e58780 VL - 13 KW - out-of-hospital cardiac arrest KW - cardiac arrest outcomes KW - bystander response KW - cardiopulmonary resuscitation KW - CPR KW - automated external defibrillator KW - AED KW - survival to discharge KW - emergency medical services KW - prehospital care KW - Utstein style N2 - Background: : Globally, there is significant variation in the out-of-hospital cardiac arrest (OHCA) survival rate. Early links in the chain of survival, including bystander cardiopulmonary resuscitation (CPR) and the use of an automated external defibrillator at the scene, are known to be of crucial importance, with strong evidence of increased survival rate with good neurological outcomes. The data from the Middle East are limited and report variable rates of bystander CPR and survival. It is crucial to get prospective, reliable data on bystander response in these regions to help plan interventions to improve bystander response and outcomes. Objective: This international collaborative study aims to describe the characteristics, including bystander interventions and outcomes, of OHCAs brought to hospitals enrolled in the study from Abu Dhabi, United Arab Emirates; Doha, Qatar; and Muscat, Oman. It also aims to describe the strength of the association between bystander response and OHCA outcomes, including the return of spontaneous circulation, survival to hospital admission, survival to discharge, and good neurological outcome at discharge in the local context of low bystander CPR rates. Methods: This multicenter, prospective, noninterventional observational study (Bro. Study) will be conducted at the emergency departments of 4 participating tertiary care hospitals in 3 countries. The data will be collected prospectively according to the Utstein style (a set of internationally accepted guidelines for uniform reporting of cardiac arrests) on demographic variables (age, sex, nationality, country, participating center, and comorbidities), peri?cardiac arrest variables (location, witnessed or not, bystander CPR, use of automated external defibrillator, time of emergency medical services arrival, initial rhythm, number of shocks, and time of prehospital CPR), and outcome variables (return of spontaneous circulation, survival to discharge, and neurological outcome at discharge and 3 months). Univariate and multivariate analysis with logistic regression models will be used to measure the strength of the association of bystander interventions with outcomes using SPSS (version 22). Results: Data collection began in November 2023 and will continue for 2 years, with publication expected by early 2026. Conclusions: Bystander response to an OHCA is critical to a favorable outcome. The reliable, baseline bystander CPR data will be a cornerstone in the team?s next planned projects, which are to qualitatively identify the barriers to bystander CPR, conduct a scoping review of community interventions in the Gulf and other Asian countries, and design and implement strategies to help improve the bystander CPR rate in the community. International Registered Report Identifier (IRRID): DERR1-10.2196/58780 UR - https://www.researchprotocols.org/2024/1/e58780 UR - http://dx.doi.org/10.2196/58780 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/58780 ER - TY - JOUR AU - An, Jinghui AU - Shi, Fengwu AU - Wang, Huajun AU - Zhang, Hang AU - Liu, Su PY - 2024/11/8 TI - Evaluating the Sensitivity of Wearable Devices in Posttranscatheter Aortic Valve Implantation Functional Assessment JO - JMIR Mhealth Uhealth SP - e65277 VL - 12 KW - aortic valve KW - implantation functional KW - wearable devices UR - https://mhealth.jmir.org/2024/1/e65277 UR - http://dx.doi.org/10.2196/65277 ID - info:doi/10.2196/65277 ER - TY - JOUR AU - Xu, Dandan AU - Xu, Dongmei AU - Wei, Lan AU - Bao, Zhipeng AU - Liao, Shengen AU - Zhang, Xinyue PY - 2024/11/5 TI - The Effectiveness of Remote Exercise Rehabilitation Based on the ?SCeiP? Model in Homebound Patients With Coronary Heart Disease: Randomized Controlled Trial JO - J Med Internet Res SP - e56552 VL - 26 KW - coronary heart disease KW - exercise rehabilitation KW - promotion strategy KW - home rehabilitation N2 - Background: While exercise rehabilitation is recognized as safe and effective, medium- to long-term compliance among patients with coronary heart disease (CHD) remains low. Therefore, promoting long-term adherence to exercise rehabilitation for these patients warrants significant attention. Objective: This study aims to investigate the impact of remote exercise rehabilitation on time investment and related cognitive levels in homebound patients with CHD. This study utilizes the SCeiP (Self-Evaluation/Condition of Exercise-Effect Perception-Internal Drive-Persistence Behavior) model, alongside WeChat and exercise bracelets. Methods: A total of 147 patients who underwent percutaneous coronary intervention in the cardiovascular department of a grade III hospital in Jiangsu Province from June 2022 to March 2023 were selected as study participants through convenience sampling. The patients were randomly divided into an experimental group and a control group. The experimental group received an exercise rehabilitation promotion strategy based on the ?SCeiP? model through WeChat and exercise bracelets, while the control group followed rehabilitation training according to a standard exercise rehabilitation guide. The days and duration of exercise, levels of cardiac rehabilitation cognition, exercise planning, and exercise input were analyzed before the intervention and at 1 month and 3 months after the intervention. Results: A total of 81 men (55.1%) and 66 women (44.9%) were recruited for the study. The completion rate of exercise days was significantly higher in the experimental group compared with the control group at both 1 month (t145=5.429, P<.001) and 3 months (t145=9.113, P<.001) after the intervention. Similarly, the completion rate of exercise duration was significantly greater in the experimental group (t145=3.471, P=.001) than in the control group (t145=5.574, P<.001). The levels of autonomy, exercise planning, and exercise input in the experimental group were significantly higher than those in the control group at both 1 month and 3 months after the intervention (P<.001). Additionally, the experimental group exhibited a significant reduction in both process anxiety and outcome anxiety scores (P<.001). Repeated measures ANOVA revealed significant differences in the trends of cognitive function related to cardiac rehabilitation between the 2 patient groups over time: autonomy, F1,145(time×group)=9.055 (P<.001); process anxiety, F1,145(time×group)=30.790 (P<.001); and outcome anxiety, F1,145(time×group)=28.186 (P<.001). As expected, the scores for exercise planning (t145=2.490, P=.01 and t145=3.379, P<.001, respectively) and exercise input (t145=2.255, P=.03 and t145=3.817, P<.001, respectively) consistently demonstrated superiority in the experimental group compared with the control group at both 1 and 3 months after the intervention. Interestingly, we observed that the levels of exercise planning and exercise input in both groups initially increased and then slightly decreased over time, although both remained higher than the preintervention levels (P<.001). Conclusions: The remote health intervention based on the ?SCeiP? model effectively enhances exercise compliance, exercise planning, exercise input, and cognitive levels during cardiac rehabilitation in patients with CHD. Trial Registration: Chinese Clinical Trial Registry ChiCTR2300069463; https://www.chictr.org.cn/showproj.html?proj=192461 UR - https://www.jmir.org/2024/1/e56552 UR - http://dx.doi.org/10.2196/56552 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/56552 ER - TY - JOUR AU - Hwang, Ha Seung AU - Lee, Hayeon AU - Lee, Hyuk Jun AU - Lee, Myeongcheol AU - Koyanagi, Ai AU - Smith, Lee AU - Rhee, Youl Sang AU - Yon, Keon Dong AU - Lee, Jinseok PY - 2024/11/5 TI - Machine Learning?Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan JO - J Med Internet Res SP - e52794 VL - 26 KW - machine learning KW - hypertension KW - cardiovascular disease KW - artificial intelligence KW - cause of death KW - cardiovascular risk KW - predictive analytics N2 - Background: Worldwide, cardiovascular diseases are the primary cause of death, with hypertension as a key contributor. In 2019, cardiovascular diseases led to 17.9 million deaths, predicted to reach 23 million by 2030. Objective: This study presents a new method to predict hypertension using demographic data, using 6 machine learning models for enhanced reliability and applicability. The goal is to harness artificial intelligence for early and accurate hypertension diagnosis across diverse populations. Methods: Data from 2 national cohort studies, National Health Insurance Service-National Sample Cohort (South Korea, n=244,814), conducted between 2002 and 2013 were used to train and test machine learning models designed to anticipate incident hypertension within 5 years of a health checkup involving those aged ?20 years, and Japanese Medical Data Center cohort (Japan, n=1,296,649) were used for extra validation. An ensemble from 6 diverse machine learning models was used to identify the 5 most salient features contributing to hypertension by presenting a feature importance analysis to confirm the contribution of each future. Results: The Adaptive Boosting and logistic regression ensemble showed superior balanced accuracy (0.812, sensitivity 0.806, specificity 0.818, and area under the receiver operating characteristic curve 0.901). The 5 key hypertension indicators were age, diastolic blood pressure, BMI, systolic blood pressure, and fasting blood glucose. The Japanese Medical Data Center cohort dataset (extra validation set) corroborated these findings (balanced accuracy 0.741 and area under the receiver operating characteristic curve 0.824). The ensemble model was integrated into a public web portal for predicting hypertension onset based on health checkup data. Conclusions: Comparative evaluation of our machine learning models against classical statistical models across 2 distinct studies emphasized the former?s enhanced stability, generalizability, and reproducibility in predicting hypertension onset. UR - https://www.jmir.org/2024/1/e52794 UR - http://dx.doi.org/10.2196/52794 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/52794 ER - TY - JOUR AU - Báez Gutiérrez, Nerea AU - Rodríguez Ramallo, Héctor AU - Mendoza-Zambrano, María Elva AU - Brown Arreola, Berenice AU - Santos Ramos, Bernardo AU - Abdel-kader Martín, Laila AU - Otero Candelera, Remedios PY - 2024/10/30 TI - Smartphone Apps for Pulmonary Hypertension: Systematic Search and Content Evaluation JO - JMIR Mhealth Uhealth SP - e57289 VL - 12 KW - pulmonary hypertension KW - mobile apps KW - smartphone KW - eHealth KW - mHealth KW - app KW - hypertension KW - chronic condition KW - mobile health app KW - monitoring KW - systematic search KW - app development KW - clinical validation KW - evaluation KW - pulmonary N2 - Background: Pulmonary hypertension (PH) is a chronic and complex condition, requiring consistent management and education. The widespread use of smartphones has opened possibilities for mobile health apps to support both patients and health care professionals in monitoring and managing PH more effectively. Objective: This study aimed to identify and assess the quality of free smartphone apps for PH targeted at either patients or health care professionals. Methods: A systematic search was conducted on freely available apps for patients with PH and health care professionals, accessed from a Spanish IP address, on Android (Google Play) and iOS (App Store) platforms. Searches were performed in October 2022 and 2023. Apps were independently analyzed by two reviewers, focusing on general characteristics. Quality assessment was based on the Mobile Application Rating Scale (MARS) framework, and Mann-Whitney U tests compared mean MARS scores against specific variables. Results: In the overall study, 21 apps were identified. In the 2022 search, 19 apps were listed (9 iOS, 7 Android, 3 available on both platforms). In the subsequent 2023 search, 16 apps were identified (6 Android, 7 iOS, 3 available on both platforms). Of those identified in 2022, 14 remained available in 2023, with only 7 updated since 2022. In addition, 12 apps targeted patients or the general population, while 9 targeted health care professionals; none involved patients in the development or design. Conversely, 13 apps involving health care professionals were identified. There were 10 apps that received pharmaceutical industry funding. The primary goal for 81% (17/21) of the apps was to disseminate general information about PH. The overall mean MARS quality was acceptable in 2022 and 2023, with mean ratings of 3.1 (SD 0.6) and 3.3 (SD 0.5), respectively. The functionality category achieved the highest scores in both years, indicating ease of use and intuitive navigation. In contrast, the subjective quality domain consistently received the lowest ratings in the MARS assessment across both years. None of the apps underwent clinical testing themselves; however, 2 incorporated tools or algorithms derived from trials. The overall quality of iOS apps statistically outperformed that of Android apps in both years (P<.05). Furthermore, the involvement of health care professionals in app development was associated with enhanced quality, a trend observed in both years (P=.003 for both years). Conclusions: This review of mobile health apps for PH reveals their emergent development stage, with generally acceptable quality but lacking refinement. It highlights the critical role of health care professionals in app development, as they contribute significantly to quality and reliability. Despite this, a notable stagnation in app quality and functionality improvement over 2 years points to a need for continuous innovation and clinical validation for effective clinical integration. This research advocates for future app developers to actively engage with health care professionals, integrate patient insights, and mandate rigorous clinical validation for PH management. UR - https://mhealth.jmir.org/2024/1/e57289 UR - http://dx.doi.org/10.2196/57289 ID - info:doi/10.2196/57289 ER - TY - JOUR AU - Erdt, Mojisola AU - Yusof, Binte Sakinah AU - Chai, Liquan AU - Md Salleh, Umairah Siti AU - Liu, Zhengyuan AU - Sarim, Binte Halimah AU - Lim, Choo Geok AU - Lim, Hazel AU - Suhaimi, Ain Nur Farah AU - Yulong, Lin AU - Guo, Yang AU - Ng, Angela AU - Ong, Sharon AU - Choo, Peide Bryan AU - Lee, Sheldon AU - Weiliang, Huang AU - Oh, Choon Hong AU - Wolters, Klara Maria AU - Chen, F. Nancy AU - Krishnaswamy, Pavitra PY - 2024/10/30 TI - Characterization of Telecare Conversations on Lifestyle Management and Their Relation to Health Care Utilization for Patients with Heart Failure: Mixed Methods Study JO - J Med Internet Res SP - e46983 VL - 26 KW - telehealth KW - telecare KW - heart failure KW - chronic disease KW - self-management KW - lifestyle management KW - behavior KW - health care utilization KW - conversation KW - dialogue KW - medical informatics N2 - Background: Telehealth interventions where providers offer support and coaching to patients with chronic conditions such as heart failure (HF) and type 2 diabetes mellitus (T2DM) are effective in improving health outcomes. However, the understanding of the content and structure of these interactions and how they relate to health care utilization remains incomplete. Objective: This study aimed to characterize the content and structure of telecare conversations on lifestyle management for patients with HF and investigate how these conversations relate to health care utilization. Methods: We leveraged real-world data from 50 patients with HF enrolled in a postdischarge telehealth program, with the primary intervention comprising a series of telephone calls from nurse telecarers over a 12-month period. For the full cohort, we transcribed 729 English-language calls and annotated conversation topics. For a subcohort (25 patients with both HF and T2DM), we annotated lifestyle management content with fine-grained dialogue acts describing typical conversational structures. For each patient, we identified calls with unusually high ratios of utterances on lifestyle management as lifestyle-focused calls. We further extracted structured data for inpatient admissions from 6 months before to 6 months after the intervention period. First, to understand conversational structures and content of lifestyle-focused calls, we compared the number of utterances, dialogue acts, and symptom attributes in lifestyle-focused calls to those in calls containing but not focused on lifestyle management. Second, to understand the perspectives of nurse telecarers on these calls, we conducted an expert evaluation where 2 nurse telecarers judged levels of concern and follow-up actions for lifestyle-focused and other calls (not focused on lifestyle management content). Finally, we assessed how the number of lifestyle-focused calls relates to the number of admissions, and to the average length of stay per admission. Results: In comparative analyses, lifestyle-focused calls had significantly fewer utterances (P=.01) and more dialogue acts (Padj=.005) than calls containing but not focused on lifestyle management. Lifestyle-focused calls did not contain deeper discussions on clinical symptoms. These findings indicate that lifestyle-focused calls entail short, intense discussions with greater emphasis on understanding patient experience and coaching than on clinical content. In the expert evaluation, nurse telecarers identified 24.2% (29/120) of calls assessed as concerning enough for follow-up. For these 29 calls, nurse telecarers were more attuned to concerns about symptoms and vitals (19/29, 65.5%) than lifestyle management concerns (4/29, 13.8%). The number of lifestyle-focused calls a patient had was modestly (but not significantly) associated with a lower average length of stay for inpatient admissions (Spearman ?=-0.30; Padj=.06), but not with the number of admissions (Spearman ?=-0.03; Padj=.84). Conclusions: Our approach and findings offer novel perspectives on the content, structure, and clinical associations of telehealth conversations on lifestyle management for patients with HF. Hence, our study could inform ways to enhance telehealth programs for self-care management in chronic conditions. UR - https://www.jmir.org/2024/1/e46983 UR - http://dx.doi.org/10.2196/46983 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/46983 ER - TY - JOUR AU - Gibson, Irene AU - Neubeck, Lis AU - Corcoran, Marissa AU - Morland, Chris AU - Donovan, Steve AU - Jones, Jennifer AU - Costello, Caroline AU - Hynes, Lisa AU - Harris, Aisling AU - Harrahill, Mary AU - Lillis, Mary AU - Atrey, Alison AU - Ski, F. Chantal AU - Savickas, Vilius AU - Byrne, Molly AU - Murphy, W. Andrew AU - McEvoy, William John AU - Wood, David AU - Jennings, Catriona PY - 2024/10/23 TI - Development of a Digital Health Intervention for the Secondary Prevention of Cardiovascular Disease (INTERCEPT): Co-Design and Usability Testing Study JO - JMIR Hum Factors SP - e63707 VL - 11 KW - cardiovascular disease KW - secondary prevention KW - digital health KW - intervention development KW - co-design KW - usability testing KW - mobile health KW - usability KW - design KW - conline workshop KW - social support KW - behavioral change KW - self-monitoring N2 - Background: Secondary prevention is an important strategy to reduce the burden of cardiovascular disease (CVD), a leading cause of death worldwide. Despite the growing evidence for the effectiveness of digital health interventions (DHIs) for the secondary prevention of CVD, the majority are designed with minimal input from target end users, resulting in poor uptake and usage. Objective: This study aimed to optimize the acceptance and effectiveness of a DHI for the secondary prevention of CVD through co-design, integrating end users? perspectives throughout. Methods: A theory-driven, person-based approach using co-design was adopted for the development of the DHI, known as INTERCEPT. This involved a 4-phase iterative process using online workshops. In phase 1, a stakeholder team of health care professionals, software developers, and public and patient involvement members was established. Phase 2 involved identification of the guiding principles, content, and design features of the DHI. In phase 3, DHI prototypes were reviewed for clarity of language, ease of navigation, and functionality. To anticipate and interpret DHI usage, phase 4 involved usability testing with participants who had a recent cardiac event (<2 years). To assess the potential impact of usability testing, the System Usability Scale was administered before and after testing. The GUIDED (Guidance for Reporting Intervention Development Studies in Health Research) checklist was used to report the development process. Results: Five key design principles were identified: simplicity and ease of use, behavioral change through goal setting and self-monitoring, personalization, system credibility, and social support. Usability testing resulted in 64 recommendations for the app, of which 51 were implemented. Improvements in System Usability Scale scores were observed when comparing the results before and after implementing the recommendations (61 vs 83; P=.02). Conclusions: Combining behavior change theory with a person-based, co-design approach facilitated the development of a DHI for the secondary prevention of CVD that optimized responsiveness to end users? needs and preferences, thereby potentially improving future engagement. UR - https://humanfactors.jmir.org/2024/1/e63707 UR - http://dx.doi.org/10.2196/63707 UR - http://www.ncbi.nlm.nih.gov/pubmed/39441626 ID - info:doi/10.2196/63707 ER - TY - JOUR AU - Zhou, You AU - Li, Si-Jia AU - Huang, Ren-Qian AU - Ma, Hao-Ming AU - Wang, Ao-Qi AU - Tang, Xing-Yi AU - Pei, Run-Yuan AU - Piao, Mei-Hua PY - 2024/10/22 TI - Behavior Change Techniques Used in Self-Management Interventions Based on mHealth Apps for Adults With Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials JO - J Med Internet Res SP - e54978 VL - 26 KW - hypertension KW - mHealth KW - app KW - behavior change technique KW - systematic review KW - meta-analysis KW - mobile phone N2 - Background: Hypertension has become an important global public health challenge. Mobile health (mHealth) intervention is a viable strategy to improve outcomes for patients with hypertension. However, evidence on the effect of mHealth app interventions on self-management in patients with hypertension is yet to be updated, and the active ingredients promoting behavior change in interventions remain unclear. Objective: We aimed to evaluate the effect of mHealth app self-management interventions on blood pressure (BP) management and investigate the use of behavior change techniques (BCTs) in mHealth app interventions. Methods: We conducted a literature search in 6 electronic databases from January 2009 to October 2023 for studies reporting the application of mHealth apps in self-management interventions. The Cochrane Risk of Bias (version 2) tool for randomized controlled trials was used to assess the quality of the studies. BCTs were coded according to the Taxonomy of BCTs (version 1). The extracted data were analyzed using RevMan5.4 software (Cochrane Collaboration). Results: We reviewed 20 studies, of which 16 were included in the meta-analysis. In total, 21 different BCTs (mean 8.7, SD 3.8 BCTs) from 12 BCT categories were reported in mHealth app interventions. The most common BCTs were self-monitoring of outcomes of behavior, feedback on outcomes of behavior, instruction on how to perform the behavior, and pharmacological support. The mHealth app interventions resulted in a ?5.78 mm Hg (95% CI ?7.97 mm Hg to ?3.59 mm Hg; P<.001) reduction in systolic BP and a ?3.28 mm Hg (95% CI ?4.39 mm Hg to ?2.17 mm Hg; P<.001) reduction in diastolic BP. The effect of interventions on BP reduction was associated with risk factors, such as hypertension, that were addressed by the mHealth app intervention (multiple risk factors vs a single risk factor: ?6.50 mm Hg, 95% CI ?9.00 mm Hg to ?3.99 mm Hg vs ?1.54 mm Hg, 95% CI ?4.15 mm Hg to 1.06 mm Hg; P=.007); the presence of a theoretical foundation (with vs without behavior change theory: ?10.06 mm Hg, 95% CI ?16.42 mm Hg to ?3.70 mm Hg vs ?4.13 mm Hg, 95% CI ?5.50 to ?2.75 mm Hg; P=.07); intervention duration (3 vs ?6 months: ?8.87 mm Hg, 95% CI ?10.90 mm Hg to ?6.83 mm Hg vs ?5.76 mm Hg, 95% CI ?8.74 mm Hg to ?2.77 mm Hg; P=.09); and the number of BCTs (?11 vs <11 BCTs: ?9.68 mm Hg, 95% CI ?13.49 mm Hg to ?5.87 mm Hg vs ?2.88 mm Hg, 95% CI ?3.90 mm Hg to ?1.86 mm Hg; P<.001). Conclusions: The self-management interventions based on mHealth apps were effective strategies for lowering BP in patients with hypertension. The effect of interventions was influenced by factors related to the study?s intervention design and BCT. UR - https://www.jmir.org/2024/1/e54978 UR - http://dx.doi.org/10.2196/54978 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/54978 ER - TY - JOUR AU - Achtari, Margaux AU - Salihu, Adil AU - Muller, Olivier AU - Abbé, Emmanuel AU - Clair, Carole AU - Schwarz, Joëlle AU - Fournier, Stephane PY - 2024/10/22 TI - Gender Bias in AI's Perception of Cardiovascular Risk JO - J Med Internet Res SP - e54242 VL - 26 KW - artificial intelligence KW - gender equity KW - coronary artery disease KW - AI KW - cardiovascular KW - risk KW - CAD KW - artery KW - coronary KW - chatbot: health care KW - men: women KW - gender bias KW - gender UR - https://www.jmir.org/2024/1/e54242 UR - http://dx.doi.org/10.2196/54242 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/54242 ER - TY - JOUR AU - Kashiwakura, Daisaku AU - Hiyama, Akiko AU - Muramatsu, Masumi AU - Hinotsu, Atsuko AU - Takeda, Michiko AU - Suzuki, Norio AU - Akiyama, Sachie AU - Kurihara, Sayuri AU - Kida, Keisuke PY - 2024/10/18 TI - A Self-Administered Eating Behavior Scale for Patients With Heart Failure Living at Home: Protocol for a Mixed Methods Scale Development Study JO - JMIR Res Protoc SP - e60719 VL - 13 KW - heart failure KW - eating behavior KW - self-care KW - patient-reported outcome measures KW - International Classification of Functioning, Disability, and Health (ICF) N2 - Background: The prevalence of heart failure (HF) is increasing worldwide, with the associated mortality rates rising consistently. Preventing HF progression requires adherence to restricted sodium intake alongside sufficient and balanced nutritional consumption. For patients at home, preparing nutritionally balanced meals is essential, either self-assisted or with the aid of close individuals. Patients with HF frequently experience decreased exercise tolerance, depression, anxiety, and social isolation, which interfere with eating behaviors, leading to inadequate dietary habits. However, measures focusing on the determinants of eating behavior among patients with HF are currently lacking. Objective: This study aims to develop a self-administered scale to assess the eating behaviors of patients with HF living at home (Self-Administered Eating Behaviors Scale for Heart Failure [SEBS-HF]). Methods: This study encompasses 3 phases. Phase 1 involves identifying factors influencing eating behaviors in patients with HF. First, a literature review will be conducted using PubMed and CINAHL databases. The specified literature will be analyzed qualitatively and inductively. Additionally, verbatim transcripts obtained from semistructured interviews of patients with HF and medical experts will be qualitatively analyzed. Based on the Phase 1 results, a preliminary scale will be constructed. In Phase 2, cognitive interviews will be conducted with patients with HF and experts; the preliminary scale will be used to qualitatively evaluate its content validity. After validation, the scale will be used in Phase 3 to conduct a cross-sectional study involving patients with HF. In Phase 3, data will be collected from clinical records and self-administered questionnaires or scales. After conducting a preliminary survey, the main survey will be conducted. The reliability and validity of the scale will be assessed using statistical methods. Results: The first phase of this study commenced in September 2023, and by May 2, 2024, a total of 7 patients with HF and 6 expert professionals were enrolled as study participants. The draft creation of the scale will be completed in 2024, and the content validity evaluation of the draft scale is expected to be finished by early 2025. The third phase will begin its investigation in mid-2025 and is expected to be completed by late 2025, after which the SEBS-HF will be published. Conclusions: The development and use of this scale will enable a more comprehensive evaluation of the factors influencing eating behaviors in patients with HF. Thus, medical and welfare professionals should provide appropriate support tailored to the specific needs of patients with HF. International Registered Report Identifier (IRRID): DERR1-10.2196/60719 UR - https://www.researchprotocols.org/2024/1/e60719 UR - http://dx.doi.org/10.2196/60719 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60719 ER - TY - JOUR AU - Mubarik, Sumaira AU - Naeem, Shafaq AU - Shen, Hui AU - Mubarak, Rabia AU - Luo, Lisha AU - Hussain, Rija Syeda AU - Hak, Eelko AU - Yu, Chuanhua AU - Liu, Xiaoxue PY - 2024/10/17 TI - Population-Level Distribution, Risk Factors, and Burden of Mortality and Disability-Adjusted Life Years Attributable to Major Noncommunicable Diseases in Western Europe (1990-2021): Ecological Analysis JO - JMIR Public Health Surveill SP - e57840 VL - 10 KW - mortality KW - smoking KW - Western Europe KW - CVDs KW - cardiovascular disease KW - HDI KW - Human Development Index KW - neoplasms KW - cancer KW - DALYs KW - disability-adjusted life years N2 - Background: Cardiovascular diseases (CVDs) and neoplasms are leading causes of mortality worldwide. Objective: This study aims to provide a comprehensive analysis of the mortality burden and disability-adjusted life years (DALYs) attributable to CVDs and neoplasms in Western Europe, investigate associated risk factors, and identify regional disparities. Additionally, the study evaluates the effectiveness of the Action Plan for the Prevention and Control of Non-Communicable Diseases (NCDs) in promoting healthier lives in the region. Methods: The study collected data on mortality and DALYs due to CVDs and cancers from 24 Western European countries using the Global Burden of Disease Study 2021. The analysis explored age, sex, and country-specific patterns, as well as risk factors contributing to these deaths. Additionally, the study examined time trends by calculating the annual percent change in mortality rates from 1990 to 2021 by region and cause. Results: In 2021, CVDs and neoplasms accounted for 27.8% and 27.1% of total deaths in Western Europe, with age-standardized death rates of 106.8 and 125.8 per 100,000, respectively. The top two CVDs in this region were ischemic heart disease and stroke, with age-standardized death rates of 47.27 (95% uncertainty interval [UI] 50.42-41.45) and 27.06 (95% UI 29.17-23.00), respectively. Similarly, the top two neoplasms were lung cancer and colorectal cancer, with age-standardized death rates of 26.4 (95% UI 27.69-24.47) and 15.1 (95% UI 16.25-13.53), respectively. Between 1990 and 2021, CVD mortality rates decreased by 61.9%, while cancer rates decreased by 28.27%. Finland had the highest CVD burden (39.5%), and Monaco had the highest rate of cancer-related deaths (34.8%). Gender differences were observed, with males experiencing a higher burden of both CVDs and cancer. Older individuals were also more at risk. Smoking had a stronger impact on CVD mortality and DALYs in males, while a higher Human Development Index was associated with increased cancer deaths and DALYs in females. Conclusions: The study findings highlight the substantial burden of NCDs, particularly CVDs and cancer, in Western Europe. This underscores the critical need for targeted interventions and effective implementation of the Action Plan for the Prevention and Control of NCDs to achieve the goal of ensuring healthy lives for all. UR - https://publichealth.jmir.org/2024/1/e57840 UR - http://dx.doi.org/10.2196/57840 ID - info:doi/10.2196/57840 ER - TY - JOUR AU - Sven?ek, Adrijana AU - Lorber, Mateja AU - Gosak, Lucija AU - Verbert, Katrien AU - Klemenc-Ketis, Zalika AU - Stiglic, Gregor PY - 2024/10/14 TI - The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review JO - JMIR Public Health Surveill SP - e60128 VL - 10 KW - cardiovascular disease prevention KW - risk factors KW - visual analytics KW - visualization KW - mobile phone KW - PRISMA N2 - Background: Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients? behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. Objective: This review aims to present the most-used visualization techniques to estimate CVD risk. Methods: In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. Results: We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing?related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). Conclusions: On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health?s effectiveness in improving CVD outcomes is limited. UR - https://publichealth.jmir.org/2024/1/e60128 UR - http://dx.doi.org/10.2196/60128 UR - http://www.ncbi.nlm.nih.gov/pubmed/39401079 ID - info:doi/10.2196/60128 ER - TY - JOUR AU - Patil, Rohan AU - Ashraf, Fatima AU - Abu Dayeh, Samer AU - Prakash, K. Siddharth PY - 2024/10/8 TI - Development and Assessment of a Point-of-Care Application (Genomic Medicine Guidance) for Heritable Thoracic Aortic Disease JO - JMIRx Med SP - e55903 VL - 5 KW - genomic medicine KW - point of care KW - thoracic aortic aneurysm KW - aortic dissection KW - decision support N2 - Background: Genetic testing can determine familial and personal risks for heritable thoracic aortic aneurysms and dissections (TAD). The 2022 American College of Cardiology/American Heart Association guidelines for TAD recommend management decisions based on the specific gene mutation. However, many clinicians lack sufficient comfort or insight to integrate genetic information into clinical practice. Objective: We therefore developed the Genomic Medicine Guidance (GMG) application, an interactive point-of-care tool to inform clinicians and patients about TAD diagnosis, treatment, and surveillance. GMG is a REDCap-based application that combines publicly available genetic data and clinical recommendations based on the TAD guidelines into one translational education tool. Methods: TAD genetic information in GMG was sourced from the Montalcino Aortic Consortium, a worldwide collaboration of TAD centers of excellence, and the National Institutes of Health genetic repositories ClinVar and ClinGen. Results: The application streamlines data on the 13 most frequently mutated TAD genes with 2286 unique pathogenic mutations that cause TAD so that users receive comprehensive recommendations for diagnostic testing, imaging, surveillance, medical therapy, and preventative surgical repair, as well as guidance for exercise safety and management during pregnancy. The application output can be displayed in a clinician view or exported as an informative pamphlet in a patient-friendly format. Conclusions: The overall goal of the GMG application is to make genomic medicine more accessible to clinicians and patients while serving as a unifying platform for research. We anticipate that these features will be catalysts for collaborative projects aiming to understand the spectrum of genetic variants contributing to TAD. UR - https://xmed.jmir.org/2024/1/e55903 UR - http://dx.doi.org/10.2196/55903 ID - info:doi/10.2196/55903 ER - TY - JOUR AU - Taylor, Marin AU - Bondi, Christina Bianca AU - Andrade, F. Brendan AU - Au-Young, H. Stephanie AU - Chau, Vann AU - Danguecan, Ashley AU - Désiré, Naddley AU - Guo, Ting AU - Ostojic-Aitkens, Dragana AU - Wade, Shari AU - Miller, Steven AU - Williams, Samantha Tricia PY - 2024/10/4 TI - Stepped-Care Web-Based Parent Support Following Congenital Heart Disease: Protocol for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e64216 VL - 13 KW - congenital heart disease KW - neurodevelopmental outcomes KW - web-based mental health care KW - stepped care KW - positive parenting KW - family well-being KW - mental health KW - I-InTERACT-North N2 - Background: Early neurodevelopmental risks, compounded with traumatic medical experiences, contribute to emotional and behavioral challenges in as many as 1 in 2 children with congenital heart disease (CHD). Parents report a strong need for supports; yet, there remains a lack of accessible, evidence-based behavioral interventions available for children with CHD and their families. I-InTERACT-North is a web-based stepped-care mental health program designed to support family well-being and reduce behavioral concerns through positive parenting for children with early medical complexity. In previous pilot studies, the program was effective in increasing positive parenting skills and decreasing child behavior problems, with high parent-reported acceptability. This paper presents the protocol for the first randomized study of stepped-care parent support for families of children with CHD. Objective: This study will involve a single-site, 2-arm, single-blind randomized controlled trial to evaluate (1) the feasibility and acceptability of a web-based stepped-care parent support program (I-InTERACT-North) and (2) the effectiveness of the program in enhancing positive parenting skills and reducing behavioral concerns among families of children with CHD. Methods: Families will be randomized (1:1) to either receive treatment or continue with care as usual for 12 months. Randomization will be stratified by child?s sex assigned at birth and baseline parent-reported child behavior intensity. Primary outcomes include positive parenting skills and child behavior at baseline, 3 months, 6 months, and 12 months. Secondary outcomes include parental mental health, quality of life, service usage, and feasibility including program reach and adherence. A sample size of 244 families will provide >95% power to detect an effect size of d=0.64. Based on attrition data from pilot studies, a target of 382 families will be enrolled. Parent reports of acceptability, adoption, and suggested adaptability of the program will be examined using cross-case thematic analyses. Primary efficacy analysis will be conducted using an intent-to-treat approach. Generalized estimating equations will be used to examine changes in positive parenting. Child behavior, quality of life, and parent mental health will be tested with repeated-measures analyses. Additional sensitivity and replication analyses will also be carried out. Results: Recruitment began in February 2024, and recruitment and follow-up will continue until January 2029. We anticipate results in late 2029. Conclusions: This study aims to test the effectiveness of I-InTERACT-North web-based stepped-care parent support in improving positive parenting skills and reducing child behavior problems in families of children with CHD compared with a care as usual control group. Results will inform future clinical implementation and expansion of this program among families of children with early medical conditions. Trial Registration: ClinicalTrials.gov NCT06075251; https://clinicaltrials.gov/study/NCT06075251 International Registered Report Identifier (IRRID): DERR1-10.2196/64216 UR - https://www.researchprotocols.org/2024/1/e64216 UR - http://dx.doi.org/10.2196/64216 UR - http://www.ncbi.nlm.nih.gov/pubmed/39365658 ID - info:doi/10.2196/64216 ER - TY - JOUR AU - Johar, Hamimatunnisa AU - Ang, Way Chiew AU - Ismail, Roshidi AU - Kassim, Zaid AU - Su, Tin Tin PY - 2024/9/26 TI - Changes in 10-Year Predicted Cardiovascular Disease Risk for a Multiethnic Semirural Population in South East Asia: Prospective Study JO - JMIR Public Health Surveill SP - e55261 VL - 10 KW - cardiovascular risk trajectory KW - Framingham risk score KW - population-based study KW - low- and middle-income countries N2 - Background: Cardiovascular disease (CVD) risk factors tend to cluster and interact multiplicatively and have been incorporated into risk equations such as the Framingham risk score, which can reasonably predict CVD over short- and long-term periods. Beyond risk factor levels at a single time point, recent evidence demonstrated that risk trajectories are differentially related to CVD risk. However, factors associated with suboptimal control or unstable CVD risk trajectories are not yet established. Objective: This study aims to examine factors associated with CVD risk trajectories in a semirural, multiethnic community-dwelling population. Methods: Data on demographic, socioeconomic, lifestyle, mental health, and cardiovascular factors were measured at baseline (2013) and during follow-up (2018) of the South East Asia Community Observatory cohort. The 10-year CVD risk change transition was computed. The trajectory patterns identified were improved; remained unchanged in low, moderate, or high CVD risk clusters; and worsened CVD risk trajectories. Multivariable regression analyses were used to examine the association between risk factors and changes in Framingham risk score and predicted CVD risk trajectory patterns with adjustments for concurrent risk factors. Results: Of the 6599 multiethnic community-dwelling individuals (n=3954, 59.92% female participants and n=2645, 40.08% male participants; mean age 55.3, SD 10.6 years), CVD risk increased over time in 33.37% (n=2202) of the sample population, while 24.38% (n=1609 remained in the high-risk trajectory pattern, which was reflected by the increased prevalence of all major CVD risk factors over the 5-year follow-up. Meanwhile, sex-specific prevalence data indicate that 21.44% (n=567) of male and 41.35% (n=1635) of female participants experienced an increase in CVD risk. However, a stark sex difference was observed in those remaining in the high CVD risk cluster, with 45.1% (n=1193) male participants and 10.52% (n=416) female participants. Regarding specific CVD risk factors, male participants exhibited a higher percentage increase in the prevalence of hypertension, antihypertensive medication use, smoking, and obesity, while female participants showed a higher prevalence of diabetes. Further regression analyses identified that Malay compared to Chinese (P<.001) and Indian (P=.04) ethnicity, nonmarried status (P<.001), full-time employment (P<.001), and depressive symptoms (P=.04) were all significantly associated with increased CVD risk scores. In addition, lower educational levels and frequently having meals from outside were significantly associated to higher odds of both worsening and remaining in high CVD risk trajectories. Conclusions: Sociodemographics and mental health were found to be differently associated with CVD risk trajectories, warranting future research to disentangle the role of psychosocial disparities in CVD. Our findings carry public health implications, suggesting that the rise in major risk factors along with psychosocial disparities could potentially elevate CVD risk among individuals in underserved settings. More prevention efforts that continuously monitor CVD risk and consider changes in risk factors among vulnerable populations should be emphasized. UR - https://publichealth.jmir.org/2024/1/e55261 UR - http://dx.doi.org/10.2196/55261 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/55261 ER - TY - JOUR AU - Brahma, Arindam AU - Chatterjee, Samir AU - Seal, Kala AU - Fitzpatrick, Ben AU - Tao, Youyou PY - 2024/9/24 TI - Development of a Cohort Analytics Tool for Monitoring Progression Patterns in Cardiovascular Diseases: Advanced Stochastic Modeling Approach JO - JMIR Med Inform SP - e59392 VL - 12 KW - healthcare analytics KW - eHealth KW - disease monitoring KW - cardiovascular disease KW - disease progression model KW - myocardial KW - stroke KW - decision support KW - continuous-time Markov chain model KW - stochastic model KW - stochastic KW - Markov KW - cardiology KW - cardiovascular KW - heart KW - monitoring KW - progression N2 - Background: The World Health Organization (WHO) reported that cardiovascular diseases (CVDs) are the leading cause of death worldwide. CVDs are chronic, with complex progression patterns involving episodes of comorbidities and multimorbidities. When dealing with chronic diseases, physicians often adopt a ?watchful waiting? strategy, and actions are postponed until information is available. Population-level transition probabilities and progression patterns can be revealed by applying time-variant stochastic modeling methods to longitudinal patient data from cohort studies. Inputs from CVD practitioners indicate that tools to generate and visualize cohort transition patterns have many impactful clinical applications. The resultant computational model can be embedded in digital decision support tools for clinicians. However, to date, no study has attempted to accomplish this for CVDs. Objective: This study aims to apply advanced stochastic modeling methods to uncover the transition probabilities and progression patterns from longitudinal episodic data of patient cohorts with CVD and thereafter use the computational model to build a digital clinical cohort analytics artifact demonstrating the actionability of such models. Methods: Our data were sourced from 9 epidemiological cohort studies by the National Heart Lung and Blood Institute and comprised chronological records of 1274 patients associated with 4839 CVD episodes across 16 years. We then used the continuous-time Markov chain method to develop our model, which offers a robust approach to time-variant transitions between disease states in chronic diseases. Results: Our study presents time-variant transition probabilities of CVD state changes, revealing patterns of CVD progression against time. We found that the transition from myocardial infarction (MI) to stroke has the fastest transition rate (mean transition time 3, SD 0 days, because only 1 patient had a MI-to-stroke transition in the dataset), and the transition from MI to angina is the slowest (mean transition time 1457, SD 1449 days). Congestive heart failure is the most probable first episode (371/840, 44.2%), followed by stroke (216/840, 25.7%). The resultant artifact is actionable as it can act as an eHealth cohort analytics tool, helping physicians gain insights into treatment and intervention strategies. Through expert panel interviews and surveys, we found 9 application use cases of our model. Conclusions: Past research does not provide actionable cohort-level decision support tools based on a comprehensive, 10-state, continuous-time Markov chain model to unveil complex CVD progression patterns from real-world patient data and support clinical decision-making. This paper aims to address this crucial limitation. Our stochastic model?embedded artifact can help clinicians in efficient disease monitoring and intervention decisions, guided by objective data-driven insights from real patient data. Furthermore, the proposed model can unveil progression patterns of any chronic disease of interest by inputting only 3 data elements: a synthetic patient identifier, episode name, and episode time in days from a baseline date. UR - https://medinform.jmir.org/2024/1/e59392 UR - http://dx.doi.org/10.2196/59392 UR - http://www.ncbi.nlm.nih.gov/pubmed/39316426 ID - info:doi/10.2196/59392 ER - TY - JOUR AU - Yun, Byungyoon AU - Park, Heejoo AU - Choi, Jaesung AU - Oh, Juyeon AU - Sim, Juho AU - Kim, Yangwook AU - Lee, Jongmin AU - Yoon, Jin-Ha PY - 2024/9/20 TI - Inequality in Mortality and Cardiovascular Risk Among Young, Low-Income, Self-Employed Workers: Nationwide Retrospective Cohort Study JO - JMIR Public Health Surveill SP - e48047 VL - 10 KW - self-employed KW - employee KW - all-cause mortality KW - cardiovascular disease KW - mental illness KW - socioeconomic status KW - nationwide study KW - inequality KW - effect modification KW - health checkups N2 - Background: Self-employment is a significant component of South Korea?s labor force; yet, it remains relatively understudied in the context of occupational safety and health. Owing to different guidelines for health checkup participation among economically active individuals, disparities in health maintenance may occur across varying employment statuses. Objective: This study aims to address such disparities by comparing the risk of all-cause mortality and comorbidities between the self-employed and employee populations in South Korea, using nationwide data. We sought to provide insights relevant to other countries with similar cultural, social, and economic contexts. Methods: This nationwide retrospective study used data from the Korean National Health Insurance Service database. Participants (aged 20?59 y) who maintained the same insurance type (self-employed or employee insurance) for ?3 years (at least 2008?2010) were recruited for this study and monitored until death or December 2021?whichever occurred first. The primary outcome was all-cause mortality. The secondary outcomes were ischemic heart disease, ischemic stroke, cancer, and hospitalization with a mental illness. Age-standardized cumulative incidence rates were estimated through an indirect method involving 5-unit age standardization. A multivariable Cox proportional hazards model was used to estimate the adjusted hazard ratio (HR) and 95% CI for each sex stratum. Subgroup analyses and an analysis of the effect modification of health checkup participation were also performed. Results: A total of 11,652,716 participants were analyzed (follow-up: median 10.92, IQR 10.92-10.92 y; age: median 42, IQR 35-50 y; male: n=7,975,116, 68.44%); all-cause mortality occurred in 1.27% (99,542/7,851,282) of employees and 3.29% (124,963/3,801,434) of self-employed individuals (P<.001). The 10-year cumulative incidence rates of all-cause mortality differed significantly by employment status (1.1% for employees and 2.8% for self-employed individuals; P<.001). The risk of all-cause mortality was significantly higher among the self-employed individuals when compared with that among employees, especially among female individuals, according to the final model (male: adjusted HR 1.44, 95% CI 1.42?1.45; female: adjusted HR 1.89, 95% CI 1.84?1.94; P<.001). The risk of the secondary outcomes, except all types of malignancies, was significantly higher among the self-employed individuals (all P values were <.001). According to subgroup analyses, this association was prominent in younger individuals with lower incomes who formed a part of the nonparticipation groups. Furthermore, health checkup participation acted as an effect modifier for the association between employment status and all-cause mortality in both sexes (male: relative excess risk due to interaction [RERI] 0.76, 95% CI 0.74?0.79; female: RERI 1.13, 95% CI 1.05?1.21). Conclusions: This study revealed that self-employed individuals face higher risks of all-cause mortality, cardio-cerebrovascular diseases, and mental illnesses when compared to employees. The mortality risk is particularly elevated in younger, lower-income individuals who do not engage in health checkups, with health checkup nonparticipation acting as an effect modifier for this association. UR - https://publichealth.jmir.org/2024/1/e48047 UR - http://dx.doi.org/10.2196/48047 ID - info:doi/10.2196/48047 ER - TY - JOUR AU - Kumar, Mandeep AU - Wilkinson, Kathryn AU - Li, Ya-Huei AU - Masih, Rohit AU - Gandhi, Mehak AU - Saadat, Haleh AU - Culmone, Julie PY - 2024/9/13 TI - Association of a Novel Electronic Form for Preoperative Cardiac Risk Assessment With Reduction in Cardiac Consultations and Testing: Retrospective Cohort Study JO - JMIR Perioper Med SP - e63076 VL - 7 KW - preoperative KW - cardiology consultations KW - decrease low value care KW - cardiology KW - cardiac KW - cohort KW - surgery KW - surgical KW - EMR KW - EMRs KW - EHR KW - EHRs KW - electronic medical record KW - electronic medical records KW - electronic health record KW - electronic health records KW - form KW - forms KW - assessment KW - assessments KW - risk KW - risks KW - referral KW - consultation KW - consultations KW - testing KW - diagnosis KW - diagnoses KW - diagnostic KW - diagnostics N2 - Background: Preoperative cardiac risk assessment is an integral part of preoperative evaluation; however, there is significant variation among providers, leading to inappropriate referrals for cardiology consultation or excessive low-value cardiac testing. We implemented a novel electronic medical record (EMR) form in our preoperative clinics to decrease variation. Objective: This study aimed to investigate the impact of the EMR form on the preoperative utilization of cardiology consultation and cardiac diagnostic testing (echocardiograms, stress tests, and cardiac catheterization) and evaluate postoperative outcomes. Methods: A retrospective cohort study was conducted. Patients who underwent outpatient preoperative evaluation prior to an elective surgery over 2 years were divided into 2 cohorts: from July 1, 2021, to June 30, 2022 (pre?EMR form implementation), and from July 1, 2022, to June 30, 2023 (post?EMR form implementation). Demographics, comorbidities, resource utilization, and surgical characteristics were analyzed. Propensity score matching was used to adjust for differences between the 2 cohorts. The primary outcomes were the utilization of preoperative cardiology consultation, cardiac testing, and 30-day postoperative major adverse cardiac events (MACE). Results: A total of 25,484 patients met the inclusion criteria. Propensity score matching yielded 11,645 well-matched pairs. The post?EMR form, matched cohort had lower cardiology consultation (pre?EMR form: n=2698, 23.2% vs post?EMR form: n=2088, 17.9%; P<.001) and echocardiogram (pre?EMR form: n=808, 6.9% vs post?EMR form: n=591, 5.1%; P<.001) utilization. There were no significant differences in the 30-day postoperative outcomes, including MACE (all P>.05). While patients with ?possible indications? for cardiology consultation had higher MACE rates, the consultations did not reduce MACE risk. Most algorithm end points, except for active cardiac conditions, had MACE rates <1%. Conclusions: In this cohort study, preoperative cardiac risk assessment using a novel EMR form was associated with a significant decrease in cardiology consultation and testing utilization, with no adverse impact on postoperative outcomes. Adopting this approach may assist perioperative medicine clinicians and anesthesiologists in efficiently decreasing unnecessary preoperative resource utilization without compromising patient safety or quality of care. UR - https://periop.jmir.org/2024/1/e63076 UR - http://dx.doi.org/10.2196/63076 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/63076 ER - TY - JOUR AU - Magon, Arianna AU - Hendriks, Jeroen AU - Caruso, Rosario PY - 2024/9/13 TI - Developing and Validating a Self-Care Self-Efficacy Scale for Oral Anticoagulation Therapy in Patients With Nonvalvular Atrial Fibrillation: Protocol for a Mixed Methods Study JO - JMIR Res Protoc SP - e51489 VL - 13 KW - oral anticoagulation therapy KW - nonvalvular atrial fibrillation KW - self-care KW - self-efficacy KW - medication adherence KW - patient-centered education KW - scale development KW - validation KW - psychometrics KW - atrial fibrillation KW - education KW - development KW - anticoagulation KW - prevention KW - stroke KW - medication KW - management N2 - Background: Oral anticoagulation therapy (OAC) is the cornerstone treatment for preventing venous thromboembolism and stroke in patients with nonvalvular atrial fibrillation (NVAF). Despite its significance, challenges in adherence and persistence to OAC regimens have been reported, leading to severe health complications. Central to addressing these challenges is the concept of self-efficacy (SE) in medication management. Currently, there is a noticeable gap in available tools specifically designed to measure SE in OAC self-care management, while such tools are crucial for enhancing patient adherence and overall treatment outcomes. Objective: This study aims to develop and validate a novel scale aimed to measure self-care self-efficacy (SCSE) in patients with NVAF under OAC, which is the patients? Self-Care Self-Efficacy Index in Oral Anticoagulation Therapy Management (SCSE-OAC), for English- and Italian-speaking populations. We also seek to assess patients? SE in managing their OAC treatment effectively and to explore the relationship between SE levels and sociodemographic and clinical variables. Methods: Using a multiphase, mixed methods observational study design, we first conceptualize the SCSE-OAC through literature reviews, patient focus groups, and expert consensus. The scale?s content validity will be evaluated through patient and expert reviews, while its construct validity is assessed using exploratory and confirmatory factor analyses, ensuring cross-cultural applicability. Criterion validity will be examined through correlations with clinical outcomes. Reliability will be tested via internal consistency and test-retest reliability measures. The study will involve adult outpatients with NVAF on OAC treatment for a minimum of 3 months, using both e-surveys and paper forms for data collection. Results: It is anticipated that the SCSE-OAC will emerge as a reliable and valid tool for measuring SE in OAC self-care management. It will enable identifying patients at risk of poor adherence due to low SE, facilitating targeted educational interventions. The scale?s validation in both English and Italian-speaking populations will underscore its applicability in diverse clinical settings, contributing significantly to personalized patient-centered care in anticoagulation management. Conclusions: The development and validation of the SCSE-OAC represent a significant advancement in the field of anticoagulation therapy. Validating the index in English- and Italian-speaking populations will enable personalized patient-centered educational interventions, ultimately improving OAC treatment outcomes. The SCSE-OAC?s focus on SCSE introduces a novel approach to identifying and addressing individual patient needs, promoting adherence, and ultimately improving health outcomes. Future endeavors will seek to extend the validation of the SCSE-OAC across diverse cultural and linguistic landscapes, broadening its applicability in global clinical and research settings. This scale-up effort is crucial for establishing a universal standard for measuring SCSE in OAC management, empowering clinicians and researchers worldwide to tailor effective and culturally sensitive interventions. Trial Registration: ClinicalTrials.gov NCT05820854; https://tinyurl.com/2mmypey7 International Registered Report Identifier (IRRID): PRR1-10.2196/51489 UR - https://www.researchprotocols.org/2024/1/e51489 UR - http://dx.doi.org/10.2196/51489 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/51489 ER - TY - JOUR AU - Straw, Isabel AU - Rees, Geraint AU - Nachev, Parashkev PY - 2024/8/26 TI - Sex-Based Performance Disparities in Machine Learning Algorithms for Cardiac Disease Prediction: Exploratory Study JO - J Med Internet Res SP - e46936 VL - 26 KW - artificial intelligence KW - machine learning KW - cardiology KW - health care KW - health equity KW - medicine KW - cardiac KW - quantitative evaluation KW - inequality KW - cardiac disease KW - performance KW - sex KW - management KW - heart failure N2 - Background: The presence of bias in artificial intelligence has garnered increased attention, with inequities in algorithmic performance being exposed across the fields of criminal justice, education, and welfare services. In health care, the inequitable performance of algorithms across demographic groups may widen health inequalities. Objective: Here, we identify and characterize bias in cardiology algorithms, looking specifically at algorithms used in the management of heart failure. Methods: Stage 1 involved a literature search of PubMed and Web of Science for key terms relating to cardiac machine learning (ML) algorithms. Papers that built ML models to predict cardiac disease were evaluated for their focus on demographic bias in model performance, and open-source data sets were retained for our investigation. Two open-source data sets were identified: (1) the University of California Irvine Heart Failure data set and (2) the University of California Irvine Coronary Artery Disease data set. We reproduced existing algorithms that have been reported for these data sets, tested them for sex biases in algorithm performance, and assessed a range of remediation techniques for their efficacy in reducing inequities. Particular attention was paid to the false negative rate (FNR), due to the clinical significance of underdiagnosis and missed opportunities for treatment. Results: In stage 1, our literature search returned 127 papers, with 60 meeting the criteria for a full review and only 3 papers highlighting sex differences in algorithm performance. In the papers that reported sex, there was a consistent underrepresentation of female patients in the data sets. No papers investigated racial or ethnic differences. In stage 2, we reproduced algorithms reported in the literature, achieving mean accuracies of 84.24% (SD 3.51%) for data set 1 and 85.72% (SD 1.75%) for data set 2 (random forest models). For data set 1, the FNR was significantly higher for female patients in 13 out of 16 experiments, meeting the threshold of statistical significance (?17.81% to ?3.37%; P<.05). A smaller disparity in the false positive rate was significant for male patients in 13 out of 16 experiments (?0.48% to +9.77%; P<.05). We observed an overprediction of disease for male patients (higher false positive rate) and an underprediction of disease for female patients (higher FNR). Sex differences in feature importance suggest that feature selection needs to be demographically tailored. Conclusions: Our research exposes a significant gap in cardiac ML research, highlighting that the underperformance of algorithms for female patients has been overlooked in the published literature. Our study quantifies sex disparities in algorithmic performance and explores several sources of bias. We found an underrepresentation of female patients in the data sets used to train algorithms, identified sex biases in model error rates, and demonstrated that a series of remediation techniques were unable to address the inequities present. UR - https://www.jmir.org/2024/1/e46936 UR - http://dx.doi.org/10.2196/46936 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/46936 ER - TY - JOUR AU - Ding, Yi AU - Wu, Xianglin AU - Cao, Qiuyu AU - Huang, Jiaojiao AU - Xu, Xiaoli AU - Jiang, Youjin AU - Huo, Yanan AU - Wan, Qin AU - Qin, Yingfen AU - Hu, Ruying AU - Shi, Lixin AU - Su, Qing AU - Yu, Xuefeng AU - Yan, Li AU - Qin, Guijun AU - Tang, Xulei AU - Chen, Gang AU - Xu, Min AU - Wang, Tiange AU - Zhao, Zhiyun AU - Gao, Zhengnan AU - Wang, Guixia AU - Shen, Feixia AU - Luo, Zuojie AU - Chen, Li AU - Li, Qiang AU - Ye, Zhen AU - Zhang, Yinfei AU - Liu, Chao AU - Wang, Youmin AU - Yang, Tao AU - Deng, Huacong AU - Chen, Lulu AU - Zeng, Tianshu AU - Zhao, Jiajun AU - Mu, Yiming AU - Wu, Shengli AU - Chen, Yuhong AU - Lu, Jieli AU - Wang, Weiqing AU - Ning, Guang AU - Xu, Yu AU - Bi, Yufang AU - Li, Mian PY - 2024/8/23 TI - Gender Disparities in the Association Between Educational Attainment and Cardiovascular-Kidney-Metabolic Syndrome: Cross-Sectional Study JO - JMIR Public Health Surveill SP - e57920 VL - 10 KW - cardiovascular-kidney-metabolic syndrome KW - education KW - health behavior KW - sex difference KW - cross-sectional study KW - gender N2 - Background: Cardiovascular-kidney-metabolic (CKM) health is affected by social determinants of health, especially education. CKM syndrome has not been evaluated in Chinese population, and the association of education with CKM syndrome in different sexes and its intertwined relation with lifestyles have not been explored. Objective: We aimed to explore the association between educational attainment and the prevalence of CKM syndrome stages in middle-aged and older Chinese men and women as well as the potential role of health behavior based on Life?s Essential 8 construct. Methods: This study used data from the nationwide, community-based REACTION (Risk Evaluation of Cancers in Chinese diabetic individuals: a longitudinal study). A total of 132,085 participants with complete information to determine CKM syndrome stage and education level were included. Educational attainment was assessed by the self-reported highest educational level achieved by the participants and recategorized as low (elementary school or no formal education) or high (middle school, high school, technical school/college, or above). CKM syndrome was ascertained and classified into 5 stages according to the American Heart Association presidential advisory released in 2023. Results: Among 132,085 participants (mean age 56.95, SD 9.19 years; n=86,675, 65.62% women) included, most had moderate-risk CKM syndrome (stages 1 and 2), and a lower proportion were at higher risk of CKM (stages 3 and 4). Along the CKM continuum, low education was associated with 34% increased odds of moderate-risk CKM syndrome for women (odds ratio 1.36, 95% CI 1.23-1.49) with a significant sex disparity, but was positively correlated with high-risk CKM for both sexes. The association between low education and high-risk CKM was more evident in women with poor health behavior but not in men, which was also interactive with and partly mediated by behavior. Conclusions: Low education was associated with adverse CKM health for both sexes but was especially detrimental to women. Such sex-specific educational disparity was closely correlated with health behavior but could not be completely attenuated by behavior modification. These findings highlight the disadvantage faced by women in CKM health ascribed to low education, underscoring the need for public health support to address this inequality. UR - https://publichealth.jmir.org/2024/1/e57920 UR - http://dx.doi.org/10.2196/57920 ID - info:doi/10.2196/57920 ER - TY - JOUR AU - Nare, Matthew AU - Jurewicz, Katherina PY - 2024/8/6 TI - Assessing Patient Trust in Automation in Health Care Systems: Within-Subjects Experimental Study JO - JMIR Hum Factors SP - e48584 VL - 11 KW - automation KW - emergency department KW - trust KW - health care KW - artificial intelligence KW - emergency KW - perceptions KW - attitude KW - opinions KW - belief KW - automated KW - trust ratings N2 - Background: Health care technology has the ability to change patient outcomes for the betterment when designed appropriately. Automation is becoming smarter and is increasingly being integrated into health care work systems. Objective: This study focuses on investigating trust between patients and an automated cardiac risk assessment tool (CRAT) in a simulated emergency department setting. Methods: A within-subjects experimental study was performed to investigate differences in automation modes for the CRAT: (1) no automation, (2) automation only, and (3) semiautomation. Participants were asked to enter their simulated symptoms for each scenario into the CRAT as instructed by the experimenter, and they would automatically be classified as high, medium, or low risk depending on the symptoms entered. Participants were asked to provide their trust ratings for each combination of risk classification and automation mode on a scale of 1 to 10 (1=absolutely no trust and 10=complete trust). Results: Results from this study indicate that the participants significantly trusted the semiautomation condition more compared to the automation-only condition (P=.002), and they trusted the no automation condition significantly more than the automation-only condition (P=.03). Additionally, participants significantly trusted the CRAT more in the high-severity scenario compared to the medium-severity scenario (P=.004). Conclusions: The findings from this study emphasize the importance of the human component of automation when designing automated technology in health care systems. Automation and artificially intelligent systems are becoming more prevalent in health care systems, and this work emphasizes the need to consider the human element when designing automation into care delivery. UR - https://humanfactors.jmir.org/2024/1/e48584 UR - http://dx.doi.org/10.2196/48584 UR - http://www.ncbi.nlm.nih.gov/pubmed/39106096 ID - info:doi/10.2196/48584 ER - TY - JOUR AU - Kapoor, Melissa AU - Holman, Blair AU - Cohen, Carolyn PY - 2024/8/5 TI - Contactless and Calibration-Free Blood Pressure and Pulse Rate Monitor for Screening and Monitoring of Hypertension: Cross-Sectional Validation Study JO - JMIR Cardio SP - e57241 VL - 8 KW - remote photoplethysmography KW - vital signs KW - calibration-free blood pressure monitor KW - medical device KW - hypertension screening KW - home blood pressure monitoring KW - vital KW - vitals KW - device KW - devices KW - hypertension KW - hypertensive KW - cardiovascular KW - cardiology KW - heart KW - blood pressure KW - monitoring KW - monitor KW - mHealth KW - mobile health KW - validation N2 - Background: The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors. Objective: This study aims to investigate the accuracy of a contactless BP monitor software app for classifying the full range of clinically relevant BPs as hypertensive or nonhypertensive and to evaluate its accuracy for measuring the pulse rate (PR) and BP of people with BPs relevant to stage-1 hypertension. Methods: The software app, known commercially as Lifelight, was investigated following the data collection and data analysis methodology outlined in International Organization for Standardization (ISO) 81060-2:2018/AMD 1:2020 ?Non-invasive Sphygmomanometers?Part 2: Clinical investigation of automated measurement type.? This validation study was conducted by the independent laboratory Element Materials Technology Boulder (formerly Clinimark). The study generated data from 85 people aged 18-85 years with a wide-ranging distribution of BPs specified in ISO 81060-2:2018/AMD 1:2020. At least 20% were required to have Fitzpatrick scale skin tones of 5 or 6 (ie, dark skin tones). The accuracy of the app?s BP measurements was assessed by comparing its BP measurements with measurements made by dual-observer manual auscultation using the same-arm sequential method specified in ISO 81060-2:2018/AMD 1:2020. The accuracy of the app?s PR measurements was assessed by comparing its measurements with concurrent electroencephalography-derived heart rate values. Results: The app measured PR with an accuracy root-mean-square of 1.3 beats per minute and mean absolute error of 1.1 (SD 0.8) beats per minute. The sensitivity and specificity with which it determined that BPs exceeded the in-clinic systolic threshold for hypertension diagnosis were 70.1% and 71.7%, respectively. These rates are consistent with those reported for conventional BP monitors in a literature review by The National Institute for Health and Care Excellence. The app?s mean error for measuring BP in the range of normotension and stage-1 hypertension (ie, 65/85, 76% of participants) was 6.5 (SD 12.9) mm Hg for systolic BP and 0.4 (SD 10.6) mm Hg for diastolic BP. Mean absolute error was 11.3 (SD 10.0) mm Hg and 8.6 (SD 6.8) mm Hg, respectively. Conclusions: A calibration-free, software-only medical device was independently tested against ISO 81060-2:2018/AMD 1:2020. The safety and performance demonstrated in this study suggest that this technique could be a potential solution for rapid and scalable screening and management of hypertension. UR - https://cardio.jmir.org/2024/1/e57241 UR - http://dx.doi.org/10.2196/57241 UR - http://www.ncbi.nlm.nih.gov/pubmed/39102277 ID - info:doi/10.2196/57241 ER - TY - JOUR AU - Liu, Chang AU - Zhang, Kai AU - Yang, Xiaodong AU - Meng, Bingbing AU - Lou, Jingsheng AU - Liu, Yanhong AU - Cao, Jiangbei AU - Liu, Kexuan AU - Mi, Weidong AU - Li, Hao PY - 2024/7/26 TI - Development and Validation of an Explainable Machine Learning Model for Predicting Myocardial Injury After Noncardiac Surgery in Two Centers in China: Retrospective Study JO - JMIR Aging SP - e54872 VL - 7 KW - myocardial injury after noncardiac surgery KW - older patients KW - machine learning KW - personalized prediction KW - myocardial injury KW - risk prediction KW - noncardiac surgery N2 - Background: Myocardial injury after noncardiac surgery (MINS) is an easily overlooked complication but closely related to postoperative cardiovascular adverse outcomes; therefore, the early diagnosis and prediction are particularly important. Objective: We aimed to develop and validate an explainable machine learning (ML) model for predicting MINS among older patients undergoing noncardiac surgery. Methods: The retrospective cohort study included older patients who had noncardiac surgery from 1 northern center and 1 southern center in China. The data sets from center 1 were divided into a training set and an internal validation set. The data set from center 2 was used as an external validation set. Before modeling, the least absolute shrinkage and selection operator and recursive feature elimination methods were used to reduce dimensions of data and select key features from all variables. Prediction models were developed based on the extracted features using several ML algorithms, including category boosting, random forest, logistic regression, naïve Bayes, light gradient boosting machine, extreme gradient boosting, support vector machine, and decision tree. Prediction performance was assessed by the area under the receiver operating characteristic (AUROC) curve as the main evaluation metric to select the best algorithms. The model performance was verified by internal and external validation data sets with the best algorithm and compared to the Revised Cardiac Risk Index. The Shapley Additive Explanations (SHAP) method was applied to calculate values for each feature, representing the contribution to the predicted risk of complication, and generate personalized explanations. Results: A total of 19,463 eligible patients were included; among those, 12,464 patients in center 1 were included as the training set; 4754 patients in center 1 were included as the internal validation set; and 2245 in center 2 were included as the external validation set. The best-performing model for prediction was the CatBoost algorithm, achieving the highest AUROC of 0.805 (95% CI 0.778?0.831) in the training set, validating with an AUROC of 0.780 in the internal validation set and 0.70 in external validation set. Additionally, CatBoost demonstrated superior performance compared to the Revised Cardiac Risk Index (AUROC 0.636; P<.001). The SHAP values indicated the ranking of the level of importance of each variable, with preoperative serum creatinine concentration, red blood cell distribution width, and age accounting for the top three. The results from the SHAP method can predict events with positive values or nonevents with negative values, providing an explicit explanation of individualized risk predictions. Conclusions: The ML models can provide a personalized and fairly accurate risk prediction of MINS, and the explainable perspective can help identify potentially modifiable sources of risk at the patient level. UR - https://aging.jmir.org/2024/1/e54872 UR - http://dx.doi.org/10.2196/54872 ID - info:doi/10.2196/54872 ER - TY - JOUR AU - van den Beuken, F. Wisse M. AU - van Schuppen, Hans AU - Demirtas, Derya AU - van Halm, P. Vokko AU - van der Geest, Patrick AU - Loer, A. Stephan AU - Schwarte, A. Lothar AU - Schober, Patrick PY - 2024/7/25 TI - Investigating Users? Attitudes Toward Automated Smartwatch Cardiac Arrest Detection: Cross-Sectional Survey Study JO - JMIR Hum Factors SP - e57574 VL - 11 KW - out-of-hospital cardiac arrest KW - wearables KW - wearable KW - digital health KW - smartwatch KW - automated cardiac arrest detection KW - emergency medicine KW - emergency KW - cardiology KW - heart KW - cardiac KW - cross sectional KW - survey KW - surveys KW - questionnaire KW - questionnaires KW - experience KW - experiences KW - attitude KW - attitudes KW - opinion KW - perception KW - perceptions KW - perspective KW - perspectives KW - acceptance KW - adoption KW - willingness KW - intent KW - intention N2 - Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival. Objective: This cross-sectional survey study aims to investigate users? perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology. Methods: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted. Results: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility. Conclusions: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology. UR - https://humanfactors.jmir.org/2024/1/e57574 UR - http://dx.doi.org/10.2196/57574 ID - info:doi/10.2196/57574 ER - TY - JOUR AU - Markovi?, Rene AU - Ternar, Luka AU - Trstenjak, Tim AU - Marhl, Marko AU - Grubelnik, Vladimir PY - 2024/7/24 TI - Cardiovascular Comorbidities in COVID-19: Comprehensive Analysis of Key Topics JO - Interact J Med Res SP - e55699 VL - 13 KW - COVID-19 KW - cardiovascular diseases KW - metabolic disorders KW - embolism and thrombosis KW - hypertension KW - hyperglycemia KW - iron metabolism disorders KW - MeSH KW - embolism KW - thrombosis KW - heart failure KW - nutritional KW - vascular disease KW - glucose KW - effective N2 - Background: The interrelation between COVID-19 and various cardiovascular and metabolic disorders has been a critical area of study. There is a growing need to understand how comorbidities such as cardiovascular diseases (CVDs) and metabolic disorders affect the risk and severity of COVID-19. Objective: The objective of this study is to systematically analyze the association between COVID-19 and cardiovascular and metabolic disorders. The focus is on comorbidity, examining the roles of CVDs such as embolism, thrombosis, hypertension, and heart failure, as well as metabolic disorders such as disorders of glucose and iron metabolism. Methods: Our study involved a systematic search in PubMed for literature published from 2000 to 2022. We established 2 databases: one for COVID-19?related articles and another for CVD-related articles, ensuring all were peer-reviewed. In terms of data analysis, statistical methods were applied to compare the frequency and relevance of MeSH (Medical Subject Headings) terms between the 2 databases. This involved analyzing the differences and ratios in the usage of these terms and employing statistical tests to determine their significance in relation to key CVDs within the COVID-19 research context. Results: The study revealed that ?Cardiovascular Diseases? and ?Nutritional and Metabolic Diseases? were highly relevant as level 1 Medical Subject Headings descriptors in COVID-19 comorbidity research. Detailed analysis at level 2 and level 3 showed ?Vascular Disease? and ?Heart Disease? as prominent descriptors under CVDs. Significantly, ?Glucose Metabolism Disorders? were frequently associated with COVID-19 comorbidities such as embolism, thrombosis, and heart failure. Furthermore, iron deficiency (ID) was notably different in its occurrence between COVID-19 and CVD articles, underlining its significance in the context of COVID-19 comorbidities. Statistical analysis underscored these differences, highlighting the importance of both glucose and iron metabolism disorders in COVID-19 research. Conclusions: This work lays the foundation for future research that utilizes a knowledge-based approach to elucidate the intricate relationships between these conditions, aiming to develop more effective health care strategies and interventions in the face of ongoing pandemic challenges. UR - https://www.i-jmr.org/2024/1/e55699 UR - http://dx.doi.org/10.2196/55699 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/55699 ER - TY - JOUR AU - Fan, Jiaqi AU - Dai, Hanyi AU - Guo, Yuchao AU - Xu, Jianguo AU - Wang, Lihan AU - Jiang, Jubo AU - Lin, Xinping AU - Li, Cheng AU - Zhou, Dao AU - Li, Huajun AU - Liu, Xianbao AU - Wang, Jian'an PY - 2024/7/19 TI - Smartwatch-Detected Arrhythmias in Patients After Transcatheter Aortic Valve Replacement (TAVR): Analysis of the SMART TAVR Trial JO - J Med Internet Res SP - e41843 VL - 26 KW - arrhythmias KW - transcatheter aortic valve replacement KW - smartwatch KW - ambulatory electrocardiography KW - smartphone KW - mobile phone N2 - Background: There are limited data available on the development of arrhythmias in patients at risk of high-degree atrioventricular block (HAVB) or complete heart block (CHB) following transcatheter aortic valve replacement (TAVR). Objective: This study aimed to explore the incidence and evolution of arrhythmias by monitoring patients at risk of HAVB or CHB after TAVR using smartwatches. Methods: We analyzed 188 consecutive patients in the prospective SMART TAVR (smartwatch-facilitated early discharge in patients undergoing TAVR) trial. Patients were divided into 2 groups according to the risk of HAVB or CHB. Patients were required to trigger a single-lead electrocardiogram (ECG) recording and send it to the Heart Health App via their smartphone. Physicians in the central ECG core lab would then analyze the ECG. The incidence and timing of arrhythmias and pacemaker implantation within a 30-day follow-up were compared. All arrhythmic events were adjudicated in a central ECG core lab. Results: The mean age of the patients was 73.1 (SD 7.3) years, of whom 105 (55.9%) were men. The mean discharge day after TAVR was 2.0 (SD 1.8) days. There were no statistically significant changes in the evolution of atrial fibrillation or atrial flutter, Mobitz I, Mobitz II, and third-degree atrial ventricular block over time in the first month after TAVR. The incidence of the left bundle branch block (LBBB) increased in the first week and decreased in the subsequent 3 weeks significantly (P<.001). Patients at higher risk of HAVB or CHB received more pacemaker implantation after discharge (n=8, 9.6% vs n=2, 1.9%; P=.04). The incidence of LBBB was higher in the group with higher HAVB or CHB risk (n=47, 56.6% vs n=34, 32.4%; P=.001). The independent predictors for pacemaker implantation were age, baseline atrial fibrillation, baseline right bundle branch block, Mobitz II, and third-degree atrioventricular block detected by the smartwatch. Conclusions: Except for LBBB, no change in arrhythmias was observed over time in the first month after TAVR. A higher incidence of pacemaker implantation after discharge was observed in patients at risk of HAVB or CHB. However, Mobitz II and third-degree atrioventricular block detected by the smartwatch during follow-ups were more valuable indicators to predict pacemaker implantation after discharge from the index TAVR. Trial Registration: ClinicalTrials.gov NCT04454177; https://clinicaltrials.gov/study/NCT04454177 UR - https://www.jmir.org/2024/1/e41843 UR - http://dx.doi.org/10.2196/41843 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/41843 ER - TY - JOUR AU - Zondag, M. Anna G. AU - Hollestelle, J. Marieke AU - van der Graaf, Rieke AU - Nathoe, M. Hendrik AU - van Solinge, W. Wouter AU - Bots, L. Michiel AU - Vernooij, M. Robin W. AU - Haitjema, Saskia AU - PY - 2024/7/11 TI - Comparison of the Response to an Electronic Versus a Traditional Informed Consent Procedure in Terms of Clinical Patient Characteristics: Observational Study JO - J Med Internet Res SP - e54867 VL - 26 KW - informed consent KW - learning health care system KW - e-consent KW - cardiovascular risk management KW - digital health KW - research ethics N2 - Background: Electronic informed consent (eIC) is increasingly used in clinical research due to several benefits including increased enrollment and improved efficiency. Within a learning health care system, a pilot was conducted with an eIC for linking data from electronic health records with national registries, general practitioners, and other hospitals. Objective: We evaluated the eIC pilot by comparing the response to the eIC with the former traditional paper-based informed consent (IC). We assessed whether the use of eIC resulted in a different study population by comparing the clinical patient characteristics between the response categories of the eIC and former face-to-face IC procedure. Methods: All patients with increased cardiovascular risk visiting the University Medical Center Utrecht, the Netherlands, were eligible for the learning health care system. From November 2021 to August 2022, an eIC was piloted at the cardiology outpatient clinic. Prior to the pilot, a traditional face-to-face paper-based IC approach was used. Responses (ie, consent, no consent, or nonresponse) were assessed and compared between the eIC and face-to-face IC cohorts. Clinical characteristics of consenting and nonresponding patients were compared between and within the eIC and the face-to-face cohorts using multivariable regression analyses. Results: A total of 2254 patients were included in the face-to-face IC cohort and 885 patients in the eIC cohort. Full consent was more often obtained in the eIC than in the face-to-face cohort (415/885, 46.9% vs 876/2254, 38.9%, respectively). Apart from lower mean hemoglobin in the full consent group of the eIC cohort (8.5 vs 8.8; P=.0021), the characteristics of the full consenting patients did not differ between the eIC and face-to-face IC cohorts. In the eIC cohort, only age differed between the full consent and the nonresponse group (median 60 vs 56; P=.0002, respectively), whereas in the face-to-face IC cohort, the full consent group seemed healthier (ie, higher hemoglobin, lower glycated hemoglobin [HbA1c], lower C-reactive protein levels) than the nonresponse group. Conclusions: More patients provided full consent using an eIC. In addition, the study population remained broadly similar. The face-to-face IC approach seemed to result in a healthier study population (ie, full consenting patients) than the patients without IC, while in the eIC cohort, the characteristics between consent groups were comparable. Thus, an eIC may lead to a better representation of the target population, increasing the generalizability of results. UR - https://www.jmir.org/2024/1/e54867 UR - http://dx.doi.org/10.2196/54867 UR - http://www.ncbi.nlm.nih.gov/pubmed/38990640 ID - info:doi/10.2196/54867 ER - TY - JOUR AU - Jo, Eunbeen AU - Song, Sanghoun AU - Kim, Jong-Ho AU - Lim, Subin AU - Kim, Hyeon Ju AU - Cha, Jung-Joon AU - Kim, Young-Min AU - Joo, Joon Hyung PY - 2024/7/8 TI - Assessing GPT-4?s Performance in Delivering Medical Advice: Comparative Analysis With Human Experts JO - JMIR Med Educ SP - e51282 VL - 10 KW - GPT-4 KW - medical advice KW - ChatGPT KW - cardiology KW - cardiologist KW - heart KW - advice KW - recommendation KW - recommendations KW - linguistic KW - linguistics KW - artificial intelligence KW - NLP KW - natural language processing KW - chatbot KW - chatbots KW - conversational agent KW - conversational agents KW - response KW - responses N2 - Background: Accurate medical advice is paramount in ensuring optimal patient care, and misinformation can lead to misguided decisions with potentially detrimental health outcomes. The emergence of large language models (LLMs) such as OpenAI?s GPT-4 has spurred interest in their potential health care applications, particularly in automated medical consultation. Yet, rigorous investigations comparing their performance to human experts remain sparse. Objective: This study aims to compare the medical accuracy of GPT-4 with human experts in providing medical advice using real-world user-generated queries, with a specific focus on cardiology. It also sought to analyze the performance of GPT-4 and human experts in specific question categories, including drug or medication information and preliminary diagnoses. Methods: We collected 251 pairs of cardiology-specific questions from general users and answers from human experts via an internet portal. GPT-4 was tasked with generating responses to the same questions. Three independent cardiologists (SL, JHK, and JJC) evaluated the answers provided by both human experts and GPT-4. Using a computer interface, each evaluator compared the pairs and determined which answer was superior, and they quantitatively measured the clarity and complexity of the questions as well as the accuracy and appropriateness of the responses, applying a 3-tiered grading scale (low, medium, and high). Furthermore, a linguistic analysis was conducted to compare the length and vocabulary diversity of the responses using word count and type-token ratio. Results: GPT-4 and human experts displayed comparable efficacy in medical accuracy (?GPT-4 is better? at 132/251, 52.6% vs ?Human expert is better? at 119/251, 47.4%). In accuracy level categorization, humans had more high-accuracy responses than GPT-4 (50/237, 21.1% vs 30/238, 12.6%) but also a greater proportion of low-accuracy responses (11/237, 4.6% vs 1/238, 0.4%; P=.001). GPT-4 responses were generally longer and used a less diverse vocabulary than those of human experts, potentially enhancing their comprehensibility for general users (sentence count: mean 10.9, SD 4.2 vs mean 5.9, SD 3.7; P<.001; type-token ratio: mean 0.69, SD 0.07 vs mean 0.79, SD 0.09; P<.001). Nevertheless, human experts outperformed GPT-4 in specific question categories, notably those related to drug or medication information and preliminary diagnoses. These findings highlight the limitations of GPT-4 in providing advice based on clinical experience. Conclusions: GPT-4 has shown promising potential in automated medical consultation, with comparable medical accuracy to human experts. However, challenges remain particularly in the realm of nuanced clinical judgment. Future improvements in LLMs may require the integration of specific clinical reasoning pathways and regulatory oversight for safe use. Further research is needed to understand the full potential of LLMs across various medical specialties and conditions. UR - https://mededu.jmir.org/2024/1/e51282 UR - http://dx.doi.org/10.2196/51282 ID - info:doi/10.2196/51282 ER - TY - JOUR AU - Liang, Huey-Wen AU - Wu, Chueh-Hung AU - Lin, Chen AU - Chang, Hsiang-Chih AU - Lin, Yu-Hsuan AU - Chen, Shao-Yu AU - Hsu, Wei-Chen PY - 2024/7/4 TI - Rest-Activity Rhythm Differences in Acute Rehabilitation Between Poststroke Patients and Non?Brain Disease Controls: Comparative Study JO - J Med Internet Res SP - e49530 VL - 26 KW - circadian rhythms KW - stroke rehabilitation, rest-activity rhythms, relative amplitude, delirium screening, interdaily stability N2 - Background: Circadian rhythm disruptions are a common concern for poststroke patients undergoing rehabilitation and might negatively impact their functional outcomes. Objective: Our research aimed to uncover unique patterns and disruptions specific to poststroke rehabilitation patients and identify potential differences in specific rest-activity rhythm indicators when compared to inpatient controls with non?brain-related lesions, such as patients with spinal cord injuries. Methods: We obtained a 7-day recording with a wearable actigraphy device from 25 poststroke patients (n=9, 36% women; median age 56, IQR 46-71) and 25 age- and gender-matched inpatient control participants (n=15, 60% women; median age 57, IQR 46.5-68.5). To assess circadian rhythm, we used a nonparametric method to calculate key rest-activity rhythm indicators?relative amplitude, interdaily stability, and intradaily variability. Relative amplitude, quantifying rest-activity rhythm amplitude while considering daily variations and unbalanced amplitudes, was calculated as the ratio of the difference between the most active 10 continuous hours and the least active 5 continuous hours to the sum of these 10 and 5 continuous hours. We also examined the clinical correlations between rest-activity rhythm indicators and delirium screening tools, such as the 4 A?s Test and the Barthel Index, which assess delirium and activities of daily living. Results: Patients who had a stroke had higher least active 5-hour values compared to the control group (median 4.29, IQR 2.88-6.49 vs median 1.84, IQR 0.67-4.34; P=.008). The most active 10-hour values showed no significant differences between the groups (stroke group: median 38.92, IQR 14.60-40.87; control group: median 31.18, IQR 18.02-46.84; P=.93). The stroke group presented a lower relative amplitude compared to the control group (median 0.74, IQR 0.57-0.85 vs median 0.88, IQR 0.71-0.96; P=.009). Further analysis revealed no significant differences in other rest-activity rhythm metrics between the two groups. Among the patients who had a stroke, a negative correlation was observed between the 4 A?s Test scores and relative amplitude (?=?0.41; P=.045). Across all participants, positive correlations emerged between the Barthel Index scores and both interdaily stability (?=0.34; P=.02) and the most active 10-hour value (?=0.42; P=.002). Conclusions: This study highlights the relevance of circadian rhythm disruptions in poststroke rehabilitation and provides insights into potential diagnostic and prognostic implications for rest-activity rhythm indicators as digital biomarkers. UR - https://www.jmir.org/2024/1/e49530 UR - http://dx.doi.org/10.2196/49530 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/49530 ER - TY - JOUR AU - Cho, Youngjin AU - Yoon, Minjae AU - Kim, Joonghee AU - Lee, Hyun Ji AU - Oh, Il-Young AU - Lee, Joo Chan AU - Kang, Seok-Min AU - Choi, Dong-Ju PY - 2024/7/3 TI - Artificial Intelligence?Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study JO - J Med Internet Res SP - e52139 VL - 26 KW - acute heart failure KW - electrocardiography KW - artificial intelligence KW - deep learning N2 - Background: Although several biomarkers exist for patients with heart failure (HF), their use in routine clinical practice is often constrained by high costs and limited availability. Objective: We examined the utility of an artificial intelligence (AI) algorithm that analyzes printed electrocardiograms (ECGs) for outcome prediction in patients with acute HF. Methods: We retrospectively analyzed prospectively collected data of patients with acute HF at two tertiary centers in Korea. Baseline ECGs were analyzed using a deep-learning system called Quantitative ECG (QCG), which was trained to detect several urgent clinical conditions, including shock, cardiac arrest, and reduced left ventricular ejection fraction (LVEF). Results: Among the 1254 patients enrolled, in-hospital cardiac death occurred in 53 (4.2%) patients, and the QCG score for critical events (QCG-Critical) was significantly higher in these patients than in survivors (mean 0.57, SD 0.23 vs mean 0.29, SD 0.20; P<.001). The QCG-Critical score was an independent predictor of in-hospital cardiac death after adjustment for age, sex, comorbidities, HF etiology/type, atrial fibrillation, and QRS widening (adjusted odds ratio [OR] 1.68, 95% CI 1.47-1.92 per 0.1 increase; P<.001), and remained a significant predictor after additional adjustments for echocardiographic LVEF and N-terminal prohormone of brain natriuretic peptide level (adjusted OR 1.59, 95% CI 1.36-1.87 per 0.1 increase; P<.001). During long-term follow-up, patients with higher QCG-Critical scores (>0.5) had higher mortality rates than those with low QCG-Critical scores (<0.25) (adjusted hazard ratio 2.69, 95% CI 2.14-3.38; P<.001). Conclusions: Predicting outcomes in patients with acute HF using the QCG-Critical score is feasible, indicating that this AI-based ECG score may be a novel biomarker for these patients. Trial Registration: ClinicalTrials.gov NCT01389843; https://clinicaltrials.gov/study/NCT01389843 UR - https://www.jmir.org/2024/1/e52139 UR - http://dx.doi.org/10.2196/52139 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/52139 ER - TY - JOUR AU - Razjouyan, Javad AU - Orkaby, R. Ariela AU - Horstman, J. Molly AU - Goyal, Parag AU - Intrator, Orna AU - Naik, D. Aanand PY - 2024/6/27 TI - The Frailty Trajectory?s Additional Edge Over the Frailty Index: Retrospective Cohort Study of Veterans With Heart Failure JO - JMIR Aging SP - e56345 VL - 7 KW - gerontology KW - geriatric KW - geriatrics KW - older adult KW - older adults KW - elder KW - elderly KW - older person KW - older people KW - ageing KW - aging KW - frailty KW - frailty index KW - frailty trajectory KW - frail KW - weak KW - weakness KW - heart failure KW - HF KW - cardiovascular disease KW - CVD KW - congestive heart failure KW - CHF KW - myocardial infarction KW - MI KW - unstable angina KW - angina KW - cardiac arrest KW - atherosclerosis KW - cardiology KW - cardiac KW - cardiologist KW - cardiologists UR - https://aging.jmir.org/2024/1/e56345 UR - http://dx.doi.org/10.2196/56345 ID - info:doi/10.2196/56345 ER - TY - JOUR AU - Zhu, Lingxuan AU - Mou, Weiming AU - Wu, Keren AU - Lai, Yancheng AU - Lin, Anqi AU - Yang, Tao AU - Zhang, Jian AU - Luo, Peng PY - 2024/6/26 TI - Multimodal ChatGPT-4V for Electrocardiogram Interpretation: Promise and Limitations JO - J Med Internet Res SP - e54607 VL - 26 KW - ChatGPT KW - ECG KW - electrocardiogram KW - multimodal KW - artificial intelligence KW - AI KW - large language model KW - diagnostic KW - quantitative analysis KW - clinical KW - clinicians KW - ECG interpretation KW - cardiovascular care KW - cardiovascular UR - https://www.jmir.org/2024/1/e54607 UR - http://dx.doi.org/10.2196/54607 UR - http://www.ncbi.nlm.nih.gov/pubmed/38764297 ID - info:doi/10.2196/54607 ER - TY - JOUR AU - Lee, Heekyung AU - Oh, Jaehoon AU - Choi, Joong Hyuk AU - Shin, Hyungoo AU - Cho, Yongil AU - Lee, Juncheol PY - 2024/6/24 TI - The Incidence and Outcomes of Out-of-Hospital Cardiac Arrest During the COVID-19 Pandemic in South Korea: Multicenter Registry Study JO - JMIR Public Health Surveill SP - e52402 VL - 10 KW - heart arrest KW - cardiopulmonary resuscitation KW - SARS-CoV-2 KW - mortality KW - outpatient KW - cardiac arrest KW - multicenter registry study KW - out-of-hospital cardiac arrest KW - heart attack KW - observational study KW - adult KW - older adults KW - analysis KW - pandemic KW - prepandemic KW - endemic KW - defibrillator KW - COVID-19 N2 - Background: The COVID-19 pandemic has profoundly affected out-of-hospital cardiac arrest (OHCA) and disrupted the chain of survival. Even after the end of the pandemic, the risk of new variants and surges persists. Analyzing the characteristics of OHCA during the pandemic is important to prepare for the next pandemic and to avoid repeated negative outcomes. However, previous studies have yielded somewhat varied results, depending on the health care system or the specific characteristics of social structures. Objective: We aimed to investigate and compare the incidence, outcomes, and characteristics of OHCA during the prepandemic and pandemic periods using data from a nationwide multicenter OHCA registry. Methods: We conducted a multicenter, retrospective, observational study using data from the Korean Cardiac Arrest Resuscitation Consortium (KoCARC) registry. This study included adult patients with OHCA in South Korea across 3 distinct 1-year periods: the prepandemic period (from January to December 2019), early phase pandemic period (from July 2020 to June 2021), and late phase pandemic period (from July 2021 to June 2022). We extracted and contrasted the characteristics of patients with OHCA, prehospital time factors, and outcomes for the patients across these 3 periods. The primary outcomes were survival to hospital admission and survival to hospital discharge. The secondary outcome was good neurological outcome. Results: From the 3 designated periods, a total of 9031 adult patients with OHCA were eligible for analysis (prepandemic: n=2728; early pandemic: n=2954; and late pandemic: n=3349). Witnessed arrest (P<.001) and arrest at home or residence (P=.001) were significantly more frequent during the pandemic period than during the prepandemic period, and automated external defibrillator use by bystanders was lower in the early phase of the pandemic than during other periods. As the pandemic advanced, the rates of the first monitored shockable rhythm (P=.10) and prehospital endotracheal intubation (P<.001) decreased significantly. Time from cardiac arrest cognition to emergency department arrival increased sequentially (prepandemic: 33 min; early pandemic: 35 min; and late pandemic: 36 min; P<.001). Both survival and neurological outcomes worsened as the pandemic progressed, with survival to discharge showing the largest statistical difference (prepandemic: 385/2728, 14.1%; early pandemic: 355/2954, 12%; and late pandemic: 392/3349, 11.7%; P=.01). Additionally, none of the outcomes differed significantly between the early and late phase pandemic periods (all P>.05). Conclusions: During the pandemic, especially amid community COVID-19 surges, the incidence of OHCA increased while survival rates and good neurological outcome at discharge decreased. Prehospital OHCA factors, which are directly related to OHCA prognosis, were adversely affected by the pandemic. Ongoing discussions are needed to maintain the chain of survival in the event of a new pandemic. Trial Registration: ClinicalTrials.gov NCT03222999; https://classic.clinicaltrials.gov/ct2/show/NCT03222999 UR - https://publichealth.jmir.org/2024/1/e52402 UR - http://dx.doi.org/10.2196/52402 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/52402 ER - TY - JOUR AU - Agyei, Frimponmaa Eunice Eno Yaa AU - Ekpezu, Akon AU - Oinas-Kukkonen, Harri PY - 2024/6/19 TI - Persuasive Systems Design Trends in Coronary Heart Disease Management: Scoping Review of Randomized Controlled Trials JO - JMIR Cardio SP - e49515 VL - 8 KW - coronary heart disease KW - persuasive systems design KW - behavior change KW - randomized controlled trial KW - RCT KW - controlled trials KW - heart KW - CHD KW - cardiovascular N2 - Background: Behavior change support systems (BCSSs) have the potential to help people maintain healthy lifestyles and aid in the self-management of coronary heart disease (CHD). The Persuasive Systems Design (PSD) model is a framework for designing and evaluating systems designed to support lifestyle modifications and health behavior change using information and communication technology. However, evidence for the underlying design principles behind BCSSs for CHD has not been extensively reported in the literature. Objective: This scoping review aims to identify existing health BCSSs for CHD, report the characteristics of these systems, and describe the persuasion context and persuasive design principles of these systems based on the PSD framework. Methods: Using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, 3 digital databases (Scopus, Web of Science, and MEDLINE) were searched between 2010 to 2022. The major inclusion criteria for studies were in accordance with the PICO (Population, Intervention, Comparison, and Outcome) approach. Results: Searches conducted in the databases identified 1195 papers, among which 30 were identified as eligible for the review. The most interesting characteristics of the BCSSs were the predominant use of primary task support principles, followed by dialogue support and credibility support and the sparing use of social support principles. Theories of behavior change such as the Social Cognitive Theory and Self-Efficacy Theory were used often to underpin these systems. However, significant trends in the use of persuasive system features on par with behavior change theories could not be established from the reviewed studies. This points to the fact that there is still no theoretical consensus on how best to design interventions to promote behavior change in patients with CHD. Conclusions: Our results highlight key software features for designing BCSSs for the prevention and management of CHD. We encourage designers of behavior change interventions to evaluate the techniques that contributed to the success of the intervention. Future research should focus on evaluating the effectiveness of the interventions, persuasive design principles, and behavior change theories using research methodologies such as meta-analysis. UR - https://cardio.jmir.org/2024/1/e49515 UR - http://dx.doi.org/10.2196/49515 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/49515 ER - TY - JOUR AU - Lee, Jun Jae AU - Lee, Hee Kyung PY - 2024/6/11 TI - Optimal Systolic Blood Pressure for the Prevention of All-Cause and Cardiovascular Disease Mortality in Older Adults With Hypertension: Nationwide Population-Based Cohort Study JO - JMIR Public Health Surveill SP - e52182 VL - 10 KW - aged KW - blood pressure KW - cardiovascular diseases KW - hypertension KW - mortality KW - older adults KW - geriatric KW - elderly KW - cardiovascular KW - Korea KW - Korean KW - insurance KW - cohort study KW - systolic KW - risk KW - aging KW - health outcome N2 - Background: Target systolic blood pressure (SBP) levels for older adults with hypertension vary across countries, leading to challenges in determining the appropriate SBP level. Objective: This study aims to identify the optimal SBP level for minimizing all-cause and cardiovascular disease (CVD) mortality in older Korean adults with hypertension. Methods: This retrospective cohort study used data from the National Health Insurance Service database. We included older adults aged 65 years or older who were newly diagnosed with hypertension and underwent a National Health Insurance Service health checkup in 2003-2004. We excluded patients who had a history of hypertension or CVD, were not prescribed medication for hypertension, had missing blood pressure or any other covariate values, and had fewer than 2 health checkups during the follow-up period until 2020. We categorized the average SBP levels into 6 categories in 10 mm Hg increments, from <120 mm Hg to ?160 mm Hg; 130-139 mm Hg was the reference range. Cox proportional hazards models were used to examine the relationship between SBP and all-cause and CVD mortalities, and subgroup analysis was conducted by age group (65-74 years and 75 years or older). Results: A total of 68,901 older adults newly diagnosed with hypertension were included in this study. During the follow-up period, 32,588 (47.3%) participants had all-cause mortality and 4273 (6.2%) had CVD mortality. Compared to older adults with SBP within the range of 130-139 mm Hg, individuals who fell into the other SBP categories, excluding those with SBP 120-129 mm Hg, showed significantly higher all-cause and CVD mortality. Subgroup analysis showed that older adults aged 65-74 years had higher all-cause and CVD mortality rates according to SBP categories than those aged 75 years or older. Conclusions: The SBP levels within the range of 120-139 mm Hg were associated with the lowest all-cause and CVD mortality rates among older Korean adults with hypertension. It is recommended to reduce SBP to <140 mm Hg, with 120 mm Hg as the minimum value for SBP, for older Korean adults with hypertension. Additionally, stricter SBP management is required for adults aged 65-74 years. UR - https://publichealth.jmir.org/2024/1/e52182 UR - http://dx.doi.org/10.2196/52182 UR - http://www.ncbi.nlm.nih.gov/pubmed/38861307 ID - info:doi/10.2196/52182 ER - TY - JOUR AU - Li, ming Yi AU - Jia, Yuheng AU - Bai, Lin AU - Yang, Bosen AU - Chen, Mao AU - Peng, Yong PY - 2024/6/7 TI - U-Shaped Relationship Between Fibrinogen Level and 10-year Mortality in Patients With Acute Coronary Syndrome: Prospective Cohort Study JO - JMIR Public Health Surveill SP - e54485 VL - 10 KW - fibrinogen KW - acute coronary syndrome KW - 10-year mortality KW - risk factor KW - coronary artery disease KW - myocardial KW - heart disease KW - inflammatory factor KW - retrospective study KW - Kaplan-Meier analysis KW - mortality KW - all-cause mortality KW - cubic-spline curve KW - regression model UR - https://publichealth.jmir.org/2024/1/e54485 UR - http://dx.doi.org/10.2196/54485 UR - http://www.ncbi.nlm.nih.gov/pubmed/38848124 ID - info:doi/10.2196/54485 ER - TY - JOUR AU - Eerdekens, Rob AU - Zelis, Jo AU - ter Horst, Herman AU - Crooijmans, Caia AU - van 't Veer, Marcel AU - Keulards, Danielle AU - Kelm, Marcus AU - Archer, Gareth AU - Kuehne, Titus AU - Brueren, Guus AU - Wijnbergen, Inge AU - Johnson, Nils AU - Tonino, Pim PY - 2024/6/3 TI - Cardiac Health Assessment Using a Wearable Device Before and After Transcatheter Aortic Valve Implantation: Prospective Study JO - JMIR Mhealth Uhealth SP - e53964 VL - 12 KW - aortic valve stenosis KW - health watch KW - quality of life KW - heart KW - cardiology KW - cardiac KW - aortic KW - valve KW - stenosis KW - watch KW - smartwatch KW - wearables KW - 6MWT KW - walking KW - test KW - QoL KW - WHOQOL-BREF KW - 6-minute walking test N2 - Background: Due to aging of the population, the prevalence of aortic valve stenosis will increase drastically in upcoming years. Consequently, transcatheter aortic valve implantation (TAVI) procedures will also expand worldwide. Optimal selection of patients who benefit with improved symptoms and prognoses is key, since TAVI is not without its risks. Currently, we are not able to adequately predict functional outcomes after TAVI. Quality of life measurement tools and traditional functional assessment tests do not always agree and can depend on factors unrelated to heart disease. Activity tracking using wearable devices might provide a more comprehensive assessment. Objective: This study aimed to identify objective parameters (eg, change in heart rate) associated with improvement after TAVI for severe aortic stenosis from a wearable device. Methods: In total, 100 patients undergoing routine TAVI wore a Philips Health Watch device for 1 week before and after the procedure. Watch data were analyzed offline?before TAVI for 97 patients and after TAVI for 75 patients. Results: Parameters such as the total number of steps and activity time did not change, in contrast to improvements in the 6-minute walking test (6MWT) and physical limitation domain of the transformed WHOQOL-BREF questionnaire. Conclusions: These findings, in an older TAVI population, show that watch-based parameters, such as the number of steps, do not change after TAVI, unlike traditional 6MWT and QoL assessments. Basic wearable device parameters might be less appropriate for measuring treatment effects from TAVI. UR - https://mhealth.jmir.org/2024/1/e53964 UR - http://dx.doi.org/10.2196/53964 ID - info:doi/10.2196/53964 ER - TY - JOUR AU - Vögeli, Benjamin AU - Arenja, Nisha AU - Schütz, Narayan AU - Nef, Tobias AU - Buluschek, Philipp AU - Saner, Hugo PY - 2024/5/31 TI - Evaluation of Ambient Sensor Systems for the Early Detection of Heart Failure Decompensation in Older Patients Living at Home Alone: Protocol for a Prospective Cohort Study JO - JMIR Res Protoc SP - e55953 VL - 13 KW - heart failure KW - home telemonitoring KW - digital health KW - biomarker KW - ambient sensor system N2 - Background: The results of telemedicine intervention studies in patients with heart failure (HF) to reduce rehospitalization rate and mortality by early detection of HF decompensation are encouraging. However, the benefits are lower than expected. A possible reason for this could be the fact that vital signs, including blood pressure, heart rate, heart rhythm, and weight changes, may not be ideal indicators of the early stages of HF decompensation but are more sensitive for acute events triggered by ischemic episodes or rhythm disturbances. Preliminary results indicate a potential role of ambient sensor?derived digital biomarkers in this setting. Objective: The aim of this study is to identify changes in ambient sensor system?derived digital biomarkers with a high potential for early detection of HF decompensation. Methods: This is a prospective interventional cohort study. A total of 24 consecutive patients with HF aged 70 years and older, living alone, and hospitalized for HF decompensation will be included. Physical activity in the apartment and toilet visits are quantified using a commercially available, passive, infrared motion sensing system (DomoHealth SA). Heart rate, respiration rate, and toss-and-turns in bed are recorded by using a commercially available Emfit QS device (Emfit Ltd), which is a contact-free piezoelectric sensor placed under the participant?s mattress. Sensor data are visualized on a dedicated dashboard for easy monitoring by health professionals. Digital biomarkers are evaluated for predefined signs of HF decompensation, including particularly decreased physical activity; time spent in bed; increasing numbers of toilet visits at night; and increasing heart rate, respiration rate, and motion in bed at night. When predefined changes in digital biomarkers occur, patients will be called in for clinical evaluation, and N-terminal pro b-type natriuretic peptide measurement (an increase of >30% considered as significant) will be performed. The sensitivity and specificity of the different biomarkers and their combinations for the detection of HF decompensation will be calculated. Results: The study is in the data collection phase. Study recruitment started in February 2024. Data analysis is scheduled to start after all data are collected. As of manuscript submission, 5 patients have been recruited. Results are expected to be published by the end of 2025. Conclusions: The results of this study will add to the current knowledge about opportunities for telemedicine to monitor older patients with HF living at home alone by evaluating the potential of ambient sensor systems for this purpose. Timely recognition of HF decompensation could enable proactive management, potentially reducing health care costs associated with preventable emergency presentations or hospitalizations. Trial Registration: ClinicalTrials.gov NCT06126848; https://clinicaltrials.gov/study/NCT06126848 International Registered Report Identifier (IRRID): PRR1-10.2196/55953 UR - https://www.researchprotocols.org/2024/1/e55953 UR - http://dx.doi.org/10.2196/55953 UR - http://www.ncbi.nlm.nih.gov/pubmed/38820577 ID - info:doi/10.2196/55953 ER - TY - JOUR AU - Seuren, Martinus Lucas AU - Shaw, Sara PY - 2024/5/31 TI - How Informal Carers Support Video Consulting in Physiotherapy, Heart Failure, and Cancer: Qualitative Study Using Linguistic Ethnography JO - J Med Internet Res SP - e51695 VL - 26 KW - delivery of health care KW - remote consultation KW - carer KW - telemedicine KW - videoconferencing KW - language KW - linguistics KW - gestures KW - physiotherapy KW - heart failure KW - care KW - patient care KW - feasibility KW - safety KW - communication KW - mobile phone N2 - Background: Informal carers play an important role in the everyday care of patients and the delivery of health care services. They aid patients in transportation to and from appointments, and they provide assistance during the appointments (eg, answering questions on the patient?s behalf). Video consultations are often seen as a way of providing patients with easier access to care. However, few studies have considered how this affects the role of informal carers and how they are needed to make video consultations safe and feasible. Objective: This study aims to identify how informal carers, usually friends or family who provide unpaid assistance, support patients and clinicians during video consultations. Methods: We conducted an in-depth analysis of the communication in a sample of video consultations drawn from 7 clinical settings across 4 National Health Service Trusts in the United Kingdom. The data set consisted of 52 video consultation recordings (of patients with diabetes, gestational diabetes, cancer, heart failure, orthopedic problems, long-term pain, and neuromuscular rehabilitation) and interviews with all participants involved in these consultations. Using Linguistic Ethnography, which embeds detailed analysis of verbal and nonverbal communication in the context of the interaction, we examined the interactional, technological, and clinical work carers did to facilitate video consultations and help patients and clinicians overcome challenges of the remote and video-mediated context. Results: Most patients (40/52, 77%) participated in the video consultation without support from an informal carer. Only 23% (12/52) of the consultations involved an informal carer. In addition to facilitating the clinical interaction (eg, answering questions on behalf of the patient), we identified 3 types of work that informal carers did: facilitating the use of technology; addressing problems when the patient could not hear or understand the clinician; and assisting with physical examinations, acting as the eyes, ears, and hands of the clinician. Carers often stayed in the background, monitoring the consultation to identify situations where they might be needed. In doing so, copresent carers reassured patients and helped them conduct the activities that make up a consultation. However, carers did not necessarily help patients solve all the challenges of a video consultation (eg, aiming the camera while laying hands on the patient during an examination). We compared cases where an informal carer was copresent with cases where the patient was alone, which showed that carers provided an important safety net, particularly for patients who were frail and experienced mobility difficulties. Conclusions: Informal carers play a critical role in making video consultations safe and feasible, particularly for patients with limited technological experience or complex needs. Guidance and research on video consulting need to consider the availability and work done by informal carers and how they can be supported in providing patients access to digital health care services. UR - https://www.jmir.org/2024/1/e51695 UR - http://dx.doi.org/10.2196/51695 UR - http://www.ncbi.nlm.nih.gov/pubmed/38819900 ID - info:doi/10.2196/51695 ER - TY - JOUR AU - Leitner, Jared AU - Chiang, Po-Han AU - Agnihotri, Parag AU - Dey, Sujit PY - 2024/5/28 TI - The Effect of an AI-Based, Autonomous, Digital Health Intervention Using Precise Lifestyle Guidance on Blood Pressure in Adults With Hypertension: Single-Arm Nonrandomized Trial JO - JMIR Cardio SP - e51916 VL - 8 KW - blood pressure KW - hypertension KW - digital health KW - lifestyle change KW - lifestyle medicine KW - wearables KW - remote patient monitoring KW - artificial intelligence KW - AI KW - mobile phone N2 - Background: Home blood pressure (BP) monitoring with lifestyle coaching is effective in managing hypertension and reducing cardiovascular risk. However, traditional manual lifestyle coaching models significantly limit availability due to high operating costs and personnel requirements. Furthermore, the lack of patient lifestyle monitoring and clinician time constraints can prevent personalized coaching on lifestyle modifications. Objective: This study assesses the effectiveness of a fully digital, autonomous, and artificial intelligence (AI)?based lifestyle coaching program on achieving BP control among adults with hypertension. Methods: Participants were enrolled in a single-arm nonrandomized trial in which they received a BP monitor and wearable activity tracker. Data were collected from these devices and a questionnaire mobile app, which were used to train personalized machine learning models that enabled precision lifestyle coaching delivered to participants via SMS text messaging and a mobile app. The primary outcomes included (1) the changes in systolic and diastolic BP from baseline to 12 and 24 weeks and (2) the percentage change of participants in the controlled, stage-1, and stage-2 hypertension categories from baseline to 12 and 24 weeks. Secondary outcomes included (1) the participant engagement rate as measured by data collection consistency and (2) the number of manual clinician outreaches. Results: In total, 141 participants were monitored over 24 weeks. At 12 weeks, systolic and diastolic BP decreased by 5.6 mm Hg (95% CI ?7.1 to ?4.2; P<.001) and 3.8 mm Hg (95% CI ?4.7 to ?2.8; P<.001), respectively. Particularly, for participants starting with stage-2 hypertension, systolic and diastolic BP decreased by 9.6 mm Hg (95% CI ?12.2 to ?6.9; P<.001) and 5.7 mm Hg (95% CI ?7.6 to ?3.9; P<.001), respectively. At 24 weeks, systolic and diastolic BP decreased by 8.1 mm Hg (95% CI ?10.1 to ?6.1; P<.001) and 5.1 mm Hg (95% CI ?6.2 to ?3.9; P<.001), respectively. For participants starting with stage-2 hypertension, systolic and diastolic BP decreased by 14.2 mm Hg (95% CI ?17.7 to ?10.7; P<.001) and 8.1 mm Hg (95% CI ?10.4 to ?5.7; P<.001), respectively, at 24 weeks. The percentage of participants with controlled BP increased by 17.2% (22/128; P<.001) and 26.5% (27/102; P<.001) from baseline to 12 and 24 weeks, respectively. The percentage of participants with stage-2 hypertension decreased by 25% (32/128; P<.001) and 26.5% (27/102; P<.001) from baseline to 12 and 24 weeks, respectively. The average weekly participant engagement rate was 92% (SD 3.9%), and only 5.9% (6/102) of the participants required manual outreach over 24 weeks. Conclusions: The study demonstrates the potential of fully digital, autonomous, and AI-based lifestyle coaching to achieve meaningful BP improvements and high engagement for patients with hypertension while substantially reducing clinician workloads. Trial Registration: ClinicalTrials.gov NCT06337734; https://clinicaltrials.gov/study/NCT06337734 UR - https://cardio.jmir.org/2024/1/e51916 UR - http://dx.doi.org/10.2196/51916 UR - http://www.ncbi.nlm.nih.gov/pubmed/38805253 ID - info:doi/10.2196/51916 ER - TY - JOUR AU - Dinh, Mackenzie AU - Lin, Chieh Chun AU - Whitfield, Candace AU - Farhan, Zahera AU - Meurer, J. William AU - Bailey, Sarah AU - Skolarus, E. Lesli PY - 2024/5/28 TI - Exploring the Acceptability and Feasibility of Remote Blood Pressure Measurements and Cognition Assessments Among Participants Recruited From a Safety-Net Emergency Department (Reach Out Cognition): Nonrandomized Mobile Health Trial JO - JMIR Form Res SP - e54010 VL - 8 KW - hypertension KW - cognition KW - mobile health KW - Bluetooth KW - remote KW - monitoring KW - monitor KW - low income KW - mHealth KW - hypertensive KW - cardiology KW - cardiovascular KW - feasibility KW - acceptability KW - satisfaction KW - RCT KW - randomized controlled trial KW - assessment KW - blood pressure KW - neurological N2 - Background: Hypertension is a prevalent cardiovascular risk factor disproportionately affecting Black Americans, who also experience a higher incidence of Alzheimer disease and Alzheimer disease?related dementias. Monitoring blood pressure (BP) and cognition may be important strategies in reducing these disparities. Objective: The objective of the Reach Out Cognition study was to explore the feasibility and acceptability of remote cognitive and BP assessments in a predominantly Black, low-income population. Methods: Reach Out was a randomized, controlled, mobile health?based clinical trial to reduce BP among patients with hypertension at an emergency department in a safety-net hospital (ie, a US hospital in which 25% of the patients are Medicaid recipients). Upon conclusion of Reach Out, participants were given the option of continuing into an extension phase, Reach Out Cognition, that included Bluetooth-enabled BP monitoring and digital cognitive assessments for 6 months. Digital cognitive assessments were text message?linked online surveys of the Self-Administered Gerocognitive Exam and Quality of Life in Neurological Disorders scale. BP assessments were measured with Bluetooth-enabled BP cuffs paired with an app and the data were manually sent to the research team. Outcomes were feasibility (ie, enrollment and 3- and 6-month completion of digital cognitive and BP assessments) and acceptability of assessments using a 4-item validated survey, ranging from 1 (not acceptable) to 5 (completely acceptable). Results: Of the 211 Reach Out participants, 107 (50.7%) consented and 71 (33.6%) completed enrollment in Reach Out Cognition. Participants had a mean age of 49.9 years; 70.4% were female and 57.8% identified as Black. Among the 71 participants, 51 (72%) completed cognitive assessments at 3 months and 34 (48%) completed these assessments at 6 months. BP assessments were completed by 37 (52%) and 20 (28%) of the 71 participants at 3 and 6 months, respectively. Participants were neutral on the acceptability of the digital cognitive assessments (mean 3.7) and Bluetooth self-measured BP (SMBP) monitoring (mean 3.9). Participants noted challenges syncing the BP cuff to the app, internet connection, and transmitting the data to the research team. Conclusions: Enrollment and assessment completion were low, while acceptability was moderate. Technological advances will eliminate some of the Bluetooth SMBP barriers and offer new strategies for cognitive assessments. Subsequent studies could benefit from offering more comprehensive support to overcome Bluetooth-related hurdles, such as personalized training materials, video conferencing, or in-person research team support. Alternatively, strategies that do not require pairing with an app and passive transmission of data could be considered. Overall, further research is warranted to optimize participant engagement and overcome technological challenges. Trial Registration: ClinicalTrials.gov NCT03422718; https://clinicaltrials.gov/study/NCT03422718 UR - https://formative.jmir.org/2024/1/e54010 UR - http://dx.doi.org/10.2196/54010 UR - http://www.ncbi.nlm.nih.gov/pubmed/38805251 ID - info:doi/10.2196/54010 ER - TY - JOUR AU - Mittal, Ajay AU - Elkaldi, Yasmine AU - Shih, Susana AU - Nathu, Riken AU - Segal, Mark PY - 2024/5/27 TI - Mobile Electrocardiograms in the Detection of Subclinical Atrial Fibrillation in High-Risk Outpatient Populations: Protocol for an Observational Study JO - JMIR Res Protoc SP - e52647 VL - 13 KW - mobile ECG KW - digital health KW - cardiology KW - ECG KW - electrocardiogram KW - atrial fibrillation KW - outpatient KW - randomized KW - controlled trial KW - controlled trials KW - smartphone KW - mobile health KW - app KW - apps KW - feasibility KW - effectiveness KW - KardiaMobile single-lead ECGs KW - mobile phone N2 - Background: Single-lead, smartphone-based mobile electrocardiograms (ECGs) have the potential to provide a noninvasive, rapid, and cost-effective means of screening for atrial fibrillation (AFib) in outpatient settings. AFib has been associated with various comorbid diseases that prompt further investigation and screening methodologies for at-risk populations. A simple 30-second sinus rhythm strip from the KardiaMobile ECG (AliveCor) can provide an effective screen for cardiac rhythm abnormalities. Objective: The aim of this study is to demonstrate the feasibility of performing Kardia-enabled ECG recordings routinely in outpatient settings in high-risk populations and its potential use in uncovering previous undiagnosed cases of AFib. Specific aim 1 is to determine the feasibility and accuracy of performing routine cardiac rhythm sampling in patients deemed at high risk for AFib. Specific aim 2 is to determine whether routine rhythm sampling in outpatient clinics with high-risk patients can be used cost-effectively in an outpatient clinic without increasing the time it takes for the patient to be seen by a physician. Methods: Participants were recruited across 6 clinic sites across the University of Florida Health Network: University of Florida Health Nephrology, Sleep Center, Ophthalmology, Urology, Neurology, and Pre-Surgical. Participants, aged 18-99 years, who agreed to partake in the study were given a consent form and completed a questionnaire regarding their past medical history and risk factors for cardiovascular disease. Single-lead, 30-second ECGs were taken by the KardiaMobile ECG device. If patients are found to have newly diagnosed AFib, the attending physician is notified, and a 12-lead ECG or standard ECG equivalent will be ordered. Results: As of March 1, 2024, a total of 2339 participants have been enrolled. Of the data collected thus far, the KardiaMobile rhythm strip reported 381 abnormal readings, which are pending analysis from a cardiologist. A total of 78 readings were labeled as possible AFib, 159 readings were labeled unclassified, and 49 were unreadable. Of note, the average age of participants was 61 (SD 10.25) years, and the average self-reported weight was 194 (SD 14.26) pounds. Additionally, 1572 (67.25%) participants report not regularly seeing a cardiologist. Regarding feasibility, the average length of enrolling a patient into the study was 3:30 (SD 0.5) minutes after informed consent was completed, and medical staff across clinic sites (n=25) reported 9 of 10 level of satisfaction with the impact of the screening on clinic flow. Conclusions: Preliminary data show promise regarding the feasibility of using KardiaMobile ECGs for the screening of AFib and prevention of cardiological disease in vulnerable outpatient populations. The use of a single-lead mobile ECG strip can serve as a low-cost, effective AFib screen for implementation across free clinics attempting to provide increased health care accessibility. International Registered Report Identifier (IRRID): DERR1-10.2196/52647 UR - https://www.researchprotocols.org/2024/1/e52647 UR - http://dx.doi.org/10.2196/52647 UR - http://www.ncbi.nlm.nih.gov/pubmed/38801762 ID - info:doi/10.2196/52647 ER - TY - JOUR AU - Adamu, Gati Umar AU - Badianyama, Marheb AU - Mpanya, Dineo AU - Maseko, Muzi AU - Tsabedze, Nqoba PY - 2024/5/23 TI - The Use of Metabolomes in Risk Stratification of Heart Failure Patients: Protocol for a Scoping Review JO - JMIR Res Protoc SP - e53905 VL - 13 KW - metabolomes KW - metabolomics KW - heart failure KW - risk stratification KW - morbidity KW - mortality KW - metabolic abnormality KW - scoping review protocol KW - electronic database N2 - Background: Heart failure (HF) is a significant health problem that is often associated with major morbidity and mortality. Metabolic abnormalities occur in HF and may be used to identify individuals at risk of developing the condition. Furthermore, these metabolic changes may play a role in the pathogenesis and progression of HF. Despite this knowledge, the utility of metabolic changes in diagnosis, management, prognosis, and therapy for patients with chronic HF has not been systematically reviewed. Objective: This scoping review aims to systematically appraise the literature on metabolic changes in patients with HF, describe the role of these changes in pathogenesis, progression, and care, and identify knowledge gaps to inform future research. Methods: This review will be conducted using a strategy based on previous reports, the JBI Manual for Evidence Synthesis, and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. A comprehensive search of electronic databases (Medline, EBSCOhost, Scopus, and Web of Science) will be conducted using keywords related to HF, myocardial failure, metabolomes, metabonomics, and analytical chemistry techniques. The search will include original peer-reviewed research papers (clinical studies conducted on humans and systematic reviews with or without a meta-analysis) published between January 2010 and September 2023. Studies that include patients with HF younger than 18 years or those not published in English will be excluded. Two authors (UGA and MB) will screen the titles and abstracts independently and perform a full-text screen of the relevant and eligible papers. Relevant data will be extracted and synthesized, and a third author or group will be consulted to resolve discrepancies. Results: This scoping review will span from January 2010 to September 2023, and the results will be published in a peer-reviewed, open-access journal as a scoping review in 2024. The presentation of the findings will use the PRISMA-ScR flow diagram and descriptive and narrative formats, including tables and graphical displays, to provide a comprehensive overview of the extracted data. Conclusions: This review aims to collect and analyze the available evidence on metabolic changes in patients with HF, aiming to enhance our current understanding of this topic. Additionally, this review will identify the most commonly used and suitable sample, analytical method, and specific metabolomes to facilitate standardization, reproducibility of results, and application in the diagnosis, treatment, and risk stratification of patients with HF. Finally, it is hoped that this review?s outcomes will inspire further research into the metabolomes of patients with HF in low- and middle-income countries. Trial Registration: Open Science Framework; https://osf.io/sp6xj International Registered Report Identifier (IRRID): DERR1-10.2196/53905 UR - https://www.researchprotocols.org/2024/1/e53905 UR - http://dx.doi.org/10.2196/53905 UR - http://www.ncbi.nlm.nih.gov/pubmed/38781584 ID - info:doi/10.2196/53905 ER - TY - JOUR AU - Xu, Huan Richard AU - Sun, Ruiqi AU - Fu, Siu-Ngor PY - 2024/5/21 TI - Out-of-Hospital Cardiac Arrest Before and During the COVID-19 Pandemic in Hong Kong: Registry-Based Study From 2017 to 2023 JO - JMIR Public Health Surveill SP - e56054 VL - 10 KW - out-of-hospital cardiac arrest KW - OHCA KW - COVID-19 KW - pandemic KW - survival KW - Chinese KW - Asian N2 - Background: The COVID-19 pandemic has exerted a significant toll on individual health and the efficacy of health care systems. However, the influence of COVID-19 on the frequency and outcomes of out-of-hospital cardiac arrest (OHCA) within the Chinese population, both before and throughout the entire pandemic period, remains to be clarified. Objective: This study aimed to fill the gaps by investigating the prevalence and outcomes of OHCA in Hong Kong (HK) both before and during the whole pandemic period. Methods: This is a retrospective regional registry study. The researchers matched OHCA data with COVID-19?confirmed case records between December 2017 and May 2023. The data included information on response times, location of OHCA, witness presence, initial rhythm, bystander cardiopulmonary resuscitation (CPR), use of public-access defibrillation, resuscitation in the accident and emergency department, and survival to admission. Descriptive analyses were conducted, and statistical tests such as analysis of variance and ?2 were used to examine differences between variables. The incidence of OHCA and survival rates were calculated, and logistic regression analysis was performed to assess associations. The prevalence of OHCA and COVID-19 during the peak of the pandemic was also described. Results: A total of 43,882 cases of OHCA were reported in HK and included in our analysis. Around 13,946 cases were recorded during the prepandemic period (2017-2019), and the remaining 29,936 cases were reported during the pandemic period (2020-2023). During the pandemic period, the proportion of female patients increased to 44.1% (13,215/29,936), and the average age increased slightly to 76.5 (SD 18.5) years. The majority of OHCAs (n=18,143, 61.1% cases) occurred at home. A witness was present in 45.9% (n=10,723) of the cases, and bystander CPR was initiated in 44.6% (n=13,318) of the cases. There was a significant increase in OHCA incidence, with a corresponding decrease in survival rates compared to the prepandemic period. The location of OHCA shifted, with a decrease in incidents in public places and a potential increase in incidents at home. We found that CPR (odds ratio 1.48, 95% CI 1.17-1.86) and public-access defibrillation (odds ratio 1.16, 95% CI 1.05-1.28) were significantly associated with a high survival to admission rate during the pandemic period. There was a correlation between the development of OHCA and the prevalence of COVID-19 in HK. Conclusions: The COVID-19 pandemic has had a significant impact on OHCA in HK, resulting in increased incidence and decreased survival rates. The findings highlight the importance of addressing the indirect effects of the pandemic, such as increased stress levels and strain on health care systems, on OHCA outcomes. Strategies should be developed to improve OHCA prevention, emergency response systems, and health care services during public health emergencies to mitigate the impact on population health. UR - https://publichealth.jmir.org/2024/1/e56054 UR - http://dx.doi.org/10.2196/56054 UR - http://www.ncbi.nlm.nih.gov/pubmed/38771620 ID - info:doi/10.2196/56054 ER - TY - JOUR AU - Xie, Puguang AU - Wang, Hao AU - Xiao, Jun AU - Xu, Fan AU - Liu, Jingyang AU - Chen, Zihang AU - Zhao, Weijie AU - Hou, Siyu AU - Wu, Dongdong AU - Ma, Yu AU - Xiao, Jingjing PY - 2024/5/10 TI - Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study JO - J Med Internet Res SP - e49848 VL - 26 KW - acute myocardial infarction KW - mortality KW - deep learning KW - explainable model KW - prediction N2 - Background: Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. Objective: This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. Methods: In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. Results: A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. Conclusions: The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI. UR - https://www.jmir.org/2024/1/e49848 UR - http://dx.doi.org/10.2196/49848 UR - http://www.ncbi.nlm.nih.gov/pubmed/38728685 ID - info:doi/10.2196/49848 ER - TY - JOUR AU - Liliequist, E. Björn AU - Särnholm, Josefin AU - Skúladóttir, Helga AU - Ólafsdóttir, Eva AU - Ljótsson, Brjánn AU - Braunschweig, Frieder PY - 2024/5/7 TI - Cognitive Behavioral Therapy for Symptom Preoccupation Among Patients With Premature Ventricular Contractions: Nonrandomized Pretest-Posttest Study JO - JMIR Cardio SP - e53815 VL - 8 KW - premature ventricular contractions KW - quality of life KW - symptom preoccupation KW - cognitive behavioral therapy: CBT N2 - Background: Premature ventricular contractions (PVCs) are a common cardiac condition often associated with disabling symptoms and impaired quality of life (QoL). Current treatment strategies have limited effectiveness in reducing symptoms and restoring QoL for patients with PVCs. Symptom preoccupation, involving cardiac-related fear, hypervigilance, and avoidance behavior, is associated with disability in other cardiac conditions and can be effectively targeted by cognitive behavioral therapy (CBT). Objective: The aim of this study was to evaluate the effect of a PVC-specific CBT protocol targeting symptom preoccupation in patients with symptomatic idiopathic PVCs. Methods: Nineteen patients diagnosed with symptomatic idiopathic PVCs and symptom preoccupation underwent PVC-specific CBT over 10 weeks. The treatment was delivered by a licensed psychologist via videoconference in conjunction with online text-based information and homework assignments. The main components of the treatment were exposure to cardiac-related symptoms and reducing cardiac-related avoidance and control behavior. Self-rated measures were collected at baseline, post treatment, and at 3- and 6-month follow-ups. The primary outcome was PVC-specific QoL at posttreatment assessment measured with a PVC-adapted version of the Atrial Fibrillation Effects on Quality of Life questionnaire. Secondary measures included symptom preoccupation measured with the Cardiac Anxiety Questionnaire. PVC burden was evaluated with 5-day continuous electrocardiogram recordings at baseline, post treatment, and 6-month follow-up. Results: We observed large improvements in PVC-specific QoL (Cohen d=1.62, P<.001) and symptom preoccupation (Cohen d=1.73, P<.001) post treatment. These results were sustained at the 3- and 6-month follow-ups. PVC burden, as measured with 5-day continuous electrocardiogram, remained unchanged throughout follow-up. However, self-reported PVC symptoms were significantly lower at posttreatment assessment and at both the 3- and 6-month follow-ups. Reduction in symptom preoccupation had a statistically significant mediating effect of the intervention on PVC-specific QoL in an explorative mediation analysis. Conclusions: This uncontrolled pilot study shows preliminary promising results for PVC-specific CBT as a potentially effective treatment approach for patients with symptomatic idiopathic PVCs and symptom preoccupation. The substantial improvements in PVC-specific QoL and symptom preoccupation, along with the decreased self-reported PVC-related symptoms warrant further investigation in a larger randomized controlled trial. Trial Registration: ClinicalTrials.gov NCT05087238; https://clinicaltrials.gov/study/NCT05087238 UR - https://cardio.jmir.org/2024/1/e53815 UR - http://dx.doi.org/10.2196/53815 UR - http://www.ncbi.nlm.nih.gov/pubmed/38713500 ID - info:doi/10.2196/53815 ER - TY - JOUR AU - Ruksakulpiwat, Suebsarn AU - Phianhasin, Lalipat AU - Benjasirisan, Chitchanok AU - Ding, Kedong AU - Ajibade, Anuoluwapo AU - Kumar, Ayanesh AU - Stewart, Cassie PY - 2024/5/6 TI - Assessing the Efficacy of ChatGPT Versus Human Researchers in Identifying Relevant Studies on mHealth Interventions for Improving Medication Adherence in Patients With Ischemic Stroke When Conducting Systematic Reviews: Comparative Analysis JO - JMIR Mhealth Uhealth SP - e51526 VL - 12 KW - ChatGPT KW - systematic reviews KW - medication adherence KW - mobile health KW - mHealth KW - ischemic stroke KW - mobile phone N2 - Background: ChatGPT by OpenAI emerged as a potential tool for researchers, aiding in various aspects of research. One such application was the identification of relevant studies in systematic reviews. However, a comprehensive comparison of the efficacy of relevant study identification between human researchers and ChatGPT has not been conducted. Objective: This study aims to compare the efficacy of ChatGPT and human researchers in identifying relevant studies on medication adherence improvement using mobile health interventions in patients with ischemic stroke during systematic reviews. Methods: This study used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Four electronic databases, including CINAHL Plus with Full Text, Web of Science, PubMed, and MEDLINE, were searched to identify articles published from inception until 2023 using search terms based on MeSH (Medical Subject Headings) terms generated by human researchers versus ChatGPT. The authors independently screened the titles, abstracts, and full text of the studies identified through separate searches conducted by human researchers and ChatGPT. The comparison encompassed several aspects, including the ability to retrieve relevant studies, accuracy, efficiency, limitations, and challenges associated with each method. Results: A total of 6 articles identified through search terms generated by human researchers were included in the final analysis, of which 4 (67%) reported improvements in medication adherence after the intervention. However, 33% (2/6) of the included studies did not clearly state whether medication adherence improved after the intervention. A total of 10 studies were included based on search terms generated by ChatGPT, of which 6 (60%) overlapped with studies identified by human researchers. Regarding the impact of mobile health interventions on medication adherence, most included studies (8/10, 80%) based on search terms generated by ChatGPT reported improvements in medication adherence after the intervention. However, 20% (2/10) of the studies did not clearly state whether medication adherence improved after the intervention. The precision in accurately identifying relevant studies was higher in human researchers (0.86) than in ChatGPT (0.77). This is consistent with the percentage of relevance, where human researchers (9.8%) demonstrated a higher percentage of relevance than ChatGPT (3%). However, when considering the time required for both humans and ChatGPT to identify relevant studies, ChatGPT substantially outperformed human researchers as it took less time to identify relevant studies. Conclusions: Our comparative analysis highlighted the strengths and limitations of both approaches. Ultimately, the choice between human researchers and ChatGPT depends on the specific requirements and objectives of each review, but the collaborative synergy of both approaches holds the potential to advance evidence-based research and decision-making in the health care field. UR - https://mhealth.jmir.org/2024/1/e51526 UR - http://dx.doi.org/10.2196/51526 UR - http://www.ncbi.nlm.nih.gov/pubmed/38710069 ID - info:doi/10.2196/51526 ER - TY - JOUR AU - Gao, Zhenyue AU - Liu, Xiaoli AU - Kang, Yu AU - Hu, Pan AU - Zhang, Xiu AU - Yan, Wei AU - Yan, Muyang AU - Yu, Pengming AU - Zhang, Qing AU - Xiao, Wendong AU - Zhang, Zhengbo PY - 2024/5/2 TI - Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep Learning Model JO - J Med Internet Res SP - e54363 VL - 26 KW - heart failure KW - multimodal deep learning KW - mortality prediction KW - admission notes KW - clinical tabular data KW - tabular KW - notes KW - deep learning KW - machine learning KW - cardiology KW - heart KW - cardiac KW - documentation KW - prognostic KW - prognosis KW - prognoses KW - predict KW - prediction KW - predictions KW - predictive N2 - Background: Clinical notes contain contextualized information beyond structured data related to patients? past and current health status. Objective: This study aimed to design a multimodal deep learning approach to improve the evaluation precision of hospital outcomes for heart failure (HF) using admission clinical notes and easily collected tabular data. Methods: Data for the development and validation of the multimodal model were retrospectively derived from 3 open-access US databases, including the Medical Information Mart for Intensive Care III v1.4 (MIMIC-III) and MIMIC-IV v1.0, collected from a teaching hospital from 2001 to 2019, and the eICU Collaborative Research Database v1.2, collected from 208 hospitals from 2014 to 2015. The study cohorts consisted of all patients with critical HF. The clinical notes, including chief complaint, history of present illness, physical examination, medical history, and admission medication, as well as clinical variables recorded in electronic health records, were analyzed. We developed a deep learning mortality prediction model for in-hospital patients, which underwent complete internal, prospective, and external evaluation. The Integrated Gradients and SHapley Additive exPlanations (SHAP) methods were used to analyze the importance of risk factors. Results: The study included 9989 (16.4%) patients in the development set, 2497 (14.1%) patients in the internal validation set, 1896 (18.3%) in the prospective validation set, and 7432 (15%) patients in the external validation set. The area under the receiver operating characteristic curve of the models was 0.838 (95% CI 0.827-0.851), 0.849 (95% CI 0.841-0.856), and 0.767 (95% CI 0.762-0.772), for the internal, prospective, and external validation sets, respectively. The area under the receiver operating characteristic curve of the multimodal model outperformed that of the unimodal models in all test sets, and tabular data contributed to higher discrimination. The medical history and physical examination were more useful than other factors in early assessments. Conclusions: The multimodal deep learning model for combining admission notes and clinical tabular data showed promising efficacy as a potentially novel method in evaluating the risk of mortality in patients with HF, providing more accurate and timely decision support. UR - https://www.jmir.org/2024/1/e54363 UR - http://dx.doi.org/10.2196/54363 UR - http://www.ncbi.nlm.nih.gov/pubmed/38696251 ID - info:doi/10.2196/54363 ER - TY - JOUR AU - Yoon, Minjae AU - Lee, Seonhwa AU - Choi, Yeon Jah AU - Jung, Mi-Hyang AU - Youn, Jong-Chan AU - Shim, Young Chi AU - Choi, Jin-Oh AU - Kim, Ju Eung AU - Kim, Hyungseop AU - Yoo, Byung-Su AU - Son, Joo Yeon AU - Choi, Dong-Ju PY - 2024/4/29 TI - Effectiveness of a Smartphone App?Based Intervention With Bluetooth-Connected Monitoring Devices and a Feedback System in Heart Failure (SMART-HF Trial): Randomized Controlled Trial JO - J Med Internet Res SP - e52075 VL - 26 KW - heart failure KW - mobile applications KW - mobile health KW - self-care KW - vital sign monitoring KW - mobile phone N2 - Background: Current heart failure (HF) guidelines recommend a multidisciplinary approach, discharge education, and self-management for HF. However, the recommendations are challenging to implement in real-world clinical settings. Objective: We developed a mobile health (mHealth) platform for HF self-care to evaluate whether a smartphone app?based intervention with Bluetooth-connected monitoring devices and a feedback system can help improve HF symptoms. Methods: In this prospective, randomized, multicenter study, we enrolled patients 20 years of age and older, hospitalized for acute HF, and who could use a smartphone from 7 tertiary hospitals in South Korea. In the intervention group (n=39), the apps were automatically paired with Bluetooth-connected monitoring devices. The patients could enter information on vital signs, HF symptoms, diet, medications, and exercise regimen into the app daily and receive feedback or alerts on their input. In the control group (n=38), patients could only enter their blood pressure, heart rate, and weight using conventional, non-Bluetooth devices and could not receive any feedback or alerts from the app. The primary end point was the change in dyspnea symptom scores from baseline to 4 weeks, assessed using a questionnaire. Results: At 4 weeks, the change in dyspnea symptom score from baseline was significantly greater in the intervention group than in the control group (mean ?1.3, SD 2.1 vs mean ?0.3, SD 2.3; P=.048). A significant reduction was found in body water composition from baseline to the final measurement in the intervention group (baseline level mean 7.4, SD 2.5 vs final level mean 6.6, SD 2.5; P=.003). App adherence, which was assessed based on log-in or the percentage of days when symptoms were first observed, was higher in the intervention group than in the control group. Composite end points, including death, rehospitalization, and urgent HF visits, were not significantly different between the 2 groups. Conclusions: The mobile-based health platform with Bluetooth-connected monitoring devices and a feedback system demonstrated improvement in dyspnea symptoms in patients with HF. This study provides evidence and rationale for implementing mobile app?based self-care strategies and feedback for patients with HF. Trial Registration: ClinicalTrials.gov NCT05668000; https://clinicaltrials.gov/study/NCT05668000 UR - https://www.jmir.org/2024/1/e52075 UR - http://dx.doi.org/10.2196/52075 UR - http://www.ncbi.nlm.nih.gov/pubmed/38683665 ID - info:doi/10.2196/52075 ER - TY - JOUR AU - Cardoso Pinto, M. Alexandra AU - Soussi, Daniella AU - Qasim, Subaan AU - Dunin-Borkowska, Aleksandra AU - Rupasinghe, Thiara AU - Ubhi, Nicholas AU - Ranasinghe, Lasith PY - 2024/4/23 TI - The Use of Animations Depicting Cardiac Electrical Activity to Improve Confidence in Understanding of Cardiac Pathology and Electrocardiography Traces Among Final-Year Medical Students: Nonrandomized Controlled Trial JO - JMIR Med Educ SP - e46507 VL - 10 KW - medical education KW - cardiology KW - technology KW - clinical skills KW - cardiac KW - cardiac electrical activity KW - ECG KW - mixed methods study KW - students KW - education KW - medical professionals KW - development KW - web-based tutorial KW - teaching KW - cardiovascular KW - learning KW - electrocardiography N2 - Background: Electrocardiography (ECG) interpretation is a fundamental skill for medical students and practicing medical professionals. Recognizing ECG pathologies promptly allows for quick intervention, especially in acute settings where urgent care is needed. However, many medical students find ECG interpretation and understanding of the underlying pathology challenging, with teaching methods varying greatly. Objective: This study involved the development of novel animations demonstrating the passage of electrical activity for well-described cardiac pathologies and showcased them alongside the corresponding live ECG traces during a web-based tutorial for final-year medical students. We aimed to assess whether the animations improved medical students? confidence in visualizing cardiac electrical activity and ECG interpretation, compared to standard ECG teaching methods. Methods: Final-year medical students at Imperial College London attended a web-based tutorial demonstrating the 7 animations depicting cardiac electrical activity and the corresponding ECG trace. Another tutorial without the animations was held to act as a control. Students completed a questionnaire assessing their confidence in interpreting ECGs and visualizing cardiovascular electrical transmission before and after the tutorial. Intervention-arm participants were also invited to a web-based focus group to explore their experiences of past ECG teaching and the tutorial, particularly on aspects they found helpful and what could be further improved in the tutorial and animations. Wilcoxon signed-rank tests and Mann-Whitney U tests were used to assess the statistical significance of any changes in confidence. Focus group transcripts were analyzed using inductive thematic analysis. Results: Overall, 19 students attended the intervention arm, with 15 (79%) completing both the pre- and posttutorial questionnaires and 15 (79%) participating in focus groups, whereas 14 students attended the control arm, with 13 (93%) completing both questionnaires. Median confidence in interpreting ECGs in the intervention arm increased after the tutorial (2, IQR 1.5-3.0 vs 3, IQR 3-4.5; P<.001). Improvement was seen in both confidence in reviewing or diagnosing cardiac rhythms and the visualization of cardiac electrical activity. However, there was no significant difference between the intervention and control arms, for all pathologies (all P>.05). The main themes from the thematic analysis were that ECGs are a complex topic and past ECG teaching has focused on memorizing traces; the visualizations enabled deeper understanding of cardiac pathology; and ECG learning requires repetition, and clinical links remain essential. Conclusions: This study highlights the value of providing concise explanations of the meaning and pathophysiology behind ECG traces, both visually and verbally. ECG teaching that incorporates relevant pathophysiology, alongside vignettes with discussions regarding investigations and management options, is likely more helpful to students than practices based solely on pattern recognition. Although the animations supported student learning, the key element was the tutor?s explanations. These animations may be more helpful as a supplement to teaching, for instance, as open-access videos. UR - https://mededu.jmir.org/2024/1/e46507 UR - http://dx.doi.org/10.2196/46507 ID - info:doi/10.2196/46507 ER - TY - JOUR AU - Shara, Nawar AU - Mirabal-Beltran, Roxanne AU - Talmadge, Bethany AU - Falah, Noor AU - Ahmad, Maryam AU - Dempers, Ramon AU - Crovatt, Samantha AU - Eisenberg, Steven AU - Anderson, Kelley PY - 2024/4/22 TI - Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data JO - JMIR Cardio SP - e53091 VL - 8 KW - machine learning KW - preeclampsia KW - cardiovascular KW - maternal KW - obstetrics KW - health disparities KW - woman KW - women KW - pregnancy KW - pregnant KW - cardiovascular condition KW - retrospective study KW - electronic health record KW - EHR KW - technology KW - decision-making KW - health disparity KW - virtual server KW - thromboembolism KW - kidney failure KW - HOPE-CAT N2 - Background: Cardiovascular conditions (eg, cardiac and coronary conditions, hypertensive disorders of pregnancy, and cardiomyopathies) were the leading cause of maternal mortality between 2017 and 2019. The United States has the highest maternal mortality rate of any high-income nation, disproportionately impacting those who identify as non-Hispanic Black or Hispanic. Novel clinical approaches to the detection and diagnosis of cardiovascular conditions are therefore imperative. Emerging research is demonstrating that machine learning (ML) is a promising tool for detecting patients at increased risk for hypertensive disorders during pregnancy. However, additional studies are required to determine how integrating ML and big data, such as electronic health records (EHRs), can improve the identification of obstetric patients at higher risk of cardiovascular conditions. Objective: This study aimed to evaluate the capability and timing of a proprietary ML algorithm, Healthy Outcomes for all Pregnancy Experiences-Cardiovascular-Risk Assessment Technology (HOPE-CAT), to detect maternal-related cardiovascular conditions and outcomes. Methods: Retrospective data from the EHRs of a large health care system were investigated by HOPE-CAT in a virtual server environment. Deidentification of EHR data and standardization enabled HOPE-CAT to analyze data without pre-existing biases. The ML algorithm assessed risk factors selected by clinical experts in cardio-obstetrics, and the algorithm was iteratively trained using relevant literature and current standards of risk identification. After refinement of the algorithm?s learned risk factors, risk profiles were generated for every patient including a designation of standard versus high risk. The profiles were individually paired with clinical outcomes pertaining to cardiovascular pregnancy conditions and complications, wherein a delta was calculated between the date of the risk profile and the actual diagnosis or intervention in the EHR. Results: In total, 604 pregnancies resulting in birth had records or diagnoses that could be compared against the risk profile; the majority of patients identified as Black (n=482, 79.8%) and aged between 21 and 34 years (n=509, 84.4%). Preeclampsia (n=547, 90.6%) was the most common condition, followed by thromboembolism (n=16, 2.7%) and acute kidney disease or failure (n=13, 2.2%). The average delta was 56.8 (SD 69.7) days between the identification of risk factors by HOPE-CAT and the first date of diagnosis or intervention of a related condition reported in the EHR. HOPE-CAT showed the strongest performance in early risk detection of myocardial infarction at a delta of 65.7 (SD 81.4) days. Conclusions: This study provides additional evidence to support ML in obstetrical patients to enhance the early detection of cardiovascular conditions during pregnancy. ML can synthesize multiday patient presentations to enhance provider decision-making and potentially reduce maternal health disparities. UR - https://cardio.jmir.org/2024/1/e53091 UR - http://dx.doi.org/10.2196/53091 UR - http://www.ncbi.nlm.nih.gov/pubmed/38648629 ID - info:doi/10.2196/53091 ER - TY - JOUR AU - Pham, Cecilia AU - Govender, Romi AU - Tehami, Salik AU - Chavez, Summer AU - Adepoju, E. Omolola AU - Liaw, Winston PY - 2024/4/22 TI - ChatGPT?s Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study JO - J Med Internet Res SP - e55037 VL - 26 KW - ChatGPT KW - artificial intelligence KW - AI KW - large language model KW - LLM KW - cardiac arrest KW - bradycardia KW - simulation KW - advanced cardiovascular life support KW - ACLS KW - bradycardia simulations KW - America KW - American KW - heart association KW - cardiac KW - life support KW - exploratory study KW - heart KW - heart attack KW - clinical decision support KW - diagnostics KW - algorithms N2 - Background: ChatGPT is the most advanced large language model to date, with prior iterations having passed medical licensing examinations, providing clinical decision support, and improved diagnostics. Although limited, past studies of ChatGPT?s performance found that artificial intelligence could pass the American Heart Association?s advanced cardiovascular life support (ACLS) examinations with modifications. ChatGPT?s accuracy has not been studied in more complex clinical scenarios. As heart disease and cardiac arrest remain leading causes of morbidity and mortality in the United States, finding technologies that help increase adherence to ACLS algorithms, which improves survival outcomes, is critical. Objective: This study aims to examine the accuracy of ChatGPT in following ACLS guidelines for bradycardia and cardiac arrest. Methods: We evaluated the accuracy of ChatGPT?s responses to 2 simulations based on the 2020 American Heart Association ACLS guidelines with 3 primary outcomes of interest: the mean individual step accuracy, the accuracy score per simulation attempt, and the accuracy score for each algorithm. For each simulation step, ChatGPT was scored for correctness (1 point) or incorrectness (0 points). Each simulation was conducted 20 times. Results: ChatGPT?s median accuracy for each step was 85% (IQR 40%-100%) for cardiac arrest and 30% (IQR 13%-81%) for bradycardia. ChatGPT?s median accuracy over 20 simulation attempts for cardiac arrest was 69% (IQR 67%-74%) and for bradycardia was 42% (IQR 33%-50%). We found that ChatGPT?s outputs varied despite consistent input, the same actions were persistently missed, repetitive overemphasis hindered guidance, and erroneous medication information was presented. Conclusions: This study highlights the need for consistent and reliable guidance to prevent potential medical errors and optimize the application of ChatGPT to enhance its reliability and effectiveness in clinical practice. UR - https://www.jmir.org/2024/1/e55037 UR - http://dx.doi.org/10.2196/55037 UR - http://www.ncbi.nlm.nih.gov/pubmed/38648098 ID - info:doi/10.2196/55037 ER - TY - JOUR AU - Mishra, Vishala AU - Sarraju, Ashish AU - Kalwani, M. Neil AU - Dexter, P. Joseph PY - 2024/4/22 TI - Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study JO - J Med Internet Res SP - e55388 VL - 26 KW - artificial intelligence KW - ChatGPT KW - GPT KW - digital health KW - large language model KW - NLP KW - language model KW - language models KW - prompt engineering KW - health communication KW - generative KW - health literacy KW - natural language processing KW - patient-physician communication KW - prevention KW - cardiology KW - cardiovascular KW - heart KW - education KW - educational KW - human-in-the-loop KW - machine learning UR - https://www.jmir.org/2024/1/e55388 UR - http://dx.doi.org/10.2196/55388 UR - http://www.ncbi.nlm.nih.gov/pubmed/38648104 ID - info:doi/10.2196/55388 ER - TY - JOUR AU - Raes, Sarah AU - Prezzi, Andrea AU - Willems, Rik AU - Heidbuchel, Hein AU - Annemans, Lieven PY - 2024/4/19 TI - Investigating the Cost-Effectiveness of Telemonitoring Patients With Cardiac Implantable Electronic Devices: Systematic Review JO - J Med Internet Res SP - e47616 VL - 26 KW - systematic review KW - cost-effectiveness KW - telemonitoring KW - cardiac device KW - implantable cardioverter-defibrillator KW - ICD KW - pacemaker KW - monitoring KW - patient management KW - effectiveness KW - cost KW - quality of life KW - cardiac implantable electronic device KW - cardiac N2 - Background: Telemonitoring patients with cardiac implantable electronic devices (CIEDs) can improve their care management. However, the results of cost-effectiveness studies are heterogeneous. Therefore, it is still a matter of debate whether telemonitoring is worth the investment. Objective: This systematic review aims to investigate the cost-effectiveness of telemonitoring patients with CIEDs, focusing on its key drivers, and the impact of the varying perspectives. Methods: A systematic review was performed in PubMed, Web of Science, Embase, and EconLit. The search was completed on July 7, 2022. Studies were included if they fulfilled the following criteria: patients had a CIED, comparison with standard care, and inclusion of health economic evaluations (eg, cost-effectiveness analyses and cost-utility analyses). Only complete and peer-reviewed studies were included, and no year limits were applied. The exclusion criteria included studies with partial economic evaluations, systematic reviews or reports, and studies without standard care as a control group. Besides general study characteristics, the following outcome measures were extracted: impact on total cost or income, cost or income drivers, cost or income drivers per patient, cost or income drivers as a percentage of the total cost impact, incremental cost-effectiveness ratios, or cost-utility ratios. Quality was assessed using the Consensus Health Economic Criteria checklist. Results: Overall, 15 cost-effectiveness analyses were included. All studies were performed in Western countries, mainly Europe, and had primarily a male participant population. Of the 15 studies, 3 (20%) calculated the incremental cost-effectiveness ratio, 1 (7%) the cost-utility ratio, and 11 (73%) the health and cost impact of telemonitoring. In total, 73% (11/15) of the studies indicated that telemonitoring of patients with implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy ICDs was cost-effective and cost-saving, both from a health care and patient perspective. Cost-effectiveness results for telemonitoring of patients with pacemakers were inconclusive. The key drivers for cost reduction from a health care perspective were hospitalizations and scheduled in-office visits. Hospitalization costs were reduced by up to US $912 per patient per year. Scheduled in-office visits included up to 61% of the total cost reduction. Key drivers for cost reduction from a patient perspective were loss of income, cost for scheduled in-office visits and transport. Finally, of the 15 studies, 8 (52%) reported improved quality of life, with statistically significance in only 1 (13%) study (P=.03). Conclusions: From a health care and patient perspective, telemonitoring of patients with an ICD or a cardiac resynchronization therapy ICD is a cost-effective and cost-saving alternative to standard care. Inconclusive results were found for patients with pacemakers. However, telemonitoring can lead to a decrease in providers? income, mainly due to a lack of reimbursement. Introducing appropriate reimbursement could make telemonitoring sustainable for providers while still being cost-effective from a health care payer perspective. Trial Registration: PROSPERO CRD42022322334; https://tinyurl.com/puunapdr UR - https://www.jmir.org/2024/1/e47616 UR - http://dx.doi.org/10.2196/47616 UR - http://www.ncbi.nlm.nih.gov/pubmed/38640471 ID - info:doi/10.2196/47616 ER - TY - JOUR AU - King, C. Ryan AU - Samaan, S. Jamil AU - Yeo, Hui Yee AU - Peng, Yuxin AU - Kunkel, C. David AU - Habib, A. Ali AU - Ghashghaei, Roxana PY - 2024/4/19 TI - A Multidisciplinary Assessment of ChatGPT?s Knowledge of Amyloidosis: Observational Study JO - JMIR Cardio SP - e53421 VL - 8 KW - amyloidosis KW - ChatGPT KW - large language models KW - cardiology KW - gastroenterology KW - neurology KW - artificial intelligence KW - multidisciplinary care KW - assessment KW - patient education KW - large language model KW - accuracy KW - reliability KW - accessibility KW - educational resources KW - dissemination KW - gastroenterologist KW - cardiologist KW - medical society KW - institution KW - institutions KW - Facebook KW - neurologist KW - reproducibility KW - amyloidosis-related N2 - Background: Amyloidosis, a rare multisystem condition, often requires complex, multidisciplinary care. Its low prevalence underscores the importance of efforts to ensure the availability of high-quality patient education materials for better outcomes. ChatGPT (OpenAI) is a large language model powered by artificial intelligence that offers a potential avenue for disseminating accurate, reliable, and accessible educational resources for both patients and providers. Its user-friendly interface, engaging conversational responses, and the capability for users to ask follow-up questions make it a promising future tool in delivering accurate and tailored information to patients. Objective: We performed a multidisciplinary assessment of the accuracy, reproducibility, and readability of ChatGPT in answering questions related to amyloidosis. Methods: In total, 98 amyloidosis questions related to cardiology, gastroenterology, and neurology were curated from medical societies, institutions, and amyloidosis Facebook support groups and inputted into ChatGPT-3.5 and ChatGPT-4. Cardiology- and gastroenterology-related responses were independently graded by a board-certified cardiologist and gastroenterologist, respectively, who specialize in amyloidosis. These 2 reviewers (RG and DCK) also graded general questions for which disagreements were resolved with discussion. Neurology-related responses were graded by a board-certified neurologist (AAH) who specializes in amyloidosis. Reviewers used the following grading scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Questions were stratified by categories for further analysis. Reproducibility was assessed by inputting each question twice into each model. The readability of ChatGPT-4 responses was also evaluated using the Textstat library in Python (Python Software Foundation) and the Textstat readability package in R software (R Foundation for Statistical Computing). Results: ChatGPT-4 (n=98) provided 93 (95%) responses with accurate information, and 82 (84%) were comprehensive. ChatGPT-3.5 (n=83) provided 74 (89%) responses with accurate information, and 66 (79%) were comprehensive. When examined by question category, ChatGTP-4 and ChatGPT-3.5 provided 53 (95%) and 48 (86%) comprehensive responses, respectively, to ?general questions? (n=56). When examined by subject, ChatGPT-4 and ChatGPT-3.5 performed best in response to cardiology questions (n=12) with both models producing 10 (83%) comprehensive responses. For gastroenterology (n=15), ChatGPT-4 received comprehensive grades for 9 (60%) responses, and ChatGPT-3.5 provided 8 (53%) responses. Overall, 96 of 98 (98%) responses for ChatGPT-4 and 73 of 83 (88%) for ChatGPT-3.5 were reproducible. The readability of ChatGPT-4?s responses ranged from 10th to beyond graduate US grade levels with an average of 15.5 (SD 1.9). Conclusions: Large language models are a promising tool for accurate and reliable health information for patients living with amyloidosis. However, ChatGPT?s responses exceeded the American Medical Association?s recommended fifth- to sixth-grade reading level. Future studies focusing on improving response accuracy and readability are warranted. Prior to widespread implementation, the technology?s limitations and ethical implications must be further explored to ensure patient safety and equitable implementation. UR - https://cardio.jmir.org/2024/1/e53421 UR - http://dx.doi.org/10.2196/53421 UR - http://www.ncbi.nlm.nih.gov/pubmed/38640472 ID - info:doi/10.2196/53421 ER - TY - JOUR AU - Regan, Wherley Elizabeth AU - Toto, Pamela AU - Brach, Jennifer PY - 2024/4/11 TI - A Community Needs Assessment and Implementation Planning for a Community Exercise Program for Survivors of Stroke: Protocol for a Pilot Hybrid Type I Clinical Effectiveness and Implementation Study JO - JMIR Res Protoc SP - e55432 VL - 13 KW - community participatory research KW - need assessment KW - exercise KW - survivors of stroke KW - community KW - community need KW - exercise program KW - stroke KW - physical activity KW - PA KW - mobility impairments KW - impairment KW - mobility KW - health decline KW - group activity KW - group exercise N2 - Background: Physical activity and exercise are important aspects of maintaining health. People with mobility impairments, including survivors of stroke, are less likely to exercise and at greater risk of developing or worsening chronic health conditions. Increasing accessible, desired options for exercise may address the gap in available physical activity programs, provide an opportunity for continued services after rehabilitation, and cultivate social connections for people after stroke and others with mobility impairments. Existing evidence-based community programs for people after stroke target cardiovascular endurance, mobility, walking ability, balance, and education. While much is known about the effectiveness of these programs, it is important to understand the local environment as implementation and sustainment strategies are context-specific. Objective: This study protocol aims to evaluate community needs and resources for exercise for adults living with mobility impairments with initial emphasis on survivors of stroke in Richland County, South Carolina. Results will inform a hybrid type I effectiveness and implementation pilot of an evidence-based group exercise program for survivors of stroke. Methods: The exploration and preparation phases of the EPIS (Exploration, Preparation, Implementation, and Sustainment) implementation model guide the study. A community needs assessment will evaluate the needs and desires of survivors of stroke through qualitative semistructured interviews with survivors of stroke, rehabilitation professionals, and fitness trainers serving people with mobility impairments. Additional data will be collected from survivors of stroke through a survey. Fitness center sites will be assessed through interviews and the Accessibility Instrument Measuring Fitness and Recreation Environments inventory. Qualitative data will be evaluated using content analysis and supported by mean survey results. Data will be categorized by the community (outer context), potential participants (outer context), and fitness center (inner context) and evaluate needs, resources, barriers, and facilitators. Results will inform evidence-based exercise program selection, adaptations, and specific local implementation strategies to influence success. Pilot outcome measures for participants (clinical effectiveness), process, and program delivery levels will be identified. An implementation logic model for interventions will be created to reflect the design elements for the pilot and their complex interactions. Results: The study was reviewed by the institutional review board and exempt approved on December 19, 2023. The study data collection began in January 2024 and is projected to be completed in June 2024. A total of 17 participants have been interviewed as of manuscript submission. Results are expected to be published in early 2025. Conclusions: Performing a needs assessment before implementing it in the community allows for early identification of complex relationships and preplanning to address problems that cannot be anticipated in controlled effectiveness research. Evaluation and preparation prior to implementation of a community exercise program enhance the potential to be successful, valued, and sustained in the community. International Registered Report Identifier (IRRID): DERR1-10.2196/55432 UR - https://www.researchprotocols.org/2024/1/e55432 UR - http://dx.doi.org/10.2196/55432 UR - http://www.ncbi.nlm.nih.gov/pubmed/38603776 ID - info:doi/10.2196/55432 ER - TY - JOUR AU - Awindaogo, Felix AU - Acheamfour-Akowuah, Emmanuel AU - Doku, Alfred AU - Kokuro, Collins AU - Agyekum, Francis AU - Owusu, Kofi Isaac PY - 2024/4/8 TI - Assessing and Improving the Care of Patients With Heart Failure in Ghana: Protocol for a Prospective Observational Study and the Ghana Heart Initiative-Heart Failure Registry JO - JMIR Res Protoc SP - e52616 VL - 13 KW - clinical KW - cross-sectional KW - epidemiology KW - Ghana KW - heart failure KW - heart KW - management KW - medium-term KW - monitoring KW - mortality KW - outcome KW - patient data KW - prevention KW - protocol KW - teaching KW - treatment N2 - Background: Heart failure (HF) is a leading cause of morbidity and mortality globally, with a high disease burden. The prevalence of HF in Ghana is increasing rapidly, but epidemiological profiles, treatment patterns, and survival data are scarce. The national capacity to diagnose and manage HF appropriately is also limited. To address the growing epidemic of HF, it is crucial to recognize the epidemiological characteristics and medium-term outcomes of HF in Ghana and improve the capability to identify and manage HF promptly and effectively at all levels of care. Objective: This study aims to determine the epidemiological characteristics and medium-term HF outcomes in Ghana. Methods: We conducted a prospective, multicenter, multilevel cross-sectional observational study of patients with HF from January to December 2023. Approximately 5000 patients presenting with HF to 9 hospitals, including teaching, regional, and municipal hospitals, will be recruited and evaluated according to a standardized protocol, including the use of an echocardiogram and an N-terminal pro-brain natriuretic peptide (NT-proBNP) test. Guideline-directed medical treatment of HF will be initiated for 6 months, and the medium-term outcomes of interventions, including rehospitalization and mortality, will be assessed. Patient data will be collated into a HF registry for continuous assessment and monitoring. Results: This intervention will generate the necessary information on the etiology of HF, clinical presentations, the diagnostic yield of various tools, and management outcomes. In addition, it will build the necessary capacity and support for HF management in Ghana. As of July 30, 2023, the training and onboarding of all 9 centers had been completed. Preliminary analyses will be conducted by the end of the second quarter of 2024, and results are expected to be publicly available by the middle of 2024. Conclusions: This study will provide the necessary data on HF, which will inform decisions on the prevention and management of HF and form the basis for future research. Trial Registration: ISRCTN Registry (United Kingdom) ISRCTN18216214; https:www.isrctn.com/ISRCTN18216214 International Registered Report Identifier (IRRID): DERR1-10.2196/52616 UR - https://www.researchprotocols.org/2024/1/e52616 UR - http://dx.doi.org/10.2196/52616 UR - http://www.ncbi.nlm.nih.gov/pubmed/38588528 ID - info:doi/10.2196/52616 ER - TY - JOUR AU - Chabrak, Sonia AU - Haggui, Abdeddayem AU - Allouche, Emna AU - Ouali, Sana AU - Ben Halima, Afef AU - Kacem, Slim AU - Krichen, Salma AU - Marrakchi, Sonia AU - Fehri, Wafa AU - Mourali, Sami Mohamed AU - Jabbari, Zeineb AU - Ben Halima, Manel AU - Neffati, Elyes AU - Heraiech, Aymen  AU - Slim, Mehdi AU - Kachboura, Salem AU - Gamra, Habib AU - Hassine, Majed AU - Kraiem, Sondes AU - Kammoun, Sofien AU - Bezdah, Leila AU - Jridi, Gouider AU - Bouraoui, Hatem AU - Kammoun, Samir AU - Hammami, Rania AU - Chettaoui, Rafik AU - Ben Ameur, Youssef AU - Azaiez, Fares AU - Tlili, Rami AU - Battikh, Kais AU - Ben Slima, Hedi AU - Chrigui, Rim AU - Fazaa, Samia AU - Sanaa, Islem AU - Ellouz, Yassine AU - Mosrati, Mohamed AU - Milouchi, Sami AU - Jarmouni, Soumaya AU - Ayadi, Wacef AU - Akrout, Malek AU - Razgallah, Rabie AU - Neffati, Wissal AU - Drissa, Meriem AU - Charfeddine, Selma AU - Abdessalem, Salem AU - Abid, Leila AU - Zakhama, Lilia PY - 2024/4/8 TI - National Tunisian Study of Cardiac Implantable Electronic Devices: Design and Protocol for a Nationwide Multicenter Prospective Observational Study JO - JMIR Res Protoc SP - e47525 VL - 13 KW - Tunisia KW - study KW - pacemaker KW - implantable cardioverter defibrillator KW - cardiac resynchronization therapy KW - design KW - complication N2 - Background: In Tunisia, the number of cardiac implantable electronic devices (CIEDs) is increasing, owing to the increase in patient life expectancy and expanding indications. Despite their life-saving potential and a significant reduction in population morbidity and mortality, their increased numbers have been associated with the development of multiple early and late complications related to vascular access, pockets, leads, or patient characteristics. Objective: The study aims to identify the rate, type, and predictors of complications occurring within the first year after CIED implantation. It also aims to describe the demographic and epidemiological characteristics of a nationwide sample of patients with CIED in Tunisia. Additionally, the study will evaluate the extent to which Tunisian electrophysiologists follow international guidelines for cardiac pacing and sudden cardiac death prevention. Methods: The Tunisian National Study of Cardiac Implantable Electronic Devices (NATURE-CIED) is a national, multicenter, prospectively monitored study that includes consecutive patients who underwent primary CIED implantation, generator replacement, and upgrade procedure. Patients were enrolled between January 18, 2021, and February 18, 2022, at all Tunisian public and private CIED implantation centers that agreed to participate in the study. All enrolled patients entered a 1-year follow-up period, with 4 consecutive visits at 1, 3, 6, and 12 months after CIED implantation. The collected data are recorded electronically on the clinical suite platform (DACIMA Clinical Suite). Results: The study started on January 18, 2021, and concluded on February 18, 2023. In total, 27 cardiologists actively participated in data collection. Over this period, 1500 patients were enrolled in the study consecutively. The mean age of the patients was 70.1 (SD 15.2) years, with a sex ratio of 1:15. Nine hundred (60%) patients were from the public sector, while 600 (40%) patients were from the private sector. A total of 1298 (86.3%) patients received a conventional pacemaker and 75 (5%) patients received a biventricular pacemaker (CRT-P). Implantable cardioverter defibrillators were implanted in 127 (8.5%) patients. Of these patients, 45 (3%) underwent CRT-D implantation. Conclusions: This study will establish the most extensive contemporary longitudinal cohort of patients undergoing CIED implantation in Tunisia, presenting a significant opportunity for real-world clinical epidemiology. It will address a crucial gap in the management of patients during the perioperative phase and follow-up, enabling the identification of individuals at particularly high risk of complications for optimal care. Trial Registration: ClinicalTrials.gov NCT05361759; https://classic.clinicaltrials.gov/ct2/show/NCT05361759 International Registered Report Identifier (IRRID): RR1-10.2196/47525 UR - https://www.researchprotocols.org/2024/1/e47525 UR - http://dx.doi.org/10.2196/47525 UR - http://www.ncbi.nlm.nih.gov/pubmed/38588529 ID - info:doi/10.2196/47525 ER - TY - JOUR AU - Wang, Xuzhi AU - Zhang, Yuankai AU - Pathiravasan, H. Chathurangi AU - Ukonu, C. Nene AU - Rong, Jian AU - Benjamin, J. Emelia AU - McManus, D. David AU - Larson, G. Martin AU - Vasan, S. Ramachandran AU - Hamburg, M. Naomi AU - Murabito, M. Joanne AU - Liu, Chunyu AU - Mitchell, F. Gary PY - 2024/4/8 TI - Association of Arterial Stiffness With Mid- to Long-Term Home Blood Pressure Variability in the Electronic Framingham Heart Study: Cohort Study JO - JMIR Cardio SP - e54801 VL - 8 KW - arterial stiffness KW - mobile health KW - mHealth KW - blood pressure KW - blood pressure variability KW - risk factors N2 - Background: Short-term blood pressure variability (BPV) is associated with arterial stiffness in patients with hypertension. Few studies have examined associations between arterial stiffness and digital home BPV over a mid- to long-term time span, irrespective of underlying hypertension. Objective: This study aims to investigate if arterial stiffness traits were associated with subsequent mid- to long-term home BPV in the electronic Framingham Heart Study (eFHS). We hypothesized that higher arterial stiffness was associated with higher home BPV over up to 1-year follow-up. Methods: At a Framingham Heart Study research examination (2016-2019), participants underwent arterial tonometry to acquire measures of arterial stiffness (carotid-femoral pulse wave velocity [CFPWV]; forward pressure wave amplitude [FWA]) and wave reflection (reflection coefficient [RC]). Participants who agreed to enroll in eFHS were provided with a digital blood pressure (BP) cuff to measure home BP weekly over up to 1-year follow-up. Participants with less than 3 weeks of BP readings were excluded. Linear regression models were used to examine associations of arterial measures with average real variability (ARV) of week-to-week home systolic (SBP) and diastolic (DBP) BP adjusting for important covariates. We obtained ARV as an average of the absolute differences of consecutive home BP measurements. ARV considers not only the dispersion of the BP readings around the mean but also the order of BP readings. In addition, ARV is more sensitive to measurement-to-measurement BPV compared with traditional BPV measures. Results: Among 857 eFHS participants (mean age 54, SD 9 years; 508/857, 59% women; mean SBP/DBP 119/76 mm Hg; 405/857, 47% hypertension), 1 SD increment in FWA was associated with 0.16 (95% CI 0.09-0.23) SD increments in ARV of home SBP and 0.08 (95% CI 0.01-0.15) SD increments in ARV of home DBP; 1 SD increment in RC was associated with 0.14 (95% CI 0.07-0.22) SD increments in ARV of home SBP and 0.11 (95% CI 0.04-0.19) SD increments in ARV of home DBP. After adjusting for important covariates, there was no significant association between CFPWV and ARV of home SBP, and similarly, no significant association existed between CFPWV and ARV of home DBP (P>.05). Conclusions: In eFHS, higher FWA and RC were associated with higher mid- to long-term ARV of week-to-week home SBP and DBP over 1-year follow-up in individuals across the BP spectrum. Our findings suggest that higher aortic stiffness and wave reflection are associated with higher week-to-week variation of BP in a home-based setting over a mid- to long-term time span. UR - https://cardio.jmir.org/2024/1/e54801 UR - http://dx.doi.org/10.2196/54801 UR - http://www.ncbi.nlm.nih.gov/pubmed/38587880 ID - info:doi/10.2196/54801 ER - TY - JOUR AU - Hu, Zhao AU - Wang, Min AU - Zheng, Si AU - Xu, Xiaowei AU - Zhang, Zhuxin AU - Ge, Qiaoyue AU - Li, Jiao AU - Yao, Yan PY - 2024/3/26 TI - Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis Within the Frameworks of Knowledge and Practice: Survey Study JO - JMIR Hum Factors SP - e55802 VL - 11 KW - clinical decision support system KW - requirements analysis KW - ventricular tachycardia KW - knowledge KW - clinical practice KW - questionnaires N2 - Background: Ventricular tachycardia (VT) diagnosis is challenging due to the similarity between VT and some forms of supraventricular tachycardia, complexity of clinical manifestations, heterogeneity of underlying diseases, and potential for life-threatening hemodynamic instability. Clinical decision support systems (CDSSs) have emerged as promising tools to augment the diagnostic capabilities of cardiologists. However, a requirements analysis is acknowledged to be vital for the success of a CDSS, especially for complex clinical tasks such as VT diagnosis. Objective: The aims of this study were to analyze the requirements for a VT diagnosis CDSS within the frameworks of knowledge and practice and to determine the clinical decision support (CDS) needs. Methods: Our multidisciplinary team first conducted semistructured interviews with seven cardiologists related to the clinical challenges of VT and expected decision support. A questionnaire was designed by the multidisciplinary team based on the results of interviews. The questionnaire was divided into four sections: demographic information, knowledge assessment, practice assessment, and CDS needs. The practice section consisted of two simulated cases for a total score of 10 marks. Online questionnaires were disseminated to registered cardiologists across China from December 2022 to February 2023. The scores for the practice section were summarized as continuous variables, using the mean, median, and range. The knowledge and CDS needs sections were assessed using a 4-point Likert scale without a neutral option. Kruskal-Wallis tests were performed to investigate the relationship between scores and practice years or specialty. Results: Of the 687 cardiologists who completed the questionnaire, 567 responses were eligible for further analysis. The results of the knowledge assessment showed that 383 cardiologists (68%) lacked knowledge in diagnostic evaluation. The overall average score of the practice assessment was 6.11 (SD 0.55); the etiological diagnosis section had the highest overall scores (mean 6.74, SD 1.75), whereas the diagnostic evaluation section had the lowest scores (mean 5.78, SD 1.19). A majority of cardiologists (344/567, 60.7%) reported the need for a CDSS. There was a significant difference in practice competency scores between general cardiologists and arrhythmia specialists (P=.02). Conclusions: There was a notable deficiency in the knowledge and practice of VT among Chinese cardiologists. Specific knowledge and practice support requirements were identified, which provide a foundation for further development and optimization of a CDSS. Moreover, it is important to consider clinicians? specialization levels and years of practice for effective and personalized support. UR - https://humanfactors.jmir.org/2024/1/e55802 UR - http://dx.doi.org/10.2196/55802 UR - http://www.ncbi.nlm.nih.gov/pubmed/38530337 ID - info:doi/10.2196/55802 ER - TY - JOUR AU - Ahn, Hyo-Jeong AU - Choi, Eue-Keun AU - Lee, So-Ryoung AU - Kwon, Soonil AU - Song, Hee-Seok AU - Lee, Young-Shin AU - Oh, Seil PY - 2024/3/21 TI - Three-Day Monitoring of Adhesive Single-Lead Electrocardiogram Patch for Premature Ventricular Complex: Prospective Study for Diagnosis Validation and Evaluation of Burden Fluctuation JO - J Med Internet Res SP - e46098 VL - 26 KW - premature ventricular complex KW - single-lead electrocardiogram KW - wearable device KW - extended monitor KW - electrocardiogram KW - EKG KW - ECG KW - wearable KW - heart KW - cardiology KW - cardiovascular N2 - Background: Wearable electrocardiogram (ECG) monitoring devices are used worldwide. However, data on the diagnostic yield of an adhesive single-lead ECG patch (SEP) to detect premature ventricular complex (PVC) and the optimal duration of wearing an SEP for PVC burden assessment are limited. Objective: We aimed to validate the diagnostic yield of an SEP (mobiCARE MC-100, Seers Technology) for PVC detection and evaluate the PVC burden variation recorded by the SEP over a 3-day monitoring period. Methods: This is a prospective study of patients with documented PVC on a 12-lead ECG. Patients underwent simultaneous ECG monitoring with the 24-hour Holter monitor and SEP on the first day. On the subsequent second and third days, ECG monitoring was continued using only SEP, and a 3-day extended monitoring was completed. The diagnostic yield of SEP for PVC detection was evaluated by comparison with the results obtained on the first day of Holter monitoring. The PVC burden monitored by SEP for 3 days was used to assess the daily and 6-hour PVC burden variations. The number of patients additionally identified to reach PVC thresholds of 10%, 15%, and 20% during the 3-day extended monitoring by SEP and the clinical factors associated with the higher PVC burden variations were explored. Results: The recruited data of 134 monitored patients (mean age, 54.6 years; males, 45/134, 33.6%) were analyzed. The median daily PVC burden of these patients was 2.4% (IQR 0.2%-10.9%), as measured by the Holter monitor, and 3.3% (IQR 0.3%-11.7%), as measured in the 3-day monitoring by SEP. The daily PVC burden detected on the first day of SEP was in agreement with that of the Holter monitor: the mean difference was ?0.07%, with 95% limits of agreement of ?1.44% to 1.30%. A higher PVC burden on the first day was correlated with a higher daily (R2=0.34) and 6-hour burden variation (R2=0.48). Three-day monitoring by SEP identified 29% (12/42), 18% (10/56), and 7% (4/60) more patients reaching 10%, 15%, and 20% of daily PVC burden, respectively. Younger age was additionally associated with the identification of clinically significant PVC burden during the extended monitoring period (P=.02). Conclusions: We found that the mobiCARE MC-100 SEP accurately detects PVC with comparable diagnostic yield to the 24-hour Holter monitor. Performing 3-day PVC monitoring with SEP, especially among younger patients, may offer a pragmatic alternative for identifying more individuals exceeding the clinically significant PVC burden threshold. UR - https://www.jmir.org/2024/1/e46098 UR - http://dx.doi.org/10.2196/46098 UR - http://www.ncbi.nlm.nih.gov/pubmed/38512332 ID - info:doi/10.2196/46098 ER - TY - JOUR AU - Cáceres Rivera, Isabel Diana AU - Rojas, Jaimes Luz Mileyde AU - Rojas, Z. Lyda AU - Gomez, Canon Diana AU - Castro Ruiz, Andrés David AU - López Romero, Alberto Luis PY - 2024/3/18 TI - Using Principles of Digital Development for a Smartphone App to Support Data Collection in Patients With Acute Myocardial Infarction and Physical Activity Intolerance: Case Study JO - JMIR Form Res SP - e33868 VL - 8 KW - app KW - applications of medical informatics KW - coronary disease KW - data collection KW - development KW - health care reform KW - health data KW - medical informatics KW - medical informatics apps KW - mobile app KW - mobile applications KW - nursing diagnosis KW - nursing research KW - research data KW - software KW - validation N2 - Background: Advances in health have highlighted the need to implement technologies as a fundamental part of the diagnosis, treatment, and recovery of patients at risk of or with health alterations. For this purpose, digital platforms have demonstrated their applicability in the identification of care needs. Nursing is a fundamental component in the care of patients with cardiovascular disorders and plays a crucial role in diagnosing human responses to these health conditions. Consequently, the validation of nursing diagnoses through ongoing research processes has become a necessity that can significantly impact both patients and health care professionals. Objective: We aimed to describe the process of developing a mobile app to validate the nursing diagnosis ?intolerance to physical activity? in patients with acute myocardial infarction. Methods: We describe the development and pilot-testing of a mobile system to support data collection for validating the nursing diagnosis of activity intolerance. This was a descriptive study conducted with 11 adults (aged ?18 years) who attended a health institution for highly complex needs with a suspected diagnosis of coronary syndrome between August and September 2019 in Floridablanca, Colombia. An app for the clinical validation of activity intolerance (North American Nursing Diagnosis Association [NANDA] code 00092) in patients with acute coronary syndrome was developed in two steps: (1) operationalization of the nursing diagnosis and (2) the app development process, which included an evaluation of the initial requirements, development and digitization of the forms, and a pilot test. The agreement level between the 2 evaluating nurses was evaluated with the ? index. Results: We developed a form that included sociodemographic data, hospital admission data, medical history, current pharmacological treatment, and thrombolysis in myocardial infarction risk score (TIMI-RS) and GRACE (Global Registry of Acute Coronary Events) scores. To identify the defining characteristics, we included official guidelines, physiological measurements, and scales such as the Piper fatigue scale and Borg scale. Participants in the pilot test (n=11) had an average age of 63.2 (SD 4.0) years and were 82% (9/11) men; 18% (2/11) had incomplete primary schooling. The agreement between the evaluators was approximately 80% for most of the defining characteristics. The most prevalent characteristics were exercise discomfort (10/11, 91%), weakness (7/11, 64%), dyspnea (3/11, 27%), abnormal heart rate in response to exercise (2/10, 20%), electrocardiogram abnormalities (1/10, 9%), and abnormal blood pressure in response to activity (1/10, 10%). Conclusions: We developed a mobile app for validating the diagnosis of ?activity intolerance.? Its use will guarantee not only optimal data collection, minimizing errors to perform validation, but will also allow the identification of individual care needs. UR - https://formative.jmir.org/2024/1/e33868 UR - http://dx.doi.org/10.2196/33868 UR - http://www.ncbi.nlm.nih.gov/pubmed/38498019 ID - info:doi/10.2196/33868 ER - TY - JOUR AU - Nair, Monika AU - Lundgren, E. Lina AU - Soliman, Amira AU - Dryselius, Petra AU - Fogelberg, Ebba AU - Petersson, Marcus AU - Hamed, Omar AU - Triantafyllou, Miltiadis AU - Nygren, Jens PY - 2024/3/11 TI - Machine Learning Model for Readmission Prediction of Patients With Heart Failure Based on Electronic Health Records: Protocol for a Quasi-Experimental Study for Impact Assessment JO - JMIR Res Protoc SP - e52744 VL - 13 KW - artificial intelligence KW - machine learning KW - readmission prediction KW - heart failure KW - clinical decision support KW - machine learning model KW - CHF KW - congestive heart failure KW - readmission KW - prediction KW - electronic health records KW - electronic health record KW - EHR KW - quasi-experimental study KW - decision-making process KW - risk assessment KW - risk assessment tool KW - predictive models KW - predictive model KW - Sweden KW - physician KW - nurse KW - nurses KW - clinician KW - clinicians N2 - Background: Care for patients with heart failure (HF) causes a substantial load on health care systems where a prominent challenge is the elevated rate of readmissions within 30 days following initial discharge. Clinical professionals face high levels of uncertainty and subjectivity in the decision-making process on the optimal timing of discharge. Unwanted hospital stays generate costs and cause stress to patients and potentially have an impact on care outcomes. Recent studies have aimed to mitigate the uncertainty by developing and testing risk assessment tools and predictive models to identify patients at risk of readmission, often using novel methods such as machine learning (ML). Objective: This study aims to investigate how a developed clinical decision support (CDS) tool alters the decision-making processes of health care professionals in the specific context of discharging patients with HF, and if so, in which ways. Additionally, the aim is to capture the experiences of health care practitioners as they engage with the system?s outputs to analyze usability aspects and obtain insights related to future implementation. Methods: A quasi-experimental design with randomized crossover assessment will be conducted with health care professionals on HF patients? scenarios in a region located in the South of Sweden. In total, 12 physicians and nurses will be randomized into control and test groups. The groups shall be provided with 20 scenarios of purposefully sampled patients. The clinicians will be asked to take decisions on the next action regarding a patient. The test group will be provided with the 10 scenarios containing patient data from electronic health records and an outcome from an ML-based CDS model on the risk level for readmission of the same patients. The control group will have 10 other scenarios without the CDS model output and containing only the patients? data from electronic medical records. The groups will switch roles for the next 10 scenarios. This study will collect data through interviews and observations. The key outcome measures are decision consistency, decision quality, work efficiency, perceived benefits of using the CDS model, reliability, validity, and confidence in the CDS model outcome, integrability in the routine workflow, ease of use, and intention to use. This study will be carried out in collaboration with Cambio Healthcare Systems. Results: The project is part of the Center for Applied Intelligent Systems Research Health research profile, funded by the Knowledge Foundation (2021-2028). Ethical approval for this study was granted by the Swedish ethical review authority (2022-07287-02). The recruitment process of the clinicians and the patient scenario selection will start in September 2023 and last till March 2024. Conclusions: This study protocol will contribute to the development of future formative evaluation studies to test ML models with clinical professionals. International Registered Report Identifier (IRRID): PRR1-10.2196/52744 UR - https://www.researchprotocols.org/2024/1/e52744 UR - http://dx.doi.org/10.2196/52744 UR - http://www.ncbi.nlm.nih.gov/pubmed/38466983 ID - info:doi/10.2196/52744 ER - TY - JOUR AU - Muehlensiepen, Felix AU - Hoffmann, Josephine Marie AU - Nübel, Jonathan AU - Ignatyev, Yury AU - Heinze, Martin AU - Butter, Christian AU - Haase-Fielitz, Anja PY - 2024/2/20 TI - Acceptance of Telemedicine by Specialists and General Practitioners in Cardiology Care: Cross-Sectional Survey Study JO - JMIR Form Res SP - e49526 VL - 8 KW - acceptance KW - adoption KW - cardiac KW - cardiology KW - cross sectional KW - health services research KW - heart KW - preference KW - survey KW - telecardiology KW - telehealth KW - telemedicine N2 - Background: In the coming years, telemedicine will play a key role in health care. Especially in rural areas with weak infrastructure, telemedicine could be crucial to providing adequate and personalized medical care. Objective: We investigated the acceptance and preferences of telemedicine among cardiologists, internists, and general practitioners. In addition, we aimed to identify knowledge, explore factors that influence the decision to adopt or reject this technology, and create starting points for demand-oriented further research. Methods: We conducted a web-based survey between May 2021 and February 2022. The 34-item questionnaire covered a wide range of questions regarding knowledge, acceptance, and use of telemedicine in cardiology care. Participants (cardiologists, internists, and general practitioners) were contacted through their professional email addresses, through a QR code published in a regional health journal, and through X (formerly known as Twitter). After exclusion of questionnaires with missed values, multidimensional scaling and k-means clustering were performed. Participants were divided into 3 clusters (C1, C2, and C3) based on their attitudes toward telecardiology. C1 uses telemedicine for personal health and clinical practice; C2 shows reluctance; C3 uses telemedicine mainly clinically. Results: We contacted 929 physicians. Of those 12.1% (112/929) completed the questionnaires. Participants were 56% male (54/97), 29% female (28/97), and 2% (2/97) diverse (median age 50 years). About 16% (18/112) of the respondents currently use telemedicine daily, 14.3% (16/112) 3-4 times a week, and 43% (48/112) did not use telemedicine at all. Overall, 35.1% (34/97) rated their knowledge of telemedicine as very good or good. Most of the respondents replied that telemedicine could support cardiology care in monitoring of blood pressure and electrocardiograms (57/97, 58.8%, both), consultation (57/97, 58.8%), and extending follow-up time (59/97, 60.8%). Reported barriers to implementation were mostly administration (26/97, 26.8%), inadequate reimbursement (25/97, 25.8%), and the purchase of technology equipment (23/97, 23.7%). Attitudes toward telemedicine in clinical practice were closely related to the number of patients being treated per annual quarter: C3 (median 1350, IQR 1000-1500) versus C1 (median 750, IQR 300-1200) and C2 (median 500, IQR 105-825). The differences between clinical caseloads of C1-C3 members were significant: C1 versus C2 (P=.03), C1 versus C3 (P=.02), and C2 versus C3 (P<.001). Most participants (87/112, 77.7%) would like to expand telemedicine approaches in the future. In the field of cardiology, the participants reported a high suitability of telemedicine. The willingness to train in telemedicine is high to very high for > 50% of the participants. Conclusions: Our results indicate generally moderate use but positive attitudes toward telemedicine among participating physicians with a higher clinical caseload. The lack of a structural framework seems to be a barrier to the effective implementation of telecardiology. UR - https://formative.jmir.org/2024/1/e49526 UR - http://dx.doi.org/10.2196/49526 UR - http://www.ncbi.nlm.nih.gov/pubmed/38376898 ID - info:doi/10.2196/49526 ER - TY - JOUR AU - Gerhardy, Benjamin AU - Sivapathan, Shanthosh AU - Orde, Sam AU - Morgan, Lucy PY - 2024/2/12 TI - Simultaneous Cardiopulmonary Exercise Testing and Echocardiography for Investigation of Cardiopulmonary Dysfunction in Outpatients: Protocol for a Scoping Review JO - JMIR Res Protoc SP - e52076 VL - 13 KW - cardiopulmonary KW - echocardiography KW - exercise KW - cardiopulmonary exercise test N2 - Background: Cardiopulmonary dysfunction is a complex process with a broad range of etiologies. Investigations performed either at rest or those that only assess the function of a single organ (heart or lungs) are often insufficient. A simultaneous cardiopulmonary exercise test with stress echocardiography is a new approach to assessing cardiopulmonary dysfunction as it provides anatomical and functional imaging simultaneously while under increasing stress. To date, the application of cardiopulmonary exercise test-stress echocardiography (CPET-SE) has been broad and without structure, and its effect on patient outcomes is unclear. Objective: The objective of this scoping review is to explore and analyze the evidence regarding the role of simultaneous CPET-SE in investigating cardiopulmonary dysfunction in outpatients. It will include any published study in which adult (older than or equal to 18 years of age) patients have completed a CPET-SE for the investigation of cardiopulmonary dysfunction. Methods: This review will follow the Arksey and O?Malley framework, supported by the Joanna Briggs Institute methodology for scoping reviews. It will use the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Data sources will include MEDLINE, Scopus, Embase, and Cochrane (including reviews, trials, and protocols) electronic databases, with no date range defined. The search will be limited to the English language with no restrictions regarding pathology. Secondary references of the included sources will also be assessed by a hand search for suitability. A 2-person title-abstract screen and data charting process will be used. Independent experts will be used for consultation including an academic librarian and clinicians. The Covidence software will be used for article screening. Results: This scoping review will provide a unified and detailed description of the applications of CPET-SE in investigating cardiopulmonary dysfunction. This will provide a platform for future research harnessing this investigatory method. The results will be presented in both tabular and graphical formats to ensure clarity. The results of this scoping review will be submitted to a relevant peer-reviewed academic journal for publication. Conclusions: The CPET-SE is a powerful tool for investigating cardiopulmonary dysfunction but remains in its infancy with a patchwork approach to indications, data reporting, and interpretation. This scoping review will unify the literature and provide a platform for future researchers and the development of a comprehensive application guideline. Trial Registration: Open Science Framework; https://osf.io/98r3e International Registered Report Identifier (IRRID): PRR1-10.2196/52076 UR - https://www.researchprotocols.org/2024/1/e52076 UR - http://dx.doi.org/10.2196/52076 UR - http://www.ncbi.nlm.nih.gov/pubmed/38345834 ID - info:doi/10.2196/52076 ER - TY - JOUR AU - Antoniou, Panagiotis AU - Dafli, Eleni AU - Giannakoulas, George AU - Igimbayeva, Gaukhar AU - Visternichan, Olga AU - Kyselov, Serhii AU - Lykhasenko, Ivetta AU - Lashkul, Dmytro AU - Nadareishvili, Ilia AU - Tabagari, Sergo AU - Bamidis, D. Panagiotis PY - 2024/1/23 TI - Education of Patients With Atrial Fibrillation and Evaluation of the Efficacy of a Mobile Virtual Patient Environment: Protocol for a Multicenter Pseudorandomized Controlled Trial JO - JMIR Res Protoc SP - e45946 VL - 13 KW - atrial fibrillation KW - virtual patient KW - scenario based learning KW - technology enhanced learning KW - mHealth KW - mobile health KW - patient engagement KW - patient education KW - cardiac arrhythmia KW - mortality KW - mobile application KW - mobile app KW - health education KW - randomized control trial KW - cardiology KW - cardiac KW - heart KW - Greece KW - Ukraine KW - Kazakhstan KW - clinical decision support systems KW - CDSS KW - virtual patient scenario KW - myocardial infarction KW - arrhythmia KW - stroke N2 - Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a leading cause of mortality and morbidity. Patient knowledge about AF and its management is paramount but often limited. Patients need to be appropriately informed about treatment options, medicinal adherence, and potential consequences of nonadherence, while also understanding treatment goals and expectations from it. Mobile health apps have experienced an explosion both in their availability and acceptance as ?soft interventions? for patient engagement and education; however, the prolific nature of such solutions revealed a gap in the evidence base regarding their efficacy and impact. Virtual patients (VPs), interactive computer simulations, have been used as learning activities in modern health care education. VPs demonstrably improved cognitive and behavioral skills; hence, they have been effectively implemented across undergraduate and postgraduate curricula. However, their application in patient education has been rather limited so far. Objective: This work aims to implement and evaluate the efficacy of a mobile-deployed VP regimen for the education and engagement of patients with AF on crucial topics regarding their condition. A mobile VP app is being developed with the goal of each VP being a simple scenario with a set goal and very specific messages and will be subsequently attempted and evaluated. Methods: A mobile VP player app is being developed so as to be used for the design of 3 educational scenarios for AF management. A pseudorandomized controlled trial for the efficacy of VPs is planned to be executed at 3 sites in Greece, Ukraine, and Kazakhstan for patients with AF. The Welch t test will be used to demonstrate the performance of patients? evaluation of the VP experience. Results: Our study is at the development stage. A preliminary study regarding the system?s development and feasibility was initiated in December 2022. The results of our study are expected to be available in 2024 or when the needed sample size is achieved. Conclusions: This study aims to evaluate and demonstrate the first significant evidence for the value of VP resources in outreach and training endeavors for empowering and patients with AF and fostering healthy habits among them. International Registered Report Identifier (IRRID): PRR1-10.2196/45946 UR - https://www.researchprotocols.org/2024/1/e45946 UR - http://dx.doi.org/10.2196/45946 UR - http://www.ncbi.nlm.nih.gov/pubmed/38261376 ID - info:doi/10.2196/45946 ER - TY - JOUR AU - Kong, Qingyu AU - Xu, Xue AU - Li, Meng AU - Meng, Xiao AU - Zhao, Cuifen AU - Yang, Xiaorong PY - 2024/1/11 TI - Global, Regional, and National Burden of Myocarditis in 204 Countries and Territories From 1990 to 2019: Updated Systematic Analysis JO - JMIR Public Health Surveill SP - e46635 VL - 10 KW - myocarditis KW - global burden KW - temporal trend KW - systematic analysis KW - incidence KW - mortality KW - disability-adjusted life years N2 - Background: Myocarditis is characterized by high disability and mortality, and imposes a severe burden on population health globally. However, the latest global magnitude and secular trend of myocarditis burden have not been reported. Objective: This study aimed to delineate the epidemiological characteristics of myocarditis burden globally for optimizing targeted prevention and research. Methods: Based on the Global Burden of Disease Study 2019, the myocarditis burden from 1990 to 2019 was modeled using the Cause of Death Ensemble tool, DisMod-MR, and spatiotemporal Gaussian regression. We depicted the epidemiology and trends of myocarditis by sex, age, year, region, and sociodemographic index (SDI). R program version 4.2.1 (R Project for Statistical Computing) was applied for all statistical analyses, and a 2-sided P-value of <.05 was considered statistically significant. Results: The number of incident cases (1,268,000) and deaths (32,450) associated with myocarditis in 2019 increased by over 1.6 times compared with the values in 1990 globally. On the other hand, the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) decreased slightly from 1990 to 2019. The disability-adjusted life years (DALYs) decreased slightly in the past 3 decades, while the age-standardized DALY rate (ASDR) decreased greatly from 18.29 per 100,000 person-years in 1990 to 12.81 per 100,000 person-years in 2019. High SDI regions always showed a more significant ASIR. The ASIR slightly decreased in all SDI regions between 1990 and 2019. Middle SDI regions had the highest ASMR and ASDR in 2019. Low SDI regions had the lowest ASMR and ASDR in 2019. The age-standardized rates (ASRs) of myocarditis were higher among males than among females from 1990 to 2019 globally. All ASRs among both sexes had a downward trend, except for the ASMR among males, which showed a stable trend, and females had a more significant decrease in the ASDR than males. Senior citizens had high incident cases and deaths among both sexes in 2019. The peak numbers of DALYs for both sexes were noted in the under 1 age group in 2019. At the national level, the estimated annual percentage changes in the ASRs had significant negative correlations with the baseline ASRs in 1990. Conclusions: Globally, the number of incident cases and deaths associated with myocarditis have increased significantly. On the other hand, the ASRs of myocarditis showed decreasing trends from 1990 to 2019. Males consistently showed higher ASRs of myocarditis than females from 1990 to 2019 globally. Senior citizens gradually predominated in terms of myocarditis burden. Policymakers should establish targeted control strategies based on gender, region, age, and SDI; strengthen aging-related health research; and take notice of the changes in the epidemic characteristics of myocarditis. UR - https://publichealth.jmir.org/2024/1/e46635 UR - http://dx.doi.org/10.2196/46635 UR - http://www.ncbi.nlm.nih.gov/pubmed/38206659 ID - info:doi/10.2196/46635 ER - TY - JOUR AU - Chang, Hao-Yun AU - Wu, Hui-Wen AU - Hung, Chi-Sheng AU - Chen, Ying-Hsien AU - Huang, Ching-Chang AU - Yang, Li-Tan AU - Hwang, Shin-Tsyr AU - Yu, Jiun-Yu AU - Lee, Jen-Kuang AU - Ho, Yi-Lwun PY - 2024/1/8 TI - Costs and Cardiovascular Benefits of a Fourth-Generation Synchronous Telehealth Program on Mortality and Cardiovascular Outcomes for Patients With Atrial Fibrillation: Retrospective Cohort Study JO - J Med Internet Res SP - e48748 VL - 26 KW - atrial fibrillation KW - cardiovascular death KW - fourth-generation synchronous program KW - ischemic stroke KW - telehealth N2 - Background: The prevalence of atrial fibrillation (AF) continues to increase in modern aging society. Patients with AF are at high risk for multiple adverse cardiovascular events, including heart failure, stroke, and mortality. Improved medical care is needed for patients with AF to enhance their quality of life and limit their medical resource utilization. With advances in the internet and technology, telehealth programs are now widely used in medical care. A fourth-generation telehealth program offers synchronous and continuous medical attention in response to physiological parameters measured at home. Although we have previously shown the benefits of this telehealth program for some patients with a high risk of cardiovascular disease, its benefits for patients with AF remains uncertain. Objective: This study aims to investigate the benefits of participating in a fourth-generation telehealth program for patients with AF in relation to cardiovascular outcomes. Methods: This was a retrospective cohort study. We retrospectively searched the medical records database of a tertiary medical center in Northern Taiwan between January 2007 and December 2017. We screened 5062 patients with cardiovascular disease and enrolled 537 patients with AF, of which 279 participated in the telehealth program and 258 did not. Bias was reduced using the inverse probability of treatment weighting adjustment based on the propensity score. Outcomes were collected and analyzed, including all-cause readmission, admission for heart failure, acute coronary syndrome, ischemic stroke, systemic embolism, bleeding events, all-cause mortality, and cardiovascular death within the follow-up period. Total medical expenses and medical costs in different departments were also compared. Subgroup analyses were conducted on ischemic stroke stratified by several subgroup variables. Results: The mean follow-up period was 3.0 (SD 1.7) years for the telehealth group and 3.4 (SD 1.9) years for the control group. After inverse probability of treatment weighting adjustment, the patients in the telehealth program had significantly fewer ischemic strokes (2.0 vs 4.5 events per 100 person-years; subdistribution hazard ratio [SHR] 0.45, 95% CI 0.22-0.92) and cardiovascular deaths (2.5 vs 5.9 events per 100 person-years; SHR 0.43, 95% CI 0.18-0.99) at the follow-up. The telehealth program particularly benefited patients comorbid with vascular disease (SHR 0.11, 95% CI 0.02-0.53 vs SHR 1.16, 95% CI 0.44-3.09; P=.01 for interaction). The total medical expenses during follow-up were similar in the telehealth and control groups. Conclusions: This study demonstrated the benefits of participating in the fourth-generation telehealth program for patients with AF by significantly reducing their ischemic stroke risk while spending the same amount on medical expenses. UR - https://www.jmir.org/2024/1/e48748 UR - http://dx.doi.org/10.2196/48748 UR - http://www.ncbi.nlm.nih.gov/pubmed/38190237 ID - info:doi/10.2196/48748 ER - TY - JOUR AU - Zhang, Pin AU - Wu, Lei AU - Zou, Ting-Ting AU - Zou, ZiXuan AU - Tu, JiaXin AU - Gong, Ren AU - Kuang, Jie PY - 2024/1/3 TI - Machine Learning for Early Prediction of Major Adverse Cardiovascular Events After First Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Retrospective Cohort Study JO - JMIR Form Res SP - e48487 VL - 8 KW - acute myocardial infarction KW - percutaneous coronary intervention KW - machine learning KW - early prediction KW - cardiovascular event N2 - Background: The incidence of major adverse cardiovascular events (MACEs) remains high in patients with acute myocardial infarction (AMI) who undergo percutaneous coronary intervention (PCI), and early prediction models to guide their clinical management are lacking. Objective: This study aimed to develop machine learning?based early prediction models for MACEs in patients with newly diagnosed AMI who underwent PCI. Methods: A total of 1531 patients with AMI who underwent PCI from January 2018 to December 2019 were enrolled in this consecutive cohort. The data comprised demographic characteristics, clinical investigations, laboratory tests, and disease-related events. Four machine learning models?artificial neural network (ANN), k-nearest neighbors, support vector machine, and random forest?were developed and compared with the logistic regression model. Our primary outcome was the model performance that predicted the MACEs, which was determined by accuracy, area under the receiver operating characteristic curve, and F1-score. Results: In total, 1362 patients were successfully followed up. With a median follow-up of 25.9 months, the incidence of MACEs was 18.5% (252/1362). The area under the receiver operating characteristic curve of the ANN, random forest, k-nearest neighbors, support vector machine, and logistic regression models were 80.49%, 72.67%, 79.80%, 77.20%, and 71.77%, respectively. The top 5 predictors in the ANN model were left ventricular ejection fraction, the number of implanted stents, age, diabetes, and the number of vessels with coronary artery disease. Conclusions: The ANN model showed good MACE prediction after PCI for patients with AMI. The use of machine learning?based prediction models may improve patient management and outcomes in clinical practice. UR - https://formative.jmir.org/2024/1/e48487 UR - http://dx.doi.org/10.2196/48487 UR - http://www.ncbi.nlm.nih.gov/pubmed/38170581 ID - info:doi/10.2196/48487 ER - TY - JOUR AU - Schulze Lammers, Sophia AU - Lawrenz, Thorsten AU - Lawin, Dennis AU - Hoyer, Annika AU - Stellbrink, Christoph AU - Albrecht, Urs-Vito PY - 2023/12/29 TI - Prolonged mHealth-Based Arrhythmia Monitoring in Patients With Hypertrophic Cardiomyopathy (HCM-PATCH): Protocol for a Single-Center Cohort Study JO - JMIR Res Protoc SP - e52035 VL - 12 KW - hypertrophic cardiomyopathy KW - nonsustained ventricular arrhythmia KW - sudden cardiac death KW - implantable cardioverter-defibrillator KW - long-term ECG KW - digital medicine KW - long-term electrocardiography N2 - Background: Patients with hypertrophic cardiomyopathy (HCM) are at increased risk of sudden cardiac death (SCD) due to ventricular arrhythmias and other arrhythmias. Screening for arrhythmias is mandatory to assess the individual SCD risk, but long-term electrocardiography (ECG) is rarely performed in routine clinical practice. Intensified monitoring may increase the detection rate of ventricular arrhythmias and identify more patients with an increased SCD risk who are potential candidates for the primary prophylactic implantation of an implantable cardioverter-defibrillator. To date, reliable data on the clinical benefit of prolonged arrhythmia monitoring in patients with HCM are rare. Objective: This prospective study aims to measure the prevalence of ventricular arrhythmias in patients with HCM observed by mobile health (mHealth)?based continuous rhythm monitoring over 14 days compared to standard practice (a 24- and 48-h long-term ECG). The frequency of ventricular arrhythmias in this 14-day period is compared with the frequency in the first 24 or 48 hours for the same patient (intraindividual comparison). Methods: Following the sample size calculation, 34 patients with a low or intermediate risk for SCD, assessed by the HCM Risk?SCD calculator, will need to be recruited in this single-center cohort study between June 2023 and February 2024. All patients will receive an ECG patch that records their heart activity over 14 days. In addition, cardiac magnetic resonance imaging and genetic testing data will be integrated into risk stratification. All patients will be asked to complete questionnaires about their symptoms; previous therapy; family history; and, at the end of the study, their experience with the ECG patch-based monitoring. Results: The Hypertrophic Cardiomyopathy: Clinical Impact of a Prolonged mHealth-Based Arrhythmia Monitoring by Single-Channel ECG (HCM-PATCH) study investigates the prevalence of nonsustained ventricular tachycardia (ie, ?3 consecutive ventricular beats at a rate of 120 beats per minute, lasting for <30 seconds) in low- to intermediate-risk patients with HCM (according to the HCM Risk?SCD calculator) with additional mHealth-based prolonged rhythm monitoring. The study was funded by third-party funding from the Department of Cardiology and Intensive Care Medicine, University Hospital Ostwestfalen-Lippe of Bielefeld University in June 2023 and approved by the institutional review board in May 2023. Data collection began in June 2023, and we plan to end the study in February 2024. Of the 34 patients, 26 have been recruited. Data analysis has not yet taken place. Publication of the results is planned for the fall of 2024. Conclusions: Prolonged mHealth-based rhythm monitoring could lead to differences in the prevalence of arrhythmias compared to 24- and 48-hour long-term ECGs. This may lead to improved identification of patients at high risk and trigger therapeutic interventions that may provide better protection from SCD or atrial fibrillation?related complications such as embolic stroke. Trial Registration: Deutsches Register Klinischer Studien DRKS00032144; https://tinyurl.com/498bkrx8 International Registered Report Identifier (IRRID): DERR1-10.2196/52035 UR - https://www.researchprotocols.org/2023/1/e52035 UR - http://dx.doi.org/10.2196/52035 UR - http://www.ncbi.nlm.nih.gov/pubmed/38157231 ID - info:doi/10.2196/52035 ER - TY - JOUR AU - Kim, Kwan Yun AU - Koo, Hyung Ja AU - Lee, Jung Sun AU - Song, Seok Hee AU - Lee, Minji PY - 2023/12/22 TI - Explainable Artificial Intelligence Warning Model Using an Ensemble Approach for In-Hospital Cardiac Arrest Prediction: Retrospective Cohort Study JO - J Med Internet Res SP - e48244 VL - 25 KW - cardiac arrest prediction KW - ensemble learning KW - temporal pattern changes KW - cost-sensitive learning KW - electronic medical records N2 - Background: Cardiac arrest (CA) is the leading cause of death in critically ill patients. Clinical research has shown that early identification of CA reduces mortality. Algorithms capable of predicting CA with high sensitivity have been developed using multivariate time series data. However, these algorithms suffer from a high rate of false alarms, and their results are not clinically interpretable. Objective: We propose an ensemble approach using multiresolution statistical features and cosine similarity?based features for the timely prediction of CA. Furthermore, this approach provides clinically interpretable results that can be adopted by clinicians. Methods: Patients were retrospectively analyzed using data from the Medical Information Mart for Intensive Care-IV database and the eICU Collaborative Research Database. Based on the multivariate vital signs of a 24-hour time window for adults diagnosed with heart failure, we extracted multiresolution statistical and cosine similarity?based features. These features were used to construct and develop gradient boosting decision trees. Therefore, we adopted cost-sensitive learning as a solution. Then, 10-fold cross-validation was performed to check the consistency of the model performance, and the Shapley additive explanation algorithm was used to capture the overall interpretability of the proposed model. Next, external validation using the eICU Collaborative Research Database was performed to check the generalization ability. Results: The proposed method yielded an overall area under the receiver operating characteristic curve (AUROC) of 0.86 and area under the precision-recall curve (AUPRC) of 0.58. In terms of the timely prediction of CA, the proposed model achieved an AUROC above 0.80 for predicting CA events up to 6 hours in advance. The proposed method simultaneously improved precision and sensitivity to increase the AUPRC, which reduced the number of false alarms while maintaining high sensitivity. This result indicates that the predictive performance of the proposed model is superior to the performances of the models reported in previous studies. Next, we demonstrated the effect of feature importance on the clinical interpretability of the proposed method and inferred the effect between the non-CA and CA groups. Finally, external validation was performed using the eICU Collaborative Research Database, and an AUROC of 0.74 and AUPRC of 0.44 were obtained in a general intensive care unit population. Conclusions: The proposed framework can provide clinicians with more accurate CA prediction results and reduce false alarm rates through internal and external validation. In addition, clinically interpretable prediction results can facilitate clinician understanding. Furthermore, the similarity of vital sign changes can provide insights into temporal pattern changes in CA prediction in patients with heart failure?related diagnoses. Therefore, our system is sufficiently feasible for routine clinical use. In addition, regarding the proposed CA prediction system, a clinically mature application has been developed and verified in the future digital health field. UR - https://www.jmir.org/2023/1/e48244 UR - http://dx.doi.org/10.2196/48244 UR - http://www.ncbi.nlm.nih.gov/pubmed/38133922 ID - info:doi/10.2196/48244 ER - TY - JOUR AU - Song, Junxian AU - Cui, Yuxia AU - Song, Jing AU - Lee, Chongyou AU - Wu, Manyan AU - Chen, Hong PY - 2023/12/19 TI - Evaluation of the Needs and Experiences of Patients with Hypertriglyceridemia: Social Media Listening Infosurveillance Study JO - J Med Internet Res SP - e44610 VL - 25 KW - social media listening KW - hypertriglyceridemia KW - infosurveillance study KW - disease cognition KW - lifestyle intervention KW - lipid disorder KW - awareness KW - online search KW - telemedicine KW - self-medication KW - Chinese medicine KW - natural language processing KW - cardiovascular disease KW - stroke KW - online platform KW - self-management KW - Q&A search platform KW - social media N2 - Background: Hypertriglyceridemia is a risk factor for cardiovascular diseases. Internet usage in China is increasing, giving rise to large-scale data sources, especially to access, disseminate, and discuss medical information. Social media listening (SML) is a new approach to analyze and monitor online discussions related to various health-related topics in diverse diseases, which can generate insights into users? experiences and expectations. However, to date, no studies have evaluated the utility of SML to understand patients? cognizance and expectations pertaining to the management of hypertriglyceridemia. Objective: The aim of this study was to utilize SML to explore the disease cognition level of patients with hypertriglyceridemia, choice of intervention measures, and the status quo of online consultations and question-and-answer (Q&A) search platforms. Methods: An infosurveillance study was conducted wherein a disease-specific comprehensive search was performed between 2004 and 2020 in Q&A search and online consultation platforms. Predefined single and combined keywords related to hypertriglyceridemia were used in the search, including disease, symptoms, diagnosis, and treatment indicators; lifestyle interventions; and therapeutic agents. The search output was aggregated using an aggregator tool and evaluated. Results: Disease-specific consultation data (n=69,845) and corresponding response data (n=111,763) were analyzed from 20 data sources (6 Q&A search platforms and 14 online consultation platforms). Doctors from inland areas had relatively high voice volumes and appear to exert a substantial influence on these platforms. Patients with hypertriglyceridemia engaging on the internet have an average level of cognition about the disease and its intervention measures. However, a strong demand for the concept of the disease and ?how to treat it? was observed. More emphasis on the persistence of the disease and the safety of medications was observed. Young patients have a lower willingness for drug interventions, whereas patients with severe hypertriglyceridemia have a clearer intention to use drug intervention and few patients have a strong willingness for the use of traditional Chinese medicine. Conclusions: Findings from this disease-specific SML study revealed that patients with hypertriglyceridemia in China actively seek information from both online Q&A search and consultation platforms. However, the integrity of internet doctors? suggestions on lifestyle interventions and the accuracy of drug intervention recommendations still need to be improved. Further, a combined prospective qualitative study with SML is required for added rigor and confirmation of the relevance of the findings. UR - https://www.jmir.org/2023/1/e44610 UR - http://dx.doi.org/10.2196/44610 UR - http://www.ncbi.nlm.nih.gov/pubmed/38113100 ID - info:doi/10.2196/44610 ER - TY - JOUR AU - Dryden, Lindsay AU - Song, Jacquelin AU - Valenzano, J. Teresa AU - Yang, Zhen AU - Debnath, Meggie AU - Lin, Rebecca AU - Topolovec-Vranic, Jane AU - Mamdani, Muhammad AU - Antoniou, Tony PY - 2023/12/6 TI - Evaluation of Machine Learning Approaches for Predicting Warfarin Discharge Dose in Cardiac Surgery Patients: Retrospective Algorithm Development and Validation Study JO - JMIR Cardio SP - e47262 VL - 7 KW - algorithm KW - anticlotting KW - anticoagulant KW - anticoagulation KW - blood thinner KW - cardiac KW - cardiology KW - develop KW - dosage KW - international normalized ratio KW - machine learning KW - medical informatics KW - pharmacology KW - postoperative KW - predict KW - prescribe KW - prescription KW - surgery KW - surgical KW - validate KW - validation KW - warfarin administration and dosage KW - warfarin N2 - Background: Warfarin dosing in cardiac surgery patients is complicated by a heightened sensitivity to the drug, predisposing patients to adverse events. Predictive algorithms are therefore needed to guide warfarin dosing in cardiac surgery patients. Objective: This study aimed to develop and validate an algorithm for predicting the warfarin dose needed to attain a therapeutic international normalized ratio (INR) at the time of discharge in cardiac surgery patients. Methods: We abstracted variables influencing warfarin dosage from the records of 1031 encounters initiating warfarin between April 1, 2011, and November 29, 2019, at St Michael?s Hospital in Toronto, Ontario, Canada. We compared the performance of penalized linear regression, k-nearest neighbors, random forest regression, gradient boosting, multivariate adaptive regression splines, and an ensemble model combining the predictions of the 5 regression models. We developed and validated separate models for predicting the warfarin dose required for achieving a discharge INR of 2.0-3.0 in patients undergoing all forms of cardiac surgery except mechanical mitral valve replacement and a discharge INR of 2.5-3.5 in patients receiving a mechanical mitral valve replacement. For the former, we selected 80% of encounters (n=780) who had initiated warfarin during their hospital admission and had achieved a target INR of 2.0-3.0 at the time of discharge as the training cohort. Following 10-fold cross-validation, model accuracy was evaluated in a test cohort comprised solely of cardiac surgery patients. For patients requiring a target INR of 2.5-3.5 (n=165), we used leave-p-out cross-validation (p=3 observations) to estimate model performance. For each approach, we determined the mean absolute error (MAE) and the proportion of predictions within 20% of the true warfarin dose. We retrospectively evaluated the best-performing algorithm in clinical practice by comparing the proportion of cardiovascular surgery patients discharged with a therapeutic INR before (April 2011 and July 2019) and following (September 2021 and May 2, 2022) its implementation in routine care. Results: Random forest regression was the best-performing model for patients with a target INR of 2.0-3.0, an MAE of 1.13 mg, and 39.5% of predictions of falling within 20% of the actual therapeutic discharge dose. For patients with a target INR of 2.5-3.5, the ensemble model performed best, with an MAE of 1.11 mg and 43.6% of predictions being within 20% of the actual therapeutic discharge dose. The proportion of cardiovascular surgery patients discharged with a therapeutic INR before and following implementation of these algorithms in clinical practice was 47.5% (305/641) and 61.1% (11/18), respectively. Conclusions: Machine learning algorithms based on routinely available clinical data can help guide initial warfarin dosing in cardiac surgery patients and optimize the postsurgical anticoagulation of these patients. UR - https://cardio.jmir.org/2023/1/e47262 UR - http://dx.doi.org/10.2196/47262 UR - http://www.ncbi.nlm.nih.gov/pubmed/38055310 ID - info:doi/10.2196/47262 ER - TY - JOUR AU - Schwab, Josephine AU - Wachinger, Jonas AU - Munana, Richard AU - Nabiryo, Maxencia AU - Sekitoleko, Isaac AU - Cazier, Juliette AU - Ingenhoff, Rebecca AU - Favaretti, Caterina AU - Subramonia Pillai, Vasanthi AU - Weswa, Ivan AU - Wafula, John AU - Emmrich, Valentin Julius AU - Bärnighausen, Till AU - Knauf, Felix AU - Knauss, Samuel AU - Nalwadda, K. Christine AU - Sudharsanan, Nikkil AU - Kalyesubula, Robert AU - McMahon, A. Shannon PY - 2023/11/30 TI - Design Research to Embed mHealth into a Community-Led Blood Pressure Management System in Uganda: Protocol for a Mixed Methods Study JO - JMIR Res Protoc SP - e46614 VL - 12 KW - Uganda KW - hypertension KW - mobile health KW - mHealth KW - mobile money KW - pooled financing KW - medication availability KW - human-centered design KW - mixed methods KW - mobile phone N2 - Background: Uncontrolled hypertension is a leading risk factor for cardiovascular diseases. In Uganda, such diseases account for approximately 10% of all deaths, with 1 in 5 adults having hypertension (>90% of the hypertensive cases are uncontrolled). Although basic health care in the country is available free of cost at government facilities, regularly accessing medication to control hypertension is difficult because supply chain challenges impede availability. Clients therefore frequently suspend treatment or buy medication individually at private facilities or pharmacies (incurring significant costs). In recent years, mobile health (mHealth) interventions have shown increasing potential in addressing health system challenges in sub-Saharan Africa, but the acceptability, feasibility, and uptake conditions of mobile money approaches to chronic disease management remain understudied. Objective: This study aims to design and pilot-test a mobile money?based intervention to increase the availability of antihypertensive medication and lower clients? out-of-pocket payments. We will build on existing local approaches and assess the acceptability, feasibility, and uptake of the designed intervention. Furthermore, rather than entering the study setting with a ready-made intervention, this research will place emphasis on gathering applied ethnographic insights early, which can then inform the parameters of the intervention prototype and concurrent trial. Methods: We will conduct a mixed methods study following a human-centered design approach. We will begin by conducting extensive qualitative research with a range of stakeholders (clients; health care providers; religious, cultural, and community leaders; academics; and policy makers at district and national levels) on their perceptions of hypertension management, money-saving systems, and mobile money in the context of health care. Our results will inform the design, iterative adaptation, and implementation of an mHealth-facilitated pooled financing intervention prototype. At study conclusion, the finalized prototype will be evaluated quantitatively via a randomized controlled trial. Results: As of August 2023, qualitative data collection, which started in November 2022, is ongoing, with data analysis of the first qualitative interviews underway to inform platform and implementation design. Recruitment for the quantitative part of this study began in August 2023. Conclusions: Our results aim to inform the ongoing discourse on novel and sustainable pathways to facilitate access to medication for the management of hypertension in resource-constrained settings. Trial Registration: German registry of clinical trials DRKS00030922; https://drks.de/search/en/trial/DRKS00030922 International Registered Report Identifier (IRRID): DERR1-10.2196/46614 UR - https://www.researchprotocols.org/2023/1/e46614 UR - http://dx.doi.org/10.2196/46614 UR - http://www.ncbi.nlm.nih.gov/pubmed/38032702 ID - info:doi/10.2196/46614 ER - TY - JOUR AU - Simonson, K. Julie AU - Anderson, Misty AU - Polacek, Cate AU - Klump, Erika AU - Haque, N. Saira PY - 2023/11/3 TI - Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review JO - JMIR Cardio SP - e47292 VL - 7 KW - arrhythmias KW - atrial fibrillation KW - clinical workflow KW - consumer wearable devices KW - smartwatches KW - wearables KW - remote patient monitoring KW - virtual care KW - mobile phone N2 - Background: Atrial fibrillation (AF), the most common cardiac arrhythmia, is often undiagnosed because of lack of awareness and frequent asymptomatic presentation. As AF is associated with increased risk of stroke, early detection is clinically relevant. Several consumer wearable devices (CWDs) have been cleared by the US Food and Drug Administration for irregular heart rhythm detection suggestive of AF. However, recommendations for the use of CWDs for AF detection in clinical practice, especially with regard to pathways for workflows and clinical decisions, remain lacking. Objective: We conducted a targeted literature review to identify articles on CWDs characterizing the current state of wearable technology for AF detection, identifying approaches to implementing CWDs into the clinical workflow, and characterizing provider and patient perspectives on CWDs for patients at risk of AF. Methods: PubMed, ClinicalTrials.gov, UpToDate Clinical Reference, and DynaMed were searched for articles in English published between January 2016 and July 2023. The searches used predefined Medical Subject Headings (MeSH) terms, keywords, and search strings. Articles of interest were specifically on CWDs; articles on ambulatory monitoring tools, tools available by prescription, or handheld devices were excluded. Search results were reviewed for relevancy and discussed among the authors for inclusion. A qualitative analysis was conducted and themes relevant to our study objectives were identified. Results: A total of 31 articles met inclusion criteria: 7 (23%) medical society reports or guidelines, 4 (13%) general reviews, 5 (16%) systematic reviews, 5 (16%) health care provider surveys, 7 (23%) consumer or patient surveys or interviews, and 3 (10%) analytical reports. Despite recognition of CWDs by medical societies, detailed guidelines regarding CWDs for AF detection were limited, as was the availability of clinical tools. A main theme was the lack of pragmatic studies assessing real-world implementation of CWDs for AF detection. Clinicians expressed concerns about data overload; potential for false positives; reimbursement issues; and the need for clinical tools such as care pathways and guidelines, preferably developed or endorsed by professional organizations. Patient-facing challenges included device costs and variability in digital literacy or technology acceptance. Conclusions: This targeted literature review highlights the lack of a comprehensive body of literature guiding real-world implementation of CWDs for AF detection and provides insights for informing additional research and developing appropriate tools and resources for incorporating these devices into clinical practice. The results should also provide an impetus for the active involvement of medical societies and other health care stakeholders in developing appropriate tools and resources for guiding the real-world use of CWDs for AF detection. These resources should target clinicians, patients, and health care systems with the goal of facilitating clinician or patient engagement and using an evidence-based approach for establishing guidelines or frameworks for administrative workflows and patient care pathways. UR - https://cardio.jmir.org/2023/1/e47292 UR - http://dx.doi.org/10.2196/47292 UR - http://www.ncbi.nlm.nih.gov/pubmed/37921865 ID - info:doi/10.2196/47292 ER - TY - JOUR AU - Nicmanis, Mitchell AU - Chur-Hansen, Anna AU - Linehan, Karen PY - 2023/11/1 TI - The Information Needs and Experiences of People Living With Cardiac Implantable Electronic Devices: Qualitative Content Analysis of Reddit Posts JO - JMIR Cardio SP - e46296 VL - 7 KW - implantable cardioverter defibrillator KW - pacemaker KW - cardiac resynchronization therapy KW - social media KW - patients KW - peer support KW - content analysis KW - experiences N2 - Background: Cardiac implantable electronic devices (CIEDs) are used to treat a range of cardiovascular diseases and can lead to substantial clinical improvements. However, studies evaluating patients? experiences of living with these devices are sparse and have focused mainly on implantable cardioverter defibrillators. In addition, there has been limited evaluation of how people living with a CIED use social media to gain insight into their condition. Objective: This study aims to analyze posts from web-based communities called subreddits on the website Reddit, intended for people living with a CIED, to characterize the informational needs and experiences of patients. Methods: Reddit was systematically searched for appropriate subreddits, and we found 1 subreddit that could be included in the analysis. A Python-based web scraping script using the Reddit application programming interface was used to extract posts from this subreddit. Each post was individually screened for relevancy, and a register of participants? demographic information was created. Conventional qualitative content analysis was used to inductively classify the qualitative data collected into codes, subcategories, and overarching categories. Results: Of the 484 posts collected using the script, 186 were excluded, resulting in 298 posts from 196 participants being included in the analysis. The median age of the participants who reported this was 33 (IQR 22.0-39.5; range 17-72) years, and the majority had a permanent pacemaker. The content analysis yielded 5 overarching categories: use of the subreddit by participants, questions and experiences related to the daily challenges of living with a CIED, physical sequelae of CIED implantation, psychological experiences of living with a CIED, and questions and experiences related to health care while living with a CIED. These categories provided insight into the diverse experiences and informational needs of participants living with a CIED. The data predominantly represented the experiences of younger and more physically active participants. Conclusions: Social media provides a platform through which people living with a CIED can share information and provide support to their peers. Participants generally sought information about the experiences of others living with a CIED. This was often done to help overcome a range of challenges faced by participants, including the need to adapt to living with a CIED, difficulties with navigating health care, psychological difficulties, and various aversive physical sequelae. These challenges may be particularly difficult for younger and physically active people. Health care professionals may leverage peer support and other aid to help people overcome the challenges they face while living with a CIED. UR - https://cardio.jmir.org/2023/1/e46296 UR - http://dx.doi.org/10.2196/46296 UR - http://www.ncbi.nlm.nih.gov/pubmed/37766632 ID - info:doi/10.2196/46296 ER - TY - JOUR AU - Soliman, Amira AU - Agvall, Björn AU - Etminani, Kobra AU - Hamed, Omar AU - Lingman, Markus PY - 2023/10/27 TI - The Price of Explainability in Machine Learning Models for 100-Day Readmission Prediction in Heart Failure: Retrospective, Comparative, Machine Learning Study JO - J Med Internet Res SP - e46934 VL - 25 KW - readmission prediction KW - heart failure KW - machine learning KW - explainable artificial intelligence KW - deep learning KW - shallow learning N2 - Background: Sensitive and interpretable machine learning (ML) models can provide valuable assistance to clinicians in managing patients with heart failure (HF) at discharge by identifying individual factors associated with a high risk of readmission. In this cohort study, we delve into the factors driving the potential utility of classification models as decision support tools for predicting readmissions in patients with HF. Objective: The primary objective of this study is to assess the trade-off between using deep learning (DL) and traditional ML models to identify the risk of 100-day readmissions in patients with HF. Additionally, the study aims to provide explanations for the model predictions by highlighting important features both on a global scale across the patient cohort and on a local level for individual patients. Methods: The retrospective data for this study were obtained from the Regional Health Care Information Platform in Region Halland, Sweden. The study cohort consisted of patients diagnosed with HF who were over 40 years old and had been hospitalized at least once between 2017 and 2019. Data analysis encompassed the period from January 1, 2017, to December 31, 2019. Two ML models were developed and validated to predict 100-day readmissions, with a focus on the explainability of the model?s decisions. These models were built based on decision trees and recurrent neural architecture. Model explainability was obtained using an ML explainer. The predictive performance of these models was compared against 2 risk assessment tools using multiple performance metrics. Results: The retrospective data set included a total of 15,612 admissions, and within these admissions, readmission occurred in 5597 cases, representing a readmission rate of 35.85%. It is noteworthy that a traditional and explainable model, informed by clinical knowledge, exhibited performance comparable to the DL model and surpassed conventional scoring methods in predicting readmission among patients with HF. The evaluation of predictive model performance was based on commonly used metrics, with an area under the precision-recall curve of 66% for the deep model and 68% for the traditional model on the holdout data set. Importantly, the explanations provided by the traditional model offer actionable insights that have the potential to enhance care planning. Conclusions: This study found that a widely used deep prediction model did not outperform an explainable ML model when predicting readmissions among patients with HF. The results suggest that model transparency does not necessarily compromise performance, which could facilitate the clinical adoption of such models. UR - https://www.jmir.org/2023/1/e46934 UR - http://dx.doi.org/10.2196/46934 UR - http://www.ncbi.nlm.nih.gov/pubmed/37889530 ID - info:doi/10.2196/46934 ER - TY - JOUR AU - Kazi, Samia AU - Truesdale, Chloe AU - Ryan, Pauline AU - Wiesner, Glen AU - Jennings, Garry AU - Chow, Clara PY - 2023/10/5 TI - Initial Implementation of the My Heart, My Life Program by the National Heart Foundation of Australia: Pilot Mixed Methods Evaluation Study JO - JMIR Cardio SP - e43889 VL - 7 KW - cardiology KW - prevention KW - digital health KW - heart KW - text message KW - text messaging KW - SMS KW - health communication KW - demographic KW - preventative KW - cardio N2 - Background: Coronary heart disease (CHD) remains the leading cause of death in Australia, with a high residual risk of repeat events in survivors. Secondary prevention therapy is crucial for reducing the risk of both death and other major adverse cardiac events. The National Heart Foundation of Australia has developed a consumer-facing support program called My Heart, My Life (MHML) to address the gap in the secondary prevention of CHD in Australia. The MHML pilot program supplies advice and support for both patients and their caregivers, and it was conducted over 8 months from November 2019 to June 2020. Objective: This study aims to describe and examine the implementation of a novel multimodality secondary CHD prevention pilot program called MHML, which was delivered through booklets, text messages, emails, and telephone calls. Methods: This pilot study consists of a mixed methods evaluation involving surveys of participants (patients and caregivers) and health professionals, in-depth interviews, and digital communication (SMS text message, electronic direct mail, and call record analytics). This study was performed in people older than 18 years with acute coronary syndrome or angina and their caregivers in 38 Australian hospitals from November 2019 to June 2020 through the National Heart Foundation of Australia web page. The main outcome measures were reach, accessibility, feasibility, barriers, and enablers to implementation of this program. Results: Of the 1004 participants (838 patients and 164 caregivers; 2 missing), 60.9% (608/1001) were males, 50.7% (491/967) were aged between 45 and 64 years, 27.4% (276/1004) were from disadvantaged areas, 2.5% (24/946) were from Aboriginal or Torres Strait Islander background, and 16.9% (170/1004) reported English as their second language. The participants (patients and their caregivers) and health professionals reported high satisfaction with the MHML program (55/62, 88.7% and 33/38, 87%, respectively). Of the 62 participants who took the survey, 88% (55/62) used the text messaging service and reported a very high level of satisfaction. Approximately 94% (58/62) and 89% (55/62) of the participants were satisfied with the quick guide booklets 1 and 2, respectively; 79% (49/62) were satisfied with the monthly email journey and 71% (44/62) were satisfied with the helpline calls. Most participants reported that the MHML program improved preventive behaviors, that is, 73% (45/62) of them reported that they maintained increased physical activity and 84% (52/62) reported that they maintained a healthy diet even after the MHML program. Conclusions: The findings of our pilot study suggest that a multimodal support program, including digital, print, phone, and web-based media, for the secondary prevention of CHD is useful and could be a potential means of providing customized at-scale secondary prevention support for survivors of acute coronary syndrome. UR - https://cardio.jmir.org/2023/1/e43889 UR - http://dx.doi.org/10.2196/43889 UR - http://www.ncbi.nlm.nih.gov/pubmed/37796544 ID - info:doi/10.2196/43889 ER - TY - JOUR AU - Abdou, Abdelrahman AU - Krishnan, Sridhar AU - Mistry, Niraj PY - 2023/10/2 TI - Evaluating a Novel Infant Heart Rate Detector for Neonatal Resuscitation Efforts: Protocol for a Proof-of-Concept Study JO - JMIR Res Protoc SP - e45512 VL - 12 KW - newborn KW - electrocardiogram KW - ECG KW - dry electrode KW - heart rate KW - pediatric KW - resuscitation KW - infant KW - vital signs KW - neonatal N2 - Background: Over 10 million newborns worldwide undergo resuscitation at birth each year. Pediatricians may use electrocardiogram (ECG), pulse oximetry (PO), and stethoscope in determining heart rate (HR), as HR guides the need for and steps of resuscitation. HR must be obtained quickly and accurately. Unfortunately, the current diagnostic modalities are either too slow, obtaining HR in more than a minute, or inaccurate. With time constraints, a reliable robust heart rate detector (HRD) modality is required. This paper discusses a protocol for conducting a methods-based comparison study to determine the HR accuracy of a novel real-time HRD based on 3D-printed dry-electrode single-lead ECG signals for cost-effective and quick HR determination. The HRD?s HR results are compared to either clinical-grade ECG or PO monitors to ensure robustness and accuracy. Objective: The purpose of this study is to design and examine the feasibility of a proof-of-concept HRD that quickly obtains HR using biocompatible 3D-printed dry electrodes for single-lead neonatal ECG acquisition. This study uses a novel HRD and compares it to the gold-standard 3-lead clinical ECG or PO in a hospital setting. Methods: A cross-sectional study is planned to be conducted in the neonatal intensive care unit or postpartum unit of a large community teaching hospital in Toronto, Canada, from June 2023 to June 2024. In total, 50 newborns will be recruited for this study. The HRD and an ECG or PO monitor will be video recorded using a digital camera concurrently for 3 minutes for each newborn. Hardware-based signal processing and patent-pending embedded algorithm-based HR estimation techniques are applied directly to the raw collected single-lead ECG and displayed on the HRD in real time during video recordings. These data will be annotated and compared to the ECG or PO readings at the same points in time. Accuracy, F1-score, and other statistical metrics will be produced to determine the HRD?s feasibility in providing reliable HR. Results: The study is ongoing. The projected end date for data collection is around July 2024. Conclusions: The study will compare the novel patent-pending 3D-printed dry electrode?based HRD?s real-time HR estimation techniques with the state-of-the-art clinical-grade ECG or PO monitors for HR accuracy and examines how fast the HRD provides reliable HR. The study will further provide recommendations and important improvements that can be made to implement the HRD for clinical applications, especially in neonatal resuscitation efforts. This work can be seen as a stepping stone in the development of robust dry-electrode single-lead ECG devices for HR estimations in the pediatric population. International Registered Report Identifier (IRRID): DERR1-10.2196/45512 UR - https://www.researchprotocols.org/2023/1/e45512 UR - http://dx.doi.org/10.2196/45512 UR - http://www.ncbi.nlm.nih.gov/pubmed/37782528 ID - info:doi/10.2196/45512 ER - TY - JOUR AU - Yang, Li-Tan AU - Lee, Jen-Kuang AU - Tsai, Chieh-Mei AU - Chen, Ying-Hsien AU - Huang, Ching-Chang AU - Wu, Hui-Wen AU - Su, Chin-Hua AU - Lee, Chien-Chang AU - Hung, Chi-Sheng AU - Ho, Yi-Lwun PY - 2023/9/26 TI - Effect of Telehealth Services on Mitral and Tricuspid Regurgitation Progression: Retrospective Study JO - J Med Internet Res SP - e47947 VL - 25 KW - mitral regurgitation KW - tricuspid regurgitation KW - telehealth KW - telemedicine KW - point-of-care ultrasound KW - cardiovascular health KW - heart disease KW - cardiac KW - cardiology KW - patience care KW - patient-reported outcome KW - remote monitoring KW - health management N2 - Background: Mitral regurgitation (MR) and tricuspid regurgitation (TR) are common cardiac conditions with high mortality risks, which can be improved through early intervention. Telehealth services, which allow for remote monitoring of patient conditions, have been proven to improve the health management of chronic diseases, but the effects on MR and TR progression are unknown. Objective: This study aimed to explore whether patients receiving telehealth services have less MR and TR progression compared with a control group. We also aimed to identify the determinants of MR and TR progression. Methods: This single-center retrospective study conducted at the National Taiwan University Hospital compared MR and TR progression (defined as either progression to moderate or greater MR and TR or MR and TR progression by ?2 grades during the study period) between the telehealth and control groups. Patients had a minimum of 2 transthoracic echocardiograms at least 6 months apart; baseline mild-moderate MR and TR or lower; and no prior surgeries on the mitral or tricuspid valve. Telehealth patients were defined as those who received telehealth services for at least 28 days within 3 months of baseline. Basic demographics, baseline blood pressure measurements, prescribed medication, and Charlson Comorbidity Index components were obtained for all patients. Results: A total of 1081 patients (n=226 in the telehealth group and n=855 in the control group) were included in the study analyses. The telehealth group showed significantly lower baseline systolic blood pressure (P<.001), higher Charlson Comorbidity Index (P=.02), higher prevalence of prior myocardial infarction (P=.01) and heart failure (P<.001), higher beta-blocker (P=.03) and diuretic (P=.04) use, and lower nitrate use (P=.04). Both groups showed similar cardiac remodeling conditions at baseline. Telehealth was found to be neutral for both MR (hazard ratio 1.10, 95% CI 0.80-1.52; P=.52) and TR (hazard ratio 1.27, 95% CI 0.92-1.74; P=.14) progression. Determinants for moderate or greater MR progression included older age, female sex, diuretic use, larger left atrial dimension, left ventricular end-diastolic dimension, left ventricular end-systolic dimension, and lower left ventricular ejection fraction. Determinants of moderate or greater TR progression included older age, female sex, diuretic use, presence of atrial fibrillation, LA dimension, left ventricular end-systolic dimension, and lower left ventricular ejection fraction; statin use was found to be protective. Conclusions: This is the first study to assess the association between telehealth services and the progression of MR and TR. Telehealth patients, who had more comorbidities, displayed similar MR and TR progression versus control patients, indicating that telehealth may slow MR and TR progression. Determinants of MR and TR progression included easy-to-measure traditional echo parameters of cardiac function, older age, female sex, and atrial fibrillation, which can be incorporated into a telehealth platform and advanced alert system, improving patient outcomes through personalized care. UR - https://www.jmir.org/2023/1/e47947 UR - http://dx.doi.org/10.2196/47947 UR - http://www.ncbi.nlm.nih.gov/pubmed/37751276 ID - info:doi/10.2196/47947 ER - TY - JOUR AU - Li, Wenzhen AU - Chen, Dajie AU - Peng, Ying AU - Lu, Zuxun AU - Kwan, Mei-Po AU - Tse, Ah Lap PY - 2023/9/5 TI - Association Between Metabolic Syndrome and Mortality: Prospective Cohort Study JO - JMIR Public Health Surveill SP - e44073 VL - 9 KW - metabolic syndrome KW - mortality KW - heart disease KW - diabetes mellitus KW - cancer N2 - Background: Metabolic syndrome (MetS) is a common metabolic disorder that results from the increasing prevalence of obesity, which has been an increasing concern in recent years. Previous evidence indicated that MetS was associated with mortality; however, different definitions of MetS were used. In 2005, the National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III updated the definition of MetS, which has since been widely adopted. Therefore, it is necessary to conduct a novel study among other populations and countries with a larger sample size using the updated definition of MetS and death code to examine the association of MetS with all-cause and cause-specific mortality. Objective: We aimed to examine the associations of MetS with all-cause and cause-specific mortality. Methods: A total of 36,414 adults were included in this study, using data from the National Health and Nutrition Examination Survey (NHANES) III (1988-1994) and the continuous NHANES (1999-2014) in the United States. Death outcomes were ascertained by linkage to National Death Index records through December 31, 2015. MetS was defined by the NCEP ATP III-2005 criterion. Complex survey design factors including sample weights, clustering, and stratification were considered for all analyses with instructions for using NHANES data. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs for mortality from all causes, heart disease, diabetes, and cancer. Results: We observed 8494 deaths during the 16.71 years of follow-up. Compared with those without MetS, individuals with MetS were associated with a significantly elevated multiadjusted HR of 1.24 (95% CI 1.16-1.33), 1.44 (95% CI 1.25-1.66), and 5.15 (95% CI 3.15-8.43) for all cause, heart diseases, and diabetes mellitus, respectively, whereas no significant association was found for cancer mortality (HR 1.17, 95% CI 0.95-1.43). Conclusions: Our study provides additional evidence that MetS and its components are significantly associated with all-cause, heart disease, and diabetes mortality, but not with cancer mortality. Health care professionals should pay more attention to MetS and its individual component. UR - https://publichealth.jmir.org/2023/1/e44073 UR - http://dx.doi.org/10.2196/44073 UR - http://www.ncbi.nlm.nih.gov/pubmed/37669100 ID - info:doi/10.2196/44073 ER - TY - JOUR AU - Molina-Luque, Rafael AU - Molina-Recio, Guillermo AU - de-Pedro?Jiménez, Domingo AU - Álvarez Fernández, Carlos AU - García?Rodríguez, María AU - Romero-Saldaña, Manuel PY - 2023/9/5 TI - The Impact of Metabolic Syndrome Risk Factors on Lung Function Impairment: Cross-Sectional Study JO - JMIR Public Health Surveill SP - e43737 VL - 9 KW - cardiometabolic risk factor KW - lung function KW - metabolic syndrome KW - restrictive lung disease KW - spirometry N2 - Background: Metabolic syndrome (MetS) is a constellation of risk factors increasingly present in the world?s population. People with this syndrome are at an increased risk of cardiovascular disease and type 2 diabetes mellitus. Moreover, evidence has shown that it affects different organs. MetS and its risk factors are independently associated with impaired lung function, which can be quantified through spirometric variables. Objective: This study aims to determine whether a high number of MetS criteria is associated with increased lung function decline. Methods: We conducted a descriptive cross-sectional study with a random sample of 1980 workers. Workers with acute respiratory pathology (eg, influenza), chronic respiratory pathology (eg, chronic bronchitis), or exposure to substances harmful to the lungs (eg, organic and inorganic dust) were not included. MetS was established based on harmonized criteria, and lung function was assessed according to spirometric variables. On the basis of these, classification into restrictive lung disease (RLD), obstructive lung disease, and mixed lung disease (MLD) was performed. In addition, the association between MetS and lung function was established based on analysis of covariance, linear trend analysis, and multiple linear regression. Results: MetS was associated with worse lung function according to all the spirometric parameters analyzed (percentage of predicted forced expiratory volume in 1 second: mean 83, SD 13.8 vs mean 89.2, SD 12.8; P<.001 and percentage of predicted forced vital capacity: mean 85.9, SD 11.6 vs mean 92, SD 11.3; P<.001). Moreover, those diagnosed with MetS had a higher prevalence of lung dysfunction (41% vs 21.9%; P<.001), RLD (23.4% vs 11.2%; P<.001), and MLD (7.3% vs 2.2%; P<.001). Furthermore, an increasing number of MetS criteria was associated with a greater impairment of pulmonary mechanics (P<.001). Similarly, with an increasing number of MetS criteria, there was a significant linear trend (P<.001) in the growth of the prevalence ratio of RLD (0 criteria: 1, 1: 1.46, 2: 1.52, 3: 2.53, 4: 2.97, and 5: 5.34) and MLD (0 criteria: 1, 1: 2.68, 2: 6.18, 3: 9.69, and 4: 11.37). Regression analysis showed that the alteration of all MetS risk factors, adjusted for various explanatory variables, was significantly associated with a worsening of spirometric parameters, except for forced expiratory volume in 1 second/forced vital capacity. Conclusions: The findings have shown that an increase in cardiometabolic risk factors is associated with a more significant worsening of spirometric variables and a higher prevalence of RLD and MLD. As spirometry could be a crucial tool for monitoring patients at risk of developing chronic pathologies, we conclude that this inexpensive and easily accessible test could help detect changes in lung function in patients with cardiometabolic disorders. This highlights the need to consider the importance of cardiometabolic health in lung function when formulating public health policies. UR - https://publichealth.jmir.org/2023/1/e43737 UR - http://dx.doi.org/10.2196/43737 UR - http://www.ncbi.nlm.nih.gov/pubmed/37669095 ID - info:doi/10.2196/43737 ER - TY - JOUR AU - Stremmel, Christopher AU - Breitschwerdt, Rüdiger PY - 2023/8/30 TI - Digital Transformation in the Diagnostics and Therapy of Cardiovascular Diseases: Comprehensive Literature Review JO - JMIR Cardio SP - e44983 VL - 7 KW - cardiovascular KW - digital medicine KW - telehealth KW - artificial intelligence KW - telemedicine KW - mobile phone KW - review N2 - Background: The digital transformation of our health care system has experienced a clear shift in the last few years due to political, medical, and technical innovations and reorganization. In particular, the cardiovascular field has undergone a significant change, with new broad perspectives in terms of optimized treatment strategies for patients nowadays. Objective: After a short historical introduction, this comprehensive literature review aimed to provide a detailed overview of the scientific evidence regarding digitalization in the diagnostics and therapy of cardiovascular diseases (CVDs). Methods: We performed an extensive literature search of the PubMed database and included all related articles that were published as of March 2022. Of the 3021 studies identified, 1639 (54.25%) studies were selected for a structured analysis and presentation (original articles: n=1273, 77.67%; reviews or comments: n=366, 22.33%). In addition to studies on CVDs in general, 829 studies could be assigned to a specific CVD with a diagnostic and therapeutic approach. For data presentation, all 829 publications were grouped into 6 categories of CVDs. Results: Evidence-based innovations in the cardiovascular field cover a wide medical spectrum, starting from the diagnosis of congenital heart diseases or arrhythmias and overoptimized workflows in the emergency care setting of acute myocardial infarction to telemedical care for patients having chronic diseases such as heart failure, coronary artery disease, or hypertension. The use of smartphones and wearables as well as the integration of artificial intelligence provides important tools for location-independent medical care and the prevention of adverse events. Conclusions: Digital transformation has opened up multiple new perspectives in the cardiovascular field, with rapidly expanding scientific evidence. Beyond important improvements in terms of patient care, these innovations are also capable of reducing costs for our health care system. In the next few years, digital transformation will continue to revolutionize the field of cardiovascular medicine and broaden our medical and scientific horizons. UR - https://cardio.jmir.org/2023/1/e44983 UR - http://dx.doi.org/10.2196/44983 UR - http://www.ncbi.nlm.nih.gov/pubmed/37647103 ID - info:doi/10.2196/44983 ER - TY - JOUR AU - Wu, Justin AU - Napoleone, Jenna AU - Linke, Sarah AU - Noble, Madison AU - Turken, Michael AU - Rakotz, Michael AU - Kirley, Kate AU - Folk Akers, Jennie AU - Juusola, Jessie AU - Jasik, Bradner Carolyn PY - 2023/8/24 TI - Long-Term Results of a Digital Hypertension Self-Management Program: Retrospective Cohort Study JO - JMIR Cardio SP - e43489 VL - 7 KW - hypertension KW - digital health program KW - home measurement KW - self-management KW - behavior change N2 - Background: Digital health programs that incorporate frequent blood pressure (BP) self-monitoring and support for behavior change offer a scalable solution for hypertension management. Objective: We examined the impact of a digital hypertension self-management and lifestyle change support program on BP over 12 months. Methods: Data were analyzed from a retrospective observational cohort of commercially insured members (n=1117) that started the Omada for Hypertension program between January 1, 2019, and September 30, 2021. Paired t tests and linear regression were used to measure the changes in systolic blood pressure (SBP) over 12 months overall and by SBP control status at baseline (?130 mm Hg vs <130 mm Hg). Results: Members were on average 50.9 years old, 50.8% (n=567) of them were female, 60.5% (n=675) of them were White, and 70.5% (n=788) of them had uncontrolled SBP at baseline (?130 mm Hg). At 12 months, all members (including members with controlled and uncontrolled BP at baseline) and those with uncontrolled SBP at baseline experienced significant mean reductions in SBP (mean ?4.8 mm Hg, 95% CI ?5.6 to ?4.0; ?8.1 mm Hg, 95% CI ?9.0 to ?7.1, respectively; both P<.001). Members with uncontrolled SBP at baseline also had significant reductions in diastolic blood pressure (?4.7 mm Hg; 95% CI ?5.3 to ?4.1), weight (?6.5 lbs, 95% CI ?7.7 to ?5.3; 2.7% weight loss), and BMI (?1.1 kg/m2; 95% CI ?1.3 to ?0.9; all P<.001). Those with controlled SBP at baseline maintained within BP goal range. Additionally, 48% (418/860) of members with uncontrolled BP at baseline experienced enough change in BP to improve their BP category. Conclusions: This study provides real-world evidence that a comprehensive digital health program involving hypertension education, at-home BP monitoring, and behavior change coaching support was effective for self-managing hypertension over 12 months. UR - https://cardio.jmir.org/2023/1/e43489 UR - http://dx.doi.org/10.2196/43489 UR - http://www.ncbi.nlm.nih.gov/pubmed/37463311 ID - info:doi/10.2196/43489 ER - TY - JOUR AU - Park, Sangil AU - Woo, Geol Ho AU - Kim, Soeun AU - Kim, Sunyoung AU - Lim, Hyunjung AU - Yon, Keon Dong AU - Rhee, Youl Sang PY - 2023/8/21 TI - Real-World Evidence of a Hospital-Linked Digital Health App for the Control of Hypertension and Diabetes Mellitus in South Korea: Nationwide Multicenter Study JO - JMIR Form Res SP - e48332 VL - 7 KW - hypertension KW - blood pressure KW - diabetes KW - glucose KW - digital health technology KW - effectiveness KW - application KW - blood glucose KW - systolic KW - diastolic KW - management KW - consumer KW - cost KW - monitoring N2 - Background: Digital health care apps have been widely used for managing chronic conditions such as diabetes mellitus and hypertension, providing promising prospects for enhanced health care delivery, increased patient engagement, and improved self-management. However, the impact of integrating these apps within hospital systems for managing such conditions still lacks conclusive evidence. Objective: We aimed to investigate the real-world effectiveness of using hospital-linked digital health care apps in lowering blood pressure (BP) and blood glucose levels in patients with hypertension and diabetes mellitus. Methods: Nationwide multicenter data on demographic characteristics and the use of a digital health care app from 233 hospitals were collected for participants aged 20 to 80 years in South Korea between August 2021 and June 2022. We divided the participants into 2 groups: 1 group consisted of individuals who exclusively used the digital health app (control) and the other group used the hospital-linked digital health app. All the patients participated in a 12-week digital health care intervention. We conducted a comparative analysis to assess the real-world effectiveness of the hospital-linked digital health app. The primary outcome was the differences in the systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG) level, and postprandial glucose (PPG) level between baseline and 12 weeks. Results: A total of 1029 participants were analyzed for the FBG level, 527 participants were analyzed for the PPG level, and 2029 participants for the SBP and DBP were enrolled. After 12 weeks, a hospital-linked digital health app was found to reduce SBP (?5.4 mm Hg, 95% CI ?7.0 to ?3.9) and DBP (?2.4 mm Hg, 95% CI ?3.4 to ?1.4) in participants without hypertension and FBG level in all participants (those without diabetes, ?4.4 mg/dL, 95% CI ?7.9 to ?1.0 and those with diabetes, ?3.2 mg/dL, 95% CI ?5.4 to ?1.0); however, there was no statistically significant difference compared to the control group (using only digital health app). Specifically, participants with diabetes using a hospital-linked digital health app demonstrated a significant decrease in PPG after 12 weeks (?10.9 mg/dL, 95% CI ?31.1 to ?5.3) compared to those using only a digital health app (P=.006). Conclusions: Hospital-linked digital interventions have greatly improved glucose control for diabetes compared with using digital health technology only. These hospital-linked digital health apps have the potential to offer consumers and health care professionals cost-effective support in decreasing glucose levels when used in conjunction with self-monitoring. UR - https://formative.jmir.org/2023/1/e48332 UR - http://dx.doi.org/10.2196/48332 UR - http://www.ncbi.nlm.nih.gov/pubmed/37603401 ID - info:doi/10.2196/48332 ER - TY - JOUR AU - Gurung, Sitaji AU - Simpson, N. Kit AU - Grov, Christian AU - Rendina, Jonathon H. AU - Huang, K. Terry T. AU - Budhwani, Henna AU - Jones, Scott Stephen AU - Dark, Tyra AU - Naar, Sylvie PY - 2023/8/16 TI - Cardiovascular Risk Assessment Among Adolescents and Youths Living With HIV: Evaluation of Electronic Health Record Findings and Implications JO - Interact J Med Res SP - e41574 VL - 12 KW - cardiovascular risk KW - cluster of differentiation 4 lymphocyte KW - electronic health record KW - viral load KW - youths living with HIV N2 - Background: The HIV epidemic remains a major public health concern, particularly among youths living with HIV. While the availability of antiretroviral therapy has significantly improved the health outcomes of people living with HIV, there is growing evidence that youths living with HIV may be at increased risk of cardiovascular disease. However, the underlying mechanisms linking HIV and cardiovascular disease among youths living with HIV remain poorly understood. One potential explanation is that HIV-related biomarkers, including detectable viral load (VL) and low cluster of differentiation 4 (CD4) lymphocyte counts, may contribute to increased cardiovascular risk. Despite the potential importance of these biomarkers, the relationship between HIV-related biomarkers and cardiovascular risk among youths living with HIV has been understudied. Objective: To address this gap, we examined whether detectable VL and low CD4 lymphocyte counts, both of which are indications of unsuppressed HIV, were associated with cardiovascular risk among youths living with HIV. Methods: We analyzed electronic health record data from 7 adolescent HIV clinics in the United States (813 youths living with HIV). We used multivariable linear regression to examine the relationship between detectable VL and CD4 lymphocyte counts of ?200 and cardiovascular risk scores, which were adapted from the gender-specific Framingham algorithm. Results: In our study, nearly half of the participants (366/766, 47.8%) had detectable VL, indicating unsuppressed HIV, while 8.6% (51/593) of them had CD4 lymphocyte counts of ?200, suggesting weakened immune function. We found that those with CD4 lymphocyte counts of ?200 had significantly higher cardiovascular risk, as assessed by Cardiac Risk Score2, than those with CD4 lymphocyte counts of >200 (P=.002). After adjusting for demographic and clinical factors, we found that for every 1000-point increase in VL copies/mL, the probability of having cardiovascular risk (Cardiac Risk Score2) increased by 38%. When measuring the strength of this connection, we observed a minor effect of VL on increased cardiovascular risk (?=.134, SE 0.014; P=.006). We obtained similar results with Cardiac Risk Score1, but the effect of CD4 lymphocyte counts of ?200 was no longer significant. Overall, our findings suggest that detectable VL is associated with increased cardiovascular risk among youths living with HIV, and that CD4 lymphocyte counts may play a role in this relationship as well. Conclusions: Our study highlights a significant association between unsuppressed HIV, indicated by detectable VL, and increased cardiovascular risk in youths living with HIV. These findings emphasize the importance of implementing interventions that address both VL suppression and cardiovascular risk reduction in this population. By tailoring interventions to meet the unique needs of youths, we can promote overall well-being throughout the HIV care continuum and across the life span. Ultimately, these efforts have the potential to improve the health outcomes and quality of life of youths living with HIV. International Registered Report Identifier (IRRID): RR2-10.2196/11185 UR - https://www.i-jmr.org/2023/1/e41574 UR - http://dx.doi.org/10.2196/41574 UR - http://www.ncbi.nlm.nih.gov/pubmed/37585242 ID - info:doi/10.2196/41574 ER - TY - JOUR AU - Newport, Rochelle AU - Grey, Corina AU - Dicker, Bridget AU - Ameratunga, Shanthi AU - Harwood, Matire PY - 2023/7/12 TI - Reasons for Ethnic Disparities in the Prehospital Care Pathway Following an Out-of-Hospital Cardiac Event: Protocol of a Systematic Review JO - JMIR Res Protoc SP - e40557 VL - 12 KW - health equity KW - ethnicity KW - Indigenous peoples KW - out-of-hospital cardiac arrest KW - emergency responders KW - health care KW - patient care KW - cardiovascular KW - cardiology N2 - Background: Substantial inequities in cardiovascular disease occur between and within countries, driving much of the current burden of global health inequities. Despite well-established treatment protocols and clinical interventions, the extent to which the prehospital care pathway for people who have experienced an out-of-hospital cardiac event (OHCE) varies by ethnicity and race is inconsistently documented. Timely access to care in this context is important for good outcomes. Therefore, identifying any barriers and enablers that influence timely prehospital care can inform equity-focused interventions. Objective: This systematic review aims to answer the question: Among adults who experience an OHCE, to what extent and why might the care pathways in the community and outcomes differ for minoritized ethnic populations compared to nonminoritized populations? In addition, we will investigate the barriers and enablers that could influence variations in the access to care for minoritized ethnic populations. Methods: This review will use Kaupapa M?ori theory to underpin the process and analysis, thus prioritizing Indigenous knowledge and experiences. A comprehensive search of the CINAHL, Embase, MEDLINE (OVID), PubMed, Scopus, Google Scholar, and Cochrane Library databases will be done using Medical Subject Headings terms themed to the 3 domains of context, health condition, and setting. All identified articles will be managed using an Endnote library. To be included in the research, papers must be published in English; have adult study populations; have an acute, nontraumatic cardiac condition as the primary health condition of interest; and be in the prehospital setting. Studies must also include comparisons by ethnicity or race to be eligible. Those studies considered suitable for inclusion will be critically appraised by multiple authors using the Mixed Methods Appraisal Tool and CONSIDER (Consolidated Criteria for Strengthening the Reporting of Health Research Involving Indigenous Peoples) framework. Risk of bias will be assessed using the Graphic Appraisal Tool for Epidemiology. Disagreements on inclusion or exclusion will be settled by a discussion with all reviewers. Data extraction will be done independently by 2 authors and collated in a Microsoft Excel spreadsheet. The outcomes of interest will include (1) symptom recognition, (2) patient decision-making, (3) health care professional decision-making, (4) the provision of cardiopulmonary resuscitation, (5) access to automated external defibrillator, and (6) witnessed status. Data will be extracted and categorized under key domains. A narrative review of these domains will be conducted using Indigenous data sovereignty approaches as a guide. Findings will be reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Results: Our research is in progress. We anticipate the systematic review will be completed and submitted for publication in October 2023. Conclusions: The review findings will inform researchers and health care professionals on the experience of minoritized populations when accessing the OHCE care pathway. Trial Registration: PROSPERO CRD42022279082; https://tinyurl.com/bdf6s4h2 International Registered Report Identifier (IRRID): PRR1-10.2196/40557 UR - https://www.researchprotocols.org/2023/1/e40557 UR - http://dx.doi.org/10.2196/40557 UR - http://www.ncbi.nlm.nih.gov/pubmed/37436809 ID - info:doi/10.2196/40557 ER - TY - JOUR AU - Yoo, Hun Kyung AU - Cho, Yongil AU - Oh, Jaehoon AU - Lee, Juncheol AU - Ko, Sung Byuk AU - Kang, Hyunggoo AU - Lim, Ho Tae AU - Lee, Hwan Sang PY - 2023/7/11 TI - Association of Socioeconomic Status With Long-Term Outcome in Survivors After Out-of-Hospital Cardiac Arrest: Nationwide Population-Based Longitudinal Study JO - JMIR Public Health Surveill SP - e47156 VL - 9 KW - out-of-hospital cardiac arrest KW - OHCA KW - socioeconomic status KW - SES KW - long-term outcome KW - survivor KW - public health KW - cardiac arrest KW - socioeconomic disparities KW - hospital discharge KW - clinical outcomes N2 - Background: Out-of-hospital cardiac arrest (OHCA) is a major public health problem and a leading cause of death worldwide. Previous studies have focused on improving the survival of people who have had OHCA by analyzing short-term survival outcomes, such as the return of spontaneous circulation, 30-day survival, and survival to discharge. Research has been conducted on prehospital prognostic factors to improve the survival of patients with OHCA, among which the association between socioeconomic status (SES) and survival has been reported. SES could affect bystander cardiopulmonary resuscitation rates and whether OHCA is witnessed, and low cardiopulmonary resuscitation education rates are associated with low SES. It has been reported that areas with high SES have shorter hospital transfer times and more public defibrillators per person. Previous studies have shown the impact of SES disparities on the short-term survival of patients with OHCA. However, understanding the impact of SES on the long-term prognosis of OHCA survivors remains limited. As long-term outcomes are more indicative of a patient?s ongoing health care needs and the burden on public health than short-term outcomes, understanding the long-term prognosis of OHCA survivors is important. Objective: This study aimed to identify whether SES influenced the long-term outcomes of OHCA. Methods: Using health claims data obtained from the National Health Insurance (NHI) service in Korea, we included OHCA survivors who were hospitalized between January 2005 and December 2015. The patients were divided into 2 groups: NHI and Medical Aid (MA) groups, with the MA group defined as having a low SES. Cumulative mortality was estimated using the Kaplan-Meier method, and a Cox proportional hazards model was used to evaluate the impact of SES on long-term mortality. A subgroup analysis was performed based on whether cardiac procedures were performed. Results: We followed 4873 OHCA survivors for up to 14 years (median of 3.3 years). The Kaplan-Meier survival curve showed that the MA group had a significantly decreased long-term survival rate compared to the NHI group. With an adjusted hazard ratio (aHR) of 1.52 (95% CI 1.35-1.72), low SES was associated with increased long-term mortality. The overall mortality rate of the patients who underwent cardiac procedures in the MA group was significantly higher than that of the NHI group (aHR 1.72, 95% CI 1.05-2.82). The overall mortality rate of patients without cardiac procedures was also increased in the MA group compared to the NHI group (aHR 1.39, 95% CI 1.23-1.58). Conclusions: OHCA survivors with low SES had an increased risk of poor long-term outcomes compared with those with higher SES. OHCA survivors with low SES who have undergone cardiac procedures need considerable care for long-term survival. UR - https://publichealth.jmir.org/2023/1/e47156 UR - http://dx.doi.org/10.2196/47156 UR - http://www.ncbi.nlm.nih.gov/pubmed/37432716 ID - info:doi/10.2196/47156 ER - TY - JOUR AU - Zaman, Sameer AU - Padayachee, Yorissa AU - Shah, Moulesh AU - Samways, Jack AU - Auton, Alice AU - Quaife, M. Nicholas AU - Sweeney, Mark AU - Howard, P. James AU - Tenorio, Indira AU - Bachtiger, Patrik AU - Kamalati, Tahereh AU - Pabari, A. Punam AU - Linton, F. Nick W. AU - Mayet, Jamil AU - Peters, S. Nicholas AU - Barton, Carys AU - Cole, D. Graham AU - Plymen, M. Carla PY - 2023/6/23 TI - Smartphone-Based Remote Monitoring in Heart Failure With Reduced Ejection Fraction: Retrospective Cohort Study of Secondary Care Use and Costs JO - JMIR Cardio SP - e45611 VL - 7 KW - heart failure KW - remote monitoring KW - smartphone care KW - telemonitoring KW - self-management KW - admission prevention KW - cohort study KW - hospitalization KW - noninvasive KW - smartphone KW - vital signs KW - diagnosis N2 - Background: Despite effective therapies, the economic burden of heart failure with reduced ejection fraction (HFrEF) is driven by frequent hospitalizations. Treatment optimization and admission avoidance rely on frequent symptom reviews and monitoring of vital signs. Remote monitoring (RM) aims to prevent admissions by facilitating early intervention, but the impact of noninvasive, smartphone-based RM of vital signs on secondary health care use and costs in the months after a new diagnosis of HFrEF is unknown. Objective: The purpose of this study is to conduct a secondary care health use and health-economic evaluation for patients with HFrEF using smartphone-based noninvasive RM and compare it with matched controls receiving usual care without RM. Methods: We conducted a retrospective study of 2 cohorts of newly diagnosed HFrEF patients, matched 1:1 for demographics, socioeconomic status, comorbidities, and HFrEF severity. They are (1) the RM group, with patients using the RM platform for >3 months and (2) the control group, with patients referred before RM was available who received usual heart failure care without RM. Emergency department (ED) attendance, hospital admissions, outpatient use, and the associated costs of this secondary care activity were extracted from the Discover data set for a 3-month period after diagnosis. Platform costs were added for the RM group. Secondary health care use and costs were analyzed using Kaplan-Meier event analysis and Cox proportional hazards modeling. Results: A total of 146 patients (mean age 63 years; 42/146, 29% female) were included (73 in each group). The groups were well-matched for all baseline characteristics except hypertension (P=.03). RM was associated with a lower hazard of ED attendance (hazard ratio [HR] 0.43; P=.02) and unplanned admissions (HR 0.26; P=.02). There were no differences in elective admissions (HR 1.03, P=.96) or outpatient use (HR 1.40; P=.18) between the 2 groups. These differences were sustained by a univariate model controlling for hypertension. Over a 3-month period, secondary health care costs were approximately 4-fold lower in the RM group than the control group, despite the additional cost of RM itself (mean cost per patient GBP £465, US $581 vs GBP £1850, US $2313, respectively; P=.04). Conclusions: This retrospective cohort study shows that smartphone-based RM of vital signs is feasible for HFrEF. This type of RM was associated with an approximately 2-fold reduction in ED attendance and a 4-fold reduction in emergency admissions over just 3 months after a new diagnosis with HFrEF. Costs were significantly lower in the RM group without increasing outpatient demand. This type of RM could be adjunctive to standard care to reduce admissions, enabling other resources to help patients unable to use RM. UR - https://cardio.jmir.org/2023/1/e45611 UR - http://dx.doi.org/10.2196/45611 UR - http://www.ncbi.nlm.nih.gov/pubmed/37351921 ID - info:doi/10.2196/45611 ER - TY - JOUR AU - Killian, O. Michael AU - Tian, Shubo AU - Xing, Aiwen AU - Hughes, Dana AU - Gupta, Dipankar AU - Wang, Xiaoyu AU - He, Zhe PY - 2023/6/20 TI - Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches JO - JMIR Cardio SP - e45352 VL - 7 KW - explainable artificial intelligence KW - machine learning KW - mortality KW - outcome prediction KW - organ rejection KW - organ transplantation KW - pediatrics KW - United Network for Organ Sharing N2 - Background: The prediction of posttransplant health outcomes for pediatric heart transplantation is critical for risk stratification and high-quality posttransplant care. Objective: The purpose of this study was to examine the use of machine learning (ML) models to predict rejection and mortality for pediatric heart transplant recipients. Methods: Various ML models were used to predict rejection and mortality at 1, 3, and 5 years after transplantation in pediatric heart transplant recipients using United Network for Organ Sharing data from 1987 to 2019. The variables used for predicting posttransplant outcomes included donor and recipient as well as medical and social factors. We evaluated 7 ML models?extreme gradient boosting (XGBoost), logistic regression, support vector machine, random forest (RF), stochastic gradient descent, multilayer perceptron, and adaptive boosting (AdaBoost)?as well as a deep learning model with 2 hidden layers with 100 neurons and a rectified linear unit (ReLU) activation function followed by batch normalization for each and a classification head with a softmax activation function. We used 10-fold cross-validation to evaluate model performance. Shapley additive explanations (SHAP) values were calculated to estimate the importance of each variable for prediction. Results: RF and AdaBoost models were the best-performing algorithms for different prediction windows across outcomes. RF outperformed other ML algorithms in predicting 5 of the 6 outcomes (area under the receiver operating characteristic curve [AUROC] 0.664 and 0.706 for 1-year and 3-year rejection, respectively, and AUROC 0.697, 0.758, and 0.763 for 1-year, 3-year, and 5-year mortality, respectively). AdaBoost achieved the best performance for prediction of 5-year rejection (AUROC 0.705). Conclusions: This study demonstrates the comparative utility of ML approaches for modeling posttransplant health outcomes using registry data. ML approaches can identify unique risk factors and their complex relationship with outcomes, thereby identifying patients considered to be at risk and informing the transplant community about the potential of these innovative approaches to improve pediatric care after heart transplantation. Future studies are required to translate the information derived from prediction models to optimize counseling, clinical care, and decision-making within pediatric organ transplant centers. UR - https://cardio.jmir.org/2023/1/e45352 UR - http://dx.doi.org/10.2196/45352 UR - http://www.ncbi.nlm.nih.gov/pubmed/37338974 ID - info:doi/10.2196/45352 ER - TY - JOUR AU - Mekhael, Mario AU - Ho, Chan AU - Noujaim, Charbel AU - Assaf, Ala AU - Younes, Hadi AU - El Hajjar, Hadi Abdel AU - Chaudhry, A. Humza AU - Lanier, Brennan AU - Chouman, Nour AU - Makan, Noor AU - Shan, Botao AU - Zhang, Yichi AU - Dagher, Lilas AU - Kreidieh, Omar AU - Marrouche, Nassir AU - Donnellan, Eoin PY - 2023/4/5 TI - Compliance Challenges in a Longitudinal COVID-19 Cohort Using Wearables for Continuous Monitoring: Observational Study JO - J Med Internet Res SP - e43134 VL - 25 KW - COVID-19 KW - digital health KW - wearables KW - compliance KW - cardiovascular health KW - heart disease KW - wearable device KW - biometric KW - remote monitoring N2 - Background: The WEAICOR (Wearables to Investigate the Long Term Cardiovascular and Behavioral Impacts of COVID-19) study was a prospective observational study that used continuous monitoring to detect and analyze biometrics. Compliance to wearables was a major challenge when conducting the study and was crucial for the results. Objective: The aim of this study was to evaluate patients? compliance to wearable wristbands and determinants of compliance in a prospective COVID-19 cohort. Methods: The Biostrap (Biostrap USA LLC) wearable device was used to monitor participants? biometric data. Compliance was calculated by dividing the total number of days in which transmissions were sent by the total number of days spent in the WEAICOR study. Univariate correlation analyses were performed, with compliance and days spent in the study as dependent variables and age, BMI, sex, symptom severity, and the number of complications or comorbidities as independent variables. Multivariate linear regression was then performed, with days spent in the study as a dependent variable, to assess the power of different parameters in determining the number of days patients spent in the study. Results: A total of 122 patients were included in this study. Patients were on average aged 41.32 years, and 46 (38%) were female. Age was found to correlate with compliance (r=0.23; P=.01). In addition, age (r=0.30; P=.001), BMI (r=0.19; P=.03), and the severity of symptoms (r=0.19; P=.03) were found to correlate with days spent in the WEAICOR study. Per our multivariate analysis, in which days spent in the study was a dependent variable, only increased age was a significant determinant of compliance with wearables (adjusted R2=0.1; ?=1.6; P=.01). Conclusions: Compliance is a major obstacle in remote monitoring studies, and the reasons for a lack of compliance are multifactorial. Patient factors such as age, in addition to environmental factors, can affect compliance to wearables. UR - https://www.jmir.org/2023/1/e43134 UR - http://dx.doi.org/10.2196/43134 UR - http://www.ncbi.nlm.nih.gov/pubmed/36763647 ID - info:doi/10.2196/43134 ER - TY - JOUR AU - Zhu, Zhihui AU - Li, Yuehuan AU - Zhang, Fan AU - Steiger, Stefanie AU - Guo, Cheng AU - Liu, Nan AU - Lu, Jiakai AU - Fan, Guangpu AU - Wu, Wenbo AU - Wu, Mingying AU - Wang, Huaibin AU - Xu, Dong AU - Chen, Yu AU - Zhu, Junming AU - Meng, Xu AU - Hou, Xiaotong AU - Anders, Hans-Joachim AU - Ye, Jian AU - Zheng, Zhe AU - Li, Chenyu AU - Zhang, Haibo PY - 2023/3/23 TI - Prediction of Male Coronary Artery Bypass Grafting Outcomes Using Body Surface Area Weighted Left Ventricular End-diastolic Diameter: Multicenter Retrospective Cohort Study JO - Interact J Med Res SP - e45898 VL - 12 KW - body surface area KW - BSA KW - left ventricular end-diastolic diameter KW - LVEDD KW - coronary artery bypass grafting KW - CABG KW - outcomes N2 - Background: The presence of a high left ventricular end-diastolic diameter (LVEDD) has been linked to a less favorable outcome in patients undergoing coronary artery bypass grafting (CABG) procedures. However, by taking into consideration the reference of left ventricular size and volume measurements relative to the patient's body surface area (BSA), it has been suggested that the accuracy of the predicting outcomes may be improved. Objective: We propose that BSA weighted LVEDD (bLVEDD) is a more accurate predictor of outcomes in patients undergoing CABG compared to simply using LVEDD alone. Methods: This study was a comprehensive retrospective cohort study that was conducted across multiple medical centers. The inclusion criteria for this study were patients who were admitted for treatment between October 2016 and May 2021. Only elective surgery patients were included in the study, while those undergoing emergency surgery were not considered. All participants in the study received standard care, and their clinical data were collected through the institutional registry in accordance with the guidelines set forth by the Society of Thoracic Surgeons National Adult Cardiac Database. bLVEDD was defined as LVEDD divided by BSA. The primary outcome was in-hospital all-cause mortality (30 days), and the secondary outcomes were postoperative severe adverse events, including use of extracorporeal membrane oxygenation, multiorgan failure, use of intra-aortic balloon pump, postoperative stroke, and postoperative myocardial infarction. Results: In total, 9474 patients from 5 centers under the Chinese Cardiac Surgery Registry were eligible for analysis. We found that a high LVEDD was a negative factor for male patients? mortality (odds ratio 1.44, P<.001) and secondary outcomes. For female patients, LVEDD was associated with secondary outcomes but did not reach statistical differences for morality. bLVEDD showed a strong association with postsurgery mortality (odds ratio 2.70, P<.001), and secondary outcomes changed in parallel with bLVEDD in male patients. However, bLVEDD did not reach statistical differences when fitting either mortality or severer outcomes in female patients. In male patients, the categorical bLVEDD showed high power to predict mortality (area under the curve [AUC] 0.71, P<.001) while BSA (AUC 0.62) and LVEDD (AUC 0.64) both contributed to the risk of mortality but were not as significant as bLVEDD (P<.001). Conclusions: bLVEDD is an important predictor for male mortality in CABG, removing the bias of BSA and showing a strong capability to accurately predict mortality outcomes. Trial Registration: ClinicalTrials.gov NCT02400125; https://clinicaltrials.gov/ct2/show/NCT02400125 UR - https://www.i-jmr.org/2023/1/e45898 UR - http://dx.doi.org/10.2196/45898 UR - http://www.ncbi.nlm.nih.gov/pubmed/36951893 ID - info:doi/10.2196/45898 ER - TY - JOUR AU - Hadjidimitriou, Stelios AU - Pagourelias, Efstathios AU - Apostolidis, Georgios AU - Dimaridis, Ioannis AU - Charisis, Vasileios AU - Bakogiannis, Constantinos AU - Hadjileontiadis, Leontios AU - Vassilikos, Vassilios PY - 2023/3/13 TI - Clinical Validation of an Artificial Intelligence?Based Tool for Automatic Estimation of Left Ventricular Ejection Fraction and Strain in Echocardiography: Protocol for a Two-Phase Prospective Cohort Study JO - JMIR Res Protoc SP - e44650 VL - 12 KW - artificial intelligence KW - clinical validation KW - computer-aided diagnosis KW - echocardiography KW - ejection fraction KW - global longitudinal strain KW - left ventricle KW - prospective cohort design KW - ultrasound N2 - Background: Echocardiography (ECHO) is a type of ultrasonographic procedure for examining the cardiac function and morphology, with functional parameters of the left ventricle (LV), such as the ejection fraction (EF) and global longitudinal strain (GLS), being important indicators. Estimation of LV-EF and LV-GLS is performed either manually or semiautomatically by cardiologists and requires a nonnegligible amount of time, while estimation accuracy depends on scan quality and the clinician?s experience in ECHO, leading to considerable measurement variability. Objective: The aim of this study is to externally validate the clinical performance of a trained artificial intelligence (AI)?based tool that automatically estimates LV-EF and LV-GLS from transthoracic ECHO scans and to produce preliminary evidence regarding its utility. Methods: This is a prospective cohort study conducted in 2 phases. ECHO scans will be collected from 120 participants referred for ECHO examination based on routine clinical practice in the Hippokration General Hospital, Thessaloniki, Greece. During the first phase, 60 scans will be processed by 15 cardiologists of different experience levels and the AI-based tool to determine whether the latter is noninferior in LV-EF and LV-GLS estimation accuracy (primary outcomes) compared to cardiologists. Secondary outcomes include the time required for estimation and Bland-Altman plots and intraclass correlation coefficients to assess measurement reliability for both the AI and cardiologists. In the second phase, the rest of the scans will be examined by the same cardiologists with and without the AI-based tool to primarily evaluate whether the combination of the cardiologist and the tool is superior in terms of correctness of LV function diagnosis (normal or abnormal) to the cardiologist?s routine examination practice, accounting for the cardiologist?s level of ECHO experience. Secondary outcomes include time to diagnosis and the system usability scale score. Reference LV-EF and LV-GLS measurements and LV function diagnoses will be provided by a panel of 3 expert cardiologists. Results: Recruitment started in September 2022, and data collection is ongoing. The results of the first phase are expected to be available by summer 2023, while the study will conclude in May 2024, with the end of the second phase. Conclusions: This study will provide external evidence regarding the clinical performance and utility of the AI-based tool based on prospectively collected ECHO scans in the routine clinical setting, thus reflecting real-world clinical scenarios. The study protocol may be useful to investigators conducting similar research. International Registered Report Identifier (IRRID): DERR1-10.2196/44650 UR - https://www.researchprotocols.org/2023/1/e44650 UR - http://dx.doi.org/10.2196/44650 UR - http://www.ncbi.nlm.nih.gov/pubmed/36912875 ID - info:doi/10.2196/44650 ER - TY - JOUR AU - Prickett, R. Timothy C. AU - Pearson, F. John AU - Troughton, W. Richard AU - Kennedy, A. Martin AU - Espiner, A. Eric PY - 2023/1/11 TI - The Predictive Value of A, B, and C-Type Natriuretic Peptides in People at Risk of Heart Disease: Protocol for a Longitudinal Observational Study JO - JMIR Res Protoc SP - e37011 VL - 12 KW - Cardiovascular risk KW - arterial and LV elastance KW - polygenic risk scores KW - cGMP KW - bioactive and amino-terminal natriuretic peptide KW - heart disease KW - cardiovascular KW - middle age KW - risk KW - prediction KW - biomarkers KW - detection N2 - Background: Heart disease and stroke are major and often unheralded causes of serious morbidity and premature death in middle age. Early detection of those most at risk is an urgent unmet need for instituting preventative measures. In an earlier community study (Canterbury Health, Ageing and Life Course [CHALICE]) of healthy people aged 50 years, contrary to previous reports, low levels of the heart hormone B-type natriuretic peptide (BNP) were associated with reduced measures of heart function and higher markers of vascular risk. A specific gene variant (rs198358) was found to be an independent contributor to higher BNP levels. A closely related vascular hormone (C-type natriuretic peptide [CNP]) showed opposite associations?higher levels were correlated with higher vascular risk and reduced cardiac function. To determine whether these novel findings predict serious heart or vascular disease in later life, this proposal re-examines the same CHALICE participants 15 years later. Objective: The primary objective is to determine the predictive value of (1) low plasma concentrations of the circulating cardiac hormones (atrial natriuretic peptide [ANP] and BNP) and (2) high levels of the vascular hormone CNP at age 50 years in detecting impaired cardiac and vascular function 15 years later. Secondary objectives are to determine specific associations of individual analytes (ANP, BNP, CNP, cyclic guanosine monophosphate [cGMP]) with echo-derived changes in cardiac performance at ages 50 years and 65 years. Methods: All of the 348 participants (205/348, 58.9% female; 53/348, 15.2% M?ori or Pacifica ethnicity) participating in the original CHALICE study?free of history of heart or renal disease at age 50 years and who consented to further study?will be contacted, recruited, and restudied as previously described. Data will include intervening health history, physical examination, heart function (speckle-tracking echocardiography), vascular status (carotid intimal thickness), and genetic status (genome-wide genotyping). Laboratory measures will include fasting blood sampling and routine biochemistry, ANP, BNP, CNP, their downstream effector (cGMP), and their bio-inactive products. Humoral metabolic-cardiovascular risk factors will be measured after an overnight fast. Primary outcomes will be analyzed using multiple linear regression. Results: The study will commence in 2022 and be completed in 2024. Conclusions: Proving our hypothesis?that low BNP and high CNP at any age in healthy people predict premature aging of heart and blood vessels, respectively?opens the way to early detection and improved outcomes for those most at risk. Confirmation of our hypotheses would improve current methods of screening and, in appropriate cases, enable interventions aimed at increasing natriuretic hormones and reducing risk of serious cardiovascular complications using drugs already available. Such advances in detection, and from interventional corrections, have the potential to not only improve health in the community but also reduce the high costs inevitably associated with heart failure. International Registered Report Identifier (IRRID): PRR1-10.2196/37011 UR - https://www.researchprotocols.org/2023/1/e37011 UR - http://dx.doi.org/10.2196/37011 UR - http://www.ncbi.nlm.nih.gov/pubmed/36630163 ID - info:doi/10.2196/37011 ER - TY - JOUR AU - Rebelo, Artur AU - Ronellenfitsch, Ulrich AU - Partsakhashvili, Jumber AU - John, Endres AU - Sekulla, Carsten AU - Krug, Sebastian AU - Rosendahl, Jonas AU - Michl, Patrick AU - Ukkat, Jörg AU - Kleeff, Jörg PY - 2022/12/13 TI - Postoperative Sigmoidoscopy and Biopsy After Elective Endovascular and Open Aortic Surgery for Preventing Mortality by Colonic Ischemia (PSB-Aorta-CI): Protocol for a Prospective Study JO - JMIR Res Protoc SP - e39071 VL - 11 IS - 12 KW - aortic KW - colonic KW - ischemia KW - surgery KW - vascular KW - cardiology KW - heart disease KW - patient treatment KW - clinical decision KW - health safety KW - risk assessment N2 - Background: Endovascular aortic repair is considered the standard procedure in treating patients diagnosed with pathologies of the abdominal aorta with suitable anatomy. Open surgery remains an option mostly for patients not suitable for endovascular surgery. Colonic ischemia is an important and life-threatening postoperative complication of these procedures. Objective: The aim of this study is to evaluate the clinical value and safety of performing a planned sigmoidoscopy and biopsy for detection of colonic ischemia in patients undergoing elective aortic surgery. We also aim to develop prediction scores which could identify patients at risk for colonic ischemia and facilitate their timely treatment. Methods: The trial is designed as a prospective study. The decision for aortic surgery and eligibility for these procedures will be ascertained according to current guidelines. Afterward, screening of the patient for the remaining inclusion and exclusion criteria will occur. If eligibility for study inclusion is confirmed, the patient will be informed about the aims of the study and all study-specific procedures (sigmoidoscopy and biopsy) and asked to provide informed consent. Results: The primary end point is the proportion of patients diagnosed endoscopically with subclinical and clinically relevant colonic ischemia among all patients undergoing aortic surgery. Patient recruitment started on June 2021. The final patient is expected to be treated by the end of June 2023. Institutional Review Board review has been completed at the University of Halle (Saale; reference #052-2021). Conclusions: this shows that sigmoidoscopy can be performed safely and is effective for the timely diagnosis of colonic ischemia in these patients, this could result in its routine implementation in both elective and emergency settings. Trial Registration: German Clinical Trials Register DRKS00025587; https://www.drks.de/drks_web/navigate.do?navigationId =trial.HTML&TRIAL_ID=DRKS00025587 International Registered Report Identifier (IRRID): DERR1-10.2196/39071 UR - https://www.researchprotocols.org/2022/12/e39071 UR - http://dx.doi.org/10.2196/39071 UR - http://www.ncbi.nlm.nih.gov/pubmed/36512391 ID - info:doi/10.2196/39071 ER - TY - JOUR AU - Sharifiheris, Zahra AU - Rahmani, Amir AU - Onwuka, Joseph AU - Bender, Miriam PY - 2022/11/17 TI - The Utilization of Heart Rate Variability for Autonomic Nervous System Assessment in Healthy Pregnant Women: Systematic Review JO - JMIR Bioinform Biotech SP - e36791 VL - 3 IS - 1 KW - heart rate variability KW - pregnancy KW - systematic review KW - autonomic nervous system assessment N2 - Background: The autonomic nervous system (ANS) plays a central role in pregnancy-induced adaptations, and failure in the required adaptations is associated with adverse neonatal and maternal outcomes. Mapping maternal ANS function in healthy pregnancy may help to understand ANS function. Objective: This study aimed to systematically review studies on the use of heart rate variability (HRV) monitoring to measure ANS function during pregnancy and determine whether specific HRV patterns representing normal ANS function have been identified during pregnancy. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was used to guide the systematic review. The CINAHL, PubMed, SCOPUS, and Web of Science databases were searched to comprehensively identify articles without a time span limitation. Studies were included if they assessed HRV in healthy pregnant individuals at least once during pregnancy or labor, with or without a comparison group (eg, complicated pregnancy). Quality assessment of the included literature was performed using the National Heart, Lung, and Blood Institute (NHLBI) tool. A narrative synthesis approach was used for data extraction and analysis, as the articles were heterogenous in scope, approaches, methods, and variables assessed, which precluded traditional meta-analysis approaches being used. Results: After full screening, 8 studies met the inclusion criteria. In 88% (7/8) of the studies, HRV was measured using electrocardiogram and operationalized in 3 different ways: linear frequency domain (FD), linear time domain (TD), and nonlinear methods. FD was measured in all (8/8), TD in 75% (6/8), and nonlinear methods in 25% (2/8) of the studies. The assessment duration varied from 5 minutes to 24 hours. TD indexes and most of the FD indexes decreased from the first to the third trimesters in the majority (5/7, 71%) of the studies. Of the FD indexes, low frequency (LF [nu]) and the LF/high frequency (HF) ratio showed an ascending trend from early to late pregnancy, indicating an increase in sympathetic activity toward the end of the pregnancy. Conclusions: We identified 3 HRV operationalization methods along with potentially indicative HRV patterns. However, we found no justification for the selection of measurement tools, measurement time frames, and operationalization methods, which threaten the generalizability and reliability of pattern findings. More research is needed to determine the criteria and methods for determining HRV patterns corresponding to ANS functioning in healthy pregnant persons. UR - https://bioinform.jmir.org/2022/1/e36791 UR - http://dx.doi.org/10.2196/36791 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/36791 ER - TY - JOUR AU - Yoo, Suyoung AU - Chang, Hansol AU - kim, Taerim AU - yoon, Hee AU - Hwang, Yeon Sung AU - Shin, Gun Tae AU - Sim, Seob Min AU - Jo, joon Ik AU - Choi, Jin-Ho AU - Cha, Chul Won PY - 2022/9/13 TI - Intervention in the Timeliness of Two Electrocardiography Types for Patients in the Emergency Department With Chest Pain: Randomized Controlled Trial JO - Interact J Med Res SP - e36335 VL - 11 IS - 2 KW - imaging KW - electrocardiography KW - wireless technology KW - emergency department KW - emergency KW - angina KW - ECG KW - EKG KW - cardiology KW - chest KW - pain KW - electrocardiogram KW - randomized KW - randomization KW - heart KW - cardiac KW - diagnose KW - diagnosis KW - accuracy N2 - Background: In the emergency department (ED), the result obtained using the 12-lead electrocardiography (ECG) is the basis for diagnosing and treating patients with chest pain. It was found that performing ECG at the appropriate time could improve treatment outcomes. Hence, a wearable ECG device with a timer can ensure that the findings are continuously recorded. Objective: We aimed to compare the time accuracy of a single-patch 12-lead ECG (SP-ECG) with that of conventional ECG (C-ECG). We hypothesized that SP-ECG would result in better time accuracy. Methods: Adult patients who visited the emergency room with chest pain but were not in shock were randomly assigned to one of the following 2 groups: the SP-ECG group or the C-ECG group. The final analysis included 33 (92%) of the 36 patients recruited. The primary outcome was the comparison of the time taken by the 2 groups to record the ECG. The average ages of the participants in the SP-ECG and C-ECG groups were 63.7 (SD 18.4) and 58.1 (SD 12.4) years, respectively. Results: With a power of 0.95 and effect sizes of 0.05 and 1.36, the minimum number of samples was calculated. The minimum sample size for each SP-ECG and C-ECG group is 15.36 participants, assuming a 20% dropout rate. As a result, 36 patients with chest pain participated, and 33 of them were analyzed. The timeliness of SP-ECG and C-ECG for the first follow-up ECG was 87.5% and 47.0%, respectively (P=.74). It was 75.0% and 35.2% at the second follow-up, respectively (P=.71). Conclusions: Continuous ECG monitoring with minimal interference from other examinations is feasible and essential in complex ED situations. However, the precision of SP-ECG has not yet been proved. Nevertheless, the application of SP-ECG is expected to improve overcrowding and human resource shortages in EDs, though more research is needed. Trial Registration: ClinicalTrials.gov NCT04114760; https://clinicaltrials.gov/ct2/show/NCT04114760 UR - https://www.i-jmr.org/2022/2/e36335 UR - http://dx.doi.org/10.2196/36335 UR - http://www.ncbi.nlm.nih.gov/pubmed/36099010 ID - info:doi/10.2196/36335 ER - TY - JOUR AU - Abid, Leila AU - Hammami, Rania AU - Abdesselem, Salem AU - Boudiche, Selim AU - Hédi, Slima Ben AU - Sayahi, Khaled AU - Bahloul, Amine AU - Chamtouri, Ikram AU - Charfeddine, Salma AU - Rais, Lamia AU - Drissa, Meriem AU - Ben Kaab, Badreddine AU - Ibn hadj amor, Hassen AU - Ben Fatma, Lilia AU - Garbaa, Riadh AU - Boukhris, Sabrine AU - Emna, Allouche AU - Ben Halima, Manel AU - Amdouni, Nesrine AU - Ghorbel, Shayma AU - Soudani, Sabrine AU - Khaled, Imen AU - Triki, Syrine AU - Bouazizi, Feten AU - Jemai, Imen AU - Abdeljalil, Ouday AU - Ammar, Yemna AU - Farah, Amani AU - Neji, Adnen AU - Oumaya, Zeineb AU - Seghaier, Sana AU - Mokrani, Samir AU - Thawaba, Hamza AU - Sarray, Hela AU - Ouaghlani, Khalil AU - Thabet, Houssem AU - Mnif, Zeineb AU - Fatma, Masmoudi Boujelben AU - Sghaier, Mohamed AU - Khalifa, Roueida AU - Fourati, Sami AU - Kammoun, Yassmine AU - Abid, Syrine AU - Hamza, Chiheb AU - Ben Jeddou, Syrine AU - Sabbah, Lassaad AU - Lakhdhar, Rim AU - Dammak, Najla AU - Sellami, Tarak AU - Herbegue, Basma AU - Koubaa, Alia AU - Triki, Faten AU - Ellouze, Tarek AU - Hmoudi, Aicha AU - Ben Ameur, Ikhlas AU - Boukhchina, Mongi Mohamed AU - Abid, Neila AU - Ouechtati, Wejdene AU - Nasrallah, Nizar AU - Houidi, Yousra AU - Mghaieth Zghal, Fathia AU - Elhem, Ghodhbane AU - Chayeb, Mounira AU - Sarra, Chenik AU - Kaabachi, Samira AU - Saadaoui, Nizar AU - Ben Ameur, Ines AU - Affes, Moufida AU - Ouali, Sana AU - Chaker, Mouna AU - Naana, Hela AU - Meriem, Dghim AU - Jarrar, Mourad AU - Mnif, Jihen AU - Turki, Ahmed AU - Zairi, Ihsen AU - Langar, Jamel AU - Dardouri, Safa AU - Hachaichi, Imen AU - Chettaoui, Rafik AU - Smat, Wajih AU - Chakroun, Amel AU - Mzoughi, Khadija AU - Mechmeche, Rachid AU - Ben Halima, Afef AU - Ben Kahla Koubaa, Sahar AU - Chtourou, Slim AU - Mohamed abdelkader, Maalej AU - Ayari, Mohsen AU - Hadrich, Moufid AU - Rami, Tlili AU - Azaiez, Fares AU - Bouhlel, Imen AU - Sahnoun, Samir AU - Jerbi, Habib AU - Imtinene, Mrad Ben AU - Riahi, Leila AU - Sahnoun, Mohamed AU - Ben Jemaa, Abdelhamid AU - Ben Salem, Amal AU - Rekik, Bassem AU - Ben Doudou, Maroua AU - Boujnah, Rachid Mohamed AU - Joulak, Anissa AU - Omar, Abid AU - Razgallah, Rabie AU - Sami, Milouchi AU - Neffati, Elyes AU - Gamra, Habib AU - Ben Youssef, Soraya AU - Sdiri, Wissem AU - Ben Halima, Nejeh AU - Ben Ameur, Youssef AU - Kachboura, Salem AU - Kraiem, Sondes AU - Fehri, Wafa AU - Zakhama, Lilia AU - Bezdah, leila AU - Mohamed Sami, Mourali AU - Drissa, Habiba AU - Maatouk, Faouzi Mohamed AU - Kammoun, Samir AU - Addad, Faouzi PY - 2022/9/2 TI - Design and Rationale of the National Observational Multicentric Tunisian Registry of Hypertension: Protocol for Evaluating Hypertensive Patient Care in Clinical Practice JO - JMIR Res Protoc SP - e21878 VL - 11 IS - 9 KW - National Tunisian Registry KW - hypertension N2 - Background: This study was designed to evaluate the care of hypertensive patients in daily clinical practice in public and private centers in all Tunisian regions. Objective: This study will provide us an overview of hypertension (HTN) management in Tunisia and the degree of adherence of practitioners to international recommendations. Methods: This is a national observational cross-sectional multicenter study that will include patients older than 18 years with HTN for a duration of 4 weeks, managed in the public sector from primary and secondary care centers as well as patients managed in the private sector. Every participating patient signed a consent form. The study will exclude patients undergoing dialysis. The parameters that will be evaluated are demographic and anthropometric data, lifestyle habits, blood pressure levels, lipid profiles, treatment, and adherence to treatment. The data are collected via the web interface in the Dacima Clinical Suite. Results: The study began on April 15, 2019 and ended on May 15, 2019. During this period, we included 25,890 patients with HTN. Data collection involved 321 investigators from 24 Tunisian districts. The investigators were doctors working in the private and public sectors. Conclusions: Observational studies are extremely useful in improving the management of HTN in developing countries. Trial Registration: ClinicalTrials.gov NCT04013503; https://clinicaltrials.gov/ct2/show/NCT04013503 International Registered Report Identifier (IRRID): DERR1-10.2196/21878 UR - https://www.researchprotocols.org/2022/9/e21878 UR - http://dx.doi.org/10.2196/21878 UR - http://www.ncbi.nlm.nih.gov/pubmed/36053572 ID - info:doi/10.2196/21878 ER - TY - JOUR AU - Rahmani, Reza AU - Moradi Farsani, Ehsan AU - Bahrami, Sima PY - 2022/8/17 TI - Ranolazine Versus Allopurinol for Eligible Symptomatic Patients With a History of Angioplasty: Comparative Efficacy Study JO - Interact J Med Res SP - e39778 VL - 11 IS - 2 KW - ranolazine KW - allopurinol KW - recurrent angina KW - exercise tolerance N2 - Background: Recurrent angina, which is defined as a return of chest pain or chest discomfort, occurs in many patients undergoing coronary interventions. Objective: This study aims to compare the antianginal efficacy of ranolazine versus allopurinol for eligible symptomatic patients with a history of angioplasty. Methods: A total of 62 eligible symptomatic patients with a history of angioplasty were randomly allocated into two groups. For group A, 300 mg of allopurinol was administered twice daily, while for group B, 1000 mg of ranolazine daily was prescribed for a duration of 4 weeks. An initial screening visit was done for all participants where patients? medical history was recorded and a physical examination was given; electrocardiography, blood pressure, and heart rate measurements were done as well. The patients were also given a blood and exercise test. At the end of the medication period, participants were revisited, and the tests were done again. All the required data were collected via a researcher-made form, and data analysis was conducted using SPSS. The study was approved by a formal ethics committee. Results: The mean age of participants in the two groups (A and B) was 57.36 (SD 8.36) and 60.27 (SD 9.17) years, respectively. Among the 62 patients, 34 (59%) were men, while 28 (41%) were women. Creatinine, fasting blood sugar, C-reactive protein, N-terminal prohormone of brain natriuretic protein, uric acid, white blood cell, and hemoglobin levels of participants were not significantly different between groups (P>.05). Both allopurinol and ranolazine increased the total exercise time and decreased the ST depression of the patients. Additionally, they both improved the chest pain severity and Duke Treadmill Score of patients. At the same time, ranolazine had a statistically greater effect on ST depression reduction (mean 2.64, SD 0.74 vs mean 1.57, SD 0.49), while allopurinol showed better efficacy in reducing chest pain severity (mean 1.86, SD 0.37 vs mean 0.59, SD 0.21) and the Duke Treadmill Score (mean ?14.77, SD 3.65 vs mean ?6.88, SD 1.93). Conclusions: Based on the results, the antianginal efficacy of allopurinol and ranolazine was approved but with different effects on ST depression, chest pain severity, and the Duke Treadmill Score. Therefore, the precise differences in their effects need to be explored further. UR - https://www.i-jmr.org/2022/2/e39778 UR - http://dx.doi.org/10.2196/39778 UR - http://www.ncbi.nlm.nih.gov/pubmed/35976197 ID - info:doi/10.2196/39778 ER - TY - JOUR AU - Matthews, Stacey AU - Atkins, Brooke AU - Walton, Natalie AU - Mitchell, Julie-Anne AU - Jennings, Garry AU - Buttery, K. Amanda PY - 2022/8/5 TI - Development and Use of a Cardiac Clinical Guideline Mobile App in Australia: Acceptability and Multi-Methods Study JO - JMIR Form Res SP - e35599 VL - 6 IS - 8 KW - mHealth KW - mobile heath KW - apps KW - app KW - guideline KW - cardiovascular disease KW - atrial fibrillation KW - heart failure KW - heart KW - cardiac KW - cardiovascular KW - acute coronary syndrome KW - smartphone KW - implementation KW - digital health KW - develop KW - evaluate KW - evaluation KW - Australia N2 - Background: Implementation of clinical guidelines into routine practice remains highly variable. Strategies to increase guideline uptake include developing digital tools and mobile apps for use in clinical practice. The National Heart Foundation of Australia in collaboration with the Cardiac Society of Australia and New Zealand published 3 key cardiac clinical guidelines, including the Australian clinical guidelines for the (1) prevention and detection of atrial fibrillation, (2) detection and management of heart failure, and (3) management of acute coronary syndromes. To improve access and uptake for health care providers, we developed the Smart Heart Guideline App. Objective: This study aims to evaluate the acceptability, implementation, and usability of an Australian-specific cardiac guidelines mobile app. Methods: We used an iterative multiple methods development and implementation approach. First, we conducted a cross-sectional web-based survey with end users (n=504 health professionals) in 2017 to determine the acceptability of an Australian-specific cardiac clinical guidelines mobile app. Second, the Smart Heart Guidelines app was created using a design, user testing, and revision process. The app includes interactive algorithms and flowcharts to inform diagnosis and management at the point of care. The freely available app was launched in October 2019 on iOS and Android operating systems and promoted and implemented using multiple methods. Third, data from 2 annual national cross-sectional general practitioner (GP) surveys in 2019 and 2020 were evaluated to understand the awareness and use of the clinical guidelines and the app. Fourth, data from the app stores were analyzed between October 1, 2019, and June 30, 2021, to evaluate usage. Results: Most health professionals surveyed (447/504, 89%) reported accessing resources electronically, and most (318/504, 63%) reported that they would use an Australian-specific cardiac guidelines app. GPs surveyed in 2019 were aware of the heart failure (159/312, 51%) and atrial fibrillation (140/312, 45%) guidelines, and in 2020, a total of 34 of 189 (18%) reported that they were aware of the app. The app was downloaded 11,313 times (7483, 66% from the Apple App Store; 3830, 34% from Google Play) during the first 20-month period. Most downloads (6300/7483, 84%) were a result of searching for the app in the stores. Monthly download rates varied. App Store data showed that people used the app twice (on average 2.06 times) during the 20 months. Many (3256/3830, 85%) Android users deleted the app. Conclusions: Health professionals supported the development of the Smart Heart Guidelines app. Although initial downloads were promising, the frequency of using the app was low and deletion rates were high. Further evaluation of users? experience of the most and least useful components of the app is needed. UR - https://formative.jmir.org/2022/8/e35599 UR - http://dx.doi.org/10.2196/35599 UR - http://www.ncbi.nlm.nih.gov/pubmed/35930350 ID - info:doi/10.2196/35599 ER - TY - JOUR AU - Hammami, Rania AU - Boudiche, Selim AU - Rami, Tlili AU - Ben Halima, Nejeh AU - Jamel, Ahmed AU - Rekik, Bassem AU - Gribaa, Rym AU - Imtinene, Mrad Ben AU - Charfeddine, Salma AU - Ellouze, Tarek AU - Bahloul, Amine AU - Hédi, Slima Ben AU - Langar, Jamel AU - Ben Ahmed, Habib AU - Ibn Elhadj, Zied AU - Hmam, Mohamed AU - Ben Abdessalem, Aymen Mohamed AU - Maaoui, Sabri AU - Fennira, Sana AU - Lobna, Laroussi AU - Hassine, Majed AU - Ouanes, Sami AU - Mohamed Faouzi, Drissi AU - Mallek, Souad AU - Mahdhaoui, Abdallah AU - Meriem, Dghim AU - Jomaa, Walid AU - Zayed, Sofien AU - Kateb, Tawfik AU - Bouchahda, Nidhal AU - Azaiez, Fares AU - Ben Salem, Helmi AU - Marouen, Morched AU - Noamen, Aymen AU - Abdesselem, Salem AU - Hichem, Denguir AU - Ibn Hadj Amor, Hassen AU - Abdeljelil, Farhati AU - Amara, Amine AU - Bejar, Karim AU - Khaldoun, Hamda Ben AU - Hamza, Chiheb AU - Ben Jamaa, Mohsen AU - Fourati, Sami AU - Elleuch, Faycal AU - Grati, Zeineb AU - Chtourou, Slim AU - Marouene, Sami AU - Sahnoun, Mohamed AU - Hadrich, Morched AU - Mohamed Abdelkader, Maalej AU - Bouraoui, Hatem AU - Kamoun, Kamel AU - Hadrich, Moufid AU - Ben Chedli, Tarek AU - Drissa, Akrem Mohamed AU - Charfeddine, Hanene AU - Saadaoui, Nizar AU - Achraf, Gargouri AU - Ahmed, Siala AU - Ayari, Mokdad AU - Nabil, Marsit AU - Mnif, Sabeur AU - Sahnoun, Maher AU - Kammoun, Helmi AU - Ben Jemaa, Khaled AU - Mostari, Gharbi AU - Hamrouni, Nebil AU - Yamen, Maazoun AU - Ellouz, Yassine AU - Smiri, Zahreddine AU - Hdiji, Amine AU - Bassem, Jerbi AU - Ayadi, Wacef AU - Zouari, Amir AU - Abbassi, Chedly AU - Fatma, Masmoudi Boujelben AU - Battikh, Kais AU - Kharrat, Elyes AU - Gtif, Imen AU - Sami, Milouchi AU - Bezdah, Leila AU - Kachboura, Salem AU - Maatouk, Faouzi Mohamed AU - Kraiem, Sondes AU - Jeridi, Gouider AU - Neffati, Elyes AU - Kammoun, Samir AU - Ben Ameur, Youssef AU - Fehri, Wafa AU - Gamra, Habib AU - Zakhama, Lilia AU - Addad, Faouzi AU - Mohamed Sami, Mourali AU - Abid, Leila PY - 2022/8/5 TI - Design and Rationale of the National Tunisian Registry of Percutaneous Coronary Intervention: Protocol for a Prospective Multicenter Observational Study JO - JMIR Res Protoc SP - e24595 VL - 11 IS - 8 KW - percutaneous coronary intervention KW - 1-year outcome KW - Tunisia KW - national KW - multicentric KW - registry KW - percutaneous KW - coronary KW - artery disease N2 - Background: Coronary artery diseases remain the leading cause of death in the world. The management of this condition has improved remarkably in the recent years owing to the development of new technical tools and multicentric registries. Objective: The aim of this study is to investigate the in-hospital and 1-year clinical outcomes of patients treated with percutaneous coronary intervention (PCI) in Tunisia. Methods: We will conduct a prospective multicentric observational study with patients older than 18 years who underwent PCI between January 31, 2020 and June 30, 2020. The primary end point is the occurrence of a major adverse cardiovascular event, defined as cardiovascular death, myocardial infarction, cerebrovascular accident, or target vessel revascularization with either repeat PCI or coronary artery bypass grafting (CABG). The secondary end points are procedural success rate, stent thrombosis, and the rate of redo PCI/CABG for in-stent restenosis. Results: In this study, the demographic profile and the general risk profile of Tunisian patients who underwent PCI and their end points will be analyzed. The complexity level of the procedures and the left main occlusion, bifurcation occlusion, and chronic total occlusion PCI will be analyzed, and immediate as well as long-term results will be determined. The National Tunisian Registry of PCI (NATURE-PCI) will be the first national multicentric registry of angioplasty in Africa. For this study, the institutional ethical committee approval was obtained (0223/2020). This trial consists of 97 cardiologists and 2498 patients who have undergone PCI with a 1-year follow-up period. Twenty-eight catheterization laboratories from both public (15 laboratories) and private (13 laboratories) sectors will enroll patients after receiving informed consent. Of the 2498 patients, 1897 (75.9%) are managed in the public sector and 601 (24.1%) are managed in the private sector. The COVID-19 pandemic started in Tunisia in March 2020; 719 patients (31.9%) were included before the COVID-19 pandemic and 1779 (60.1%) during the pandemic. The inclusion of patients has been finished, and we expect to publish the results by the end of 2022. Conclusions: This study would add data and provide a valuable opportunity for real-world clinical epidemiology and practice in the field of interventional cardiology in Tunisia with insights into the uptake of PCI in this limited-income region. Trial Registration: Clinicaltrials.gov NCT04219761; https://clinicaltrials.gov/ct2/show/NCT04219761 International Registered Report Identifier (IRRID): RR1-10.2196/24595 UR - https://www.researchprotocols.org/2022/8/e24595 UR - http://dx.doi.org/10.2196/24595 UR - http://www.ncbi.nlm.nih.gov/pubmed/35930353 ID - info:doi/10.2196/24595 ER - TY - JOUR AU - Huang, Yanqun AU - Zheng, Zhimin AU - Ma, Moxuan AU - Xin, Xin AU - Liu, Honglei AU - Fei, Xiaolu AU - Wei, Lan AU - Chen, Hui PY - 2022/8/3 TI - Improving the Performance of Outcome Prediction for Inpatients With Acute Myocardial Infarction Based on Embedding Representation Learned From Electronic Medical Records: Development and Validation Study JO - J Med Internet Res SP - e37486 VL - 24 IS - 8 KW - representation learning KW - skip-gram KW - feature association strengths KW - feature importance KW - mortality risk prediction KW - acute myocardial infarction N2 - Background: The widespread secondary use of electronic medical records (EMRs) promotes health care quality improvement. Representation learning that can automatically extract hidden information from EMR data has gained increasing attention. Objective: We aimed to propose a patient representation with more feature associations and task-specific feature importance to improve the outcome prediction performance for inpatients with acute myocardial infarction (AMI). Methods: Medical concepts, including patients? age, gender, disease diagnoses, laboratory tests, structured radiological features, procedures, and medications, were first embedded into real-value vectors using the improved skip-gram algorithm, where concepts in the context windows were selected by feature association strengths measured by association rule confidence. Then, each patient was represented as the sum of the feature embeddings weighted by the task-specific feature importance, which was applied to facilitate predictive model prediction from global and local perspectives. We finally applied the proposed patient representation into mortality risk prediction for 3010 and 1671 AMI inpatients from a public data set and a private data set, respectively, and compared it with several reference representation methods in terms of the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and F1-score. Results: Compared with the reference methods, the proposed embedding-based representation showed consistently superior predictive performance on the 2 data sets, achieving mean AUROCs of 0.878 and 0.973, AUPRCs of 0.220 and 0.505, and F1-scores of 0.376 and 0.674 for the public and private data sets, respectively, while the greatest AUROCs, AUPRCs, and F1-scores among the reference methods were 0.847 and 0.939, 0.196 and 0.283, and 0.344 and 0.361 for the public and private data sets, respectively. Feature importance integrated in patient representation reflected features that were also critical in prediction tasks and clinical practice. Conclusions: The introduction of feature associations and feature importance facilitated an effective patient representation and contributed to prediction performance improvement and model interpretation. UR - https://www.jmir.org/2022/8/e37486 UR - http://dx.doi.org/10.2196/37486 UR - http://www.ncbi.nlm.nih.gov/pubmed/35921141 ID - info:doi/10.2196/37486 ER - TY - JOUR AU - Yeung, Kan Andy Wai AU - Kulnik, Tino Stefan AU - Parvanov, D. Emil AU - Fassl, Anna AU - Eibensteiner, Fabian AU - Völkl-Kernstock, Sabine AU - Kletecka-Pulker, Maria AU - Crutzen, Rik AU - Gutenberg, Johanna AU - Höppchen, Isabel AU - Niebauer, Josef AU - Smeddinck, David Jan AU - Willschke, Harald AU - Atanasov, G. Atanas PY - 2022/5/11 TI - Research on Digital Technology Use in Cardiology: Bibliometric Analysis JO - J Med Internet Res SP - e36086 VL - 24 IS - 5 KW - cardiovascular KW - heart KW - hypertension KW - atrial fibrillation KW - cardiopulmonary resuscitation KW - electrocardiography KW - photoplethysmography KW - wearable device, digital health, mHealth KW - cardiology KW - cardiac KW - health application N2 - Background: Digital technology uses in cardiology have become a popular research focus in recent years. However, there has been no published bibliometric report that analyzed the corresponding academic literature in order to derive key publishing trends and characteristics of this scientific area. Objective: We used a bibliometric approach to identify and analyze the academic literature on digital technology uses in cardiology, and to unveil popular research topics, key authors, institutions, countries, and journals. We further captured the cardiovascular conditions and diagnostic tools most commonly investigated within this field. Methods: The Web of Science electronic database was queried to identify relevant papers on digital technology uses in cardiology. Publication and citation data were acquired directly from the database. Complete bibliographic data were exported to VOSviewer, a dedicated bibliometric software package, and related to the semantic content of titles, abstracts, and keywords. A term map was constructed for findings visualization. Results: The analysis was based on data from 12,529 papers. Of the top 5 most productive institutions, 4 were based in the United States. The United States was the most productive country (4224/12,529, 33.7%), followed by United Kingdom (1136/12,529, 9.1%), Germany (1067/12,529, 8.5%), China (682/12,529, 5.4%), and Italy (622/12,529, 5.0%). Cardiovascular diseases that had been frequently investigated included hypertension (152/12,529, 1.2%), atrial fibrillation (122/12,529, 1.0%), atherosclerosis (116/12,529, 0.9%), heart failure (106/12,529, 0.8%), and arterial stiffness (80/12,529, 0.6%). Recurring modalities were electrocardiography (170/12,529, 1.4%), angiography (127/12,529, 1.0%), echocardiography (127/12,529, 1.0%), digital subtraction angiography (111/12,529, 0.9%), and photoplethysmography (80/12,529, 0.6%). For a literature subset on smartphone apps and wearable devices, the Journal of Medical Internet Research (20/632, 3.2%) and other JMIR portfolio journals (51/632, 8.0%) were the major publishing venues. Conclusions: Digital technology uses in cardiology target physicians, patients, and the general public. Their functions range from assisting diagnosis, recording cardiovascular parameters, and patient education, to teaching laypersons about cardiopulmonary resuscitation. This field already has had a great impact in health care, and we anticipate continued growth. UR - https://www.jmir.org/2022/5/e36086 UR - http://dx.doi.org/10.2196/36086 UR - http://www.ncbi.nlm.nih.gov/pubmed/35544307 ID - info:doi/10.2196/36086 ER - TY - JOUR AU - Borgonovo, Giulia AU - Vettus, Elen AU - Greco, Alessandra AU - Leo, Anna Laura AU - Faletra, Fulvio Francesco AU - Klersy, Catherine AU - Curti, Moreno AU - Valli, Mariacarla PY - 2022/4/21 TI - Early Detection of Cardiotoxicity From Systemic and Radiation Therapy in Patients With Breast Cancer: Protocol for a Multi-Institutional Prospective Study JO - JMIR Res Protoc SP - e31887 VL - 11 IS - 4 KW - breast cancer KW - cardiotoxicity KW - cardiac diagnostic imaging KW - radiotherapy KW - chemotherapy N2 - Background: The incidence of breast cancer is rising worldwide. Recent advances in systemic and local treatments have significantly improved survival rates of patients having early breast cancer. In the last decade, great attention has been paid to the prevention and early detection of cardiotoxicity induced by breast cancer treatments. Systemic therapy-related cardiac toxicities have been extensively studied. Radiotherapy, an essential component of breast cancer treatment, can also increase the risk of heart diseases. Consequently, it is important to balance the expected benefits of cancer treatment with cardiovascular risk and to identify strategies to prevent cardiotoxicity and improve long-term outcomes and quality of life for these patients. Objective: This CardioTox Breast study aims to investigate the use of cardiac imaging, based on cardiac magnetic resonance and echocardiography, and to identify associated circulating biomarkers to assess early tissue changes in chemo-induced and radiation-induced cardiotoxicity in the time window of 12 months after the end of radiotherapy in patients with breast cancer. Methods: The CardioTox Breast trial is a multicenter observational prospective longitudinal study. We aim to enroll 150 women with stage I-III unilateral breast cancer, treated with breast conserving surgery, who planned to receive radiotherapy with or without systemic therapy. Baseline and follow-up data include cardiac measurements based on cardiac magnetic resonance imaging, echocardiography, and circulating biomarkers of cardiac toxicity. Results: This study details the protocol of the CardioTox Breast trial. Recruitment started in September 2020. The results of this study will not be published until data are mature for the final analysis of the primary study end point. Conclusions: The CardioTox Breast study is designed to investigate the effects of systemic and radiation therapy on myocardial function and structure, thus providing additional evidence on whether cardiac magnetic resonance is the optimal screening imaging for cardiotoxicity. Trial Registration: ClinicalTrials.gov NCT04790266; https://clinicaltrials.gov/ct2/show/NCT04790266 International Registered Report Identifier (IRRID): DERR1-10.2196/31887 UR - https://www.researchprotocols.org/2022/4/e31887 UR - http://dx.doi.org/10.2196/31887 UR - http://www.ncbi.nlm.nih.gov/pubmed/35451989 ID - info:doi/10.2196/31887 ER - TY - JOUR AU - Bezerra Giordan, Leticia AU - Tong, Ly Huong AU - Atherton, J. John AU - Ronto, Rimante AU - Chau, Josephine AU - Kaye, David AU - Shaw, Tim AU - Chow, Clara AU - Laranjo, Liliana PY - 2022/3/31 TI - The Use of Mobile Apps for Heart Failure Self-management: Systematic Review of Experimental and Qualitative Studies JO - JMIR Cardio SP - e33839 VL - 6 IS - 1 KW - heart failure KW - self-management KW - mobile health KW - mobile app KW - secondary prevention KW - mobile phone N2 - Background: Heart failure self-management is essential to avoid decompensation and readmissions. Mobile apps seem promising in supporting heart failure self-management, and there has been a rapid growth in publications in this area. However, to date, systematic reviews have mostly focused on remote monitoring interventions using nonapp types of mobile technologies to transmit data to health care providers, rarely focusing on supporting patient self-management of heart failure. Objective: This study aims to systematically review the evidence on the effect of heart failure self-management apps on health outcomes, patient-reported outcomes, and patient experience. Methods: Four databases (PubMed, Embase, CINAHL, and PsycINFO) were searched for studies examining interventions that comprised a mobile app targeting heart failure self-management and reported any health-related outcomes or patient-reported outcomes or perspectives published from 2008 to December 2021. The studies were independently screened. The risk of bias was appraised using Cochrane tools. We performed a narrative synthesis of the results. The protocol was registered on PROSPERO (International Prospective Register of Systematic Reviews; CRD42020158041). Results: A total of 28 articles (randomized controlled trials [RCTs]: n=10, 36%), assessing 23 apps, and a total of 1397 participants were included. The most common app features were weight monitoring (19/23, 83%), symptom monitoring (18/23, 78%), and vital sign monitoring (15/23, 65%). Only 26% (6/23) of the apps provided all guideline-defined core components of heart failure self-management programs: education, symptom monitoring, medication support, and physical activity support. RCTs were small, involving altogether 717 participants, had ?6 months of follow-up, and outcomes were predominantly self-reported. Approximately 20% (2/10) of RCTs reported a significant improvement in their primary outcomes: heart failure knowledge (P=.002) and self-care (P=.004). One of the RCTs found a significant reduction in readmissions (P=.02), and 20% (2/10) of RCTs reported higher unplanned clinic visits. Other experimental studies also found significant improvements in knowledge, self-care, and readmissions, among others. Less than half of the studies involved patients and clinicians in the design of apps. Engagement with the intervention was poorly reported, with only 11% (3/28) of studies quantifying app engagement metrics such as frequency of use over the study duration. The most desirable app features were automated self-monitoring and feedback, personalization, communication with clinicians, and data sharing and integration. Conclusions: Mobile apps may improve heart failure self-management; however, more robust evaluation studies are needed to analyze key end points for heart failure. On the basis of the results of this review, we provide a road map for future studies in this area. UR - https://cardio.jmir.org/2022/1/e33839 UR - http://dx.doi.org/10.2196/33839 UR - http://www.ncbi.nlm.nih.gov/pubmed/35357311 ID - info:doi/10.2196/33839 ER - TY - JOUR AU - Shan, Rongzi AU - Chandra, V. Neha AU - Hsu, J. Jeffrey AU - Fraschilla, Stephanie AU - Moore, Melissa AU - Ardehali, Abbas AU - Nsair, Ali AU - Parikh, V. Rushi PY - 2022/3/30 TI - The Impact of Transitioning From In-Person to Virtual Heart Transplantation Selection Committee Meetings: Observational Study JO - JMIR Cardio SP - e35490 VL - 6 IS - 1 KW - telemedicine KW - transplantation KW - heart failure KW - physician KW - heart transplant KW - virtual meeting KW - interprofessional relations KW - health systems KW - selection committee N2 - Background: Heart transplant selection committee meetings have transitioned from in-person to remote video meetings during the COVID-19 pandemic, but how this impacts committee members and patient outcomes is unknown. Objective: The aim of this study is to determine the perceived impact of remote video transplant selection meetings on usability and patient care and to measure patient selection outcomes during the transition period from in-person to virtual meetings. Methods: A 35-item anonymous survey was developed and distributed electronically to the heart transplant selection committee. We reviewed medical records to compare the outcomes of patients presented at in-person meetings (January-March 2020) to those presented during video meetings (March-June 2020). Results: Among 83 committee members queried, 50 were regular attendees. Of the 50 regular attendees, 24 (48%) were physicians and 26 (52%) were nonphysicians, including nurses, social workers, and coordinators; 46 responses were received, 23 (50%) from physicians and 23 (50%) from nonphysicians, with 41 responses fully completed. Overall, respondents were satisfied with the videoconference format and felt that video meetings did not impact patient care and were an acceptable alternative to in-person meetings. However, 54% (22/41) preferred in-person meetings, with 71% (15/21) of nonphysicians preferring in-person meetings compared to only 35% (7/20) of physicians (P=.02). Of the 46 new patient evaluations presented, there was a statistically nonsignificant trend toward fewer patients initially declined at video meetings compared with in-person meetings (6/24, 25% compared to 10/22, 45%; P=.32). Conclusions: The transition from in-person to video heart transplant selection committee meetings was well-received and did not appear to affect committee members? perceived ability to deliver patient care. Patient selection outcomes were similar between meeting modalities. UR - https://cardio.jmir.org/2022/1/e35490 UR - http://dx.doi.org/10.2196/35490 UR - http://www.ncbi.nlm.nih.gov/pubmed/35353041 ID - info:doi/10.2196/35490 ER - TY - JOUR AU - Castela Forte, José AU - Gannamani, Rahul AU - Folkertsma, Pytrik AU - Kumaraswamy, Sridhar AU - Mount, Sarah AU - van Dam, Sipko AU - Hoogsteen, Jan PY - 2022/3/23 TI - Changes in Blood Lipid Levels After a Digitally Enabled Cardiometabolic Preventive Health Program: Pre-Post Study in an Adult Dutch General Population Cohort JO - JMIR Cardio SP - e34946 VL - 6 IS - 1 KW - cholesterol KW - lifestyle intervention KW - prevention KW - hypercholesterolemia KW - digital health N2 - Background: Despite widespread education, many individuals fail to follow basic health behaviors such as consuming a healthy diet and exercising. Positive changes in lifestyle habits are associated with improvements in multiple cardiometabolic health risk factors, including lipid levels. Digital lifestyle interventions have been suggested as a viable complement or potential alternative to conventional health behavior change strategies. However, the benefit of digital preventive interventions for lipid levels in a preventive health context remains unclear. Objective: This observational study aimed to determine how the levels of lipids, namely total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, non-HDL cholesterol, and triglycerides, changed over time in a Dutch general population cohort undergoing a digital preventive health program. Moreover, we looked to establish associations between lifestyle factors at baseline and lipid levels. Methods: We included 348 adults from the Dutch general population who underwent a digitally enabled preventive health program at Ancora Health between January 2020 and October 2021. Upon enrollment, participants underwent a baseline assessment involving a comprehensive lifestyle questionnaire, a blood biochemistry panel, physical measurements, and cardiopulmonary fitness measurements. Thereafter, users underwent a lifestyle coaching program and could access the digital application to register and track health behaviors, weight, and anthropometric data at any time. Lipid levels were categorized as normal, elevated, high, and clinical dyslipidemia according to accepted international standards. If at least one lipid marker was high or HDL was low, participants received specific coaching and advice for cardiometabolic health. We retrospectively analyzed the mean and percentage changes in lipid markers in users who were remeasured after a cardiometabolic health?focused intervention, and studied the association between baseline user lifestyle characteristics and having normal lipid levels. Results: In our cohort, 199 (57.2%) participants had dyslipidemia at baseline, of which 104 participants were advised to follow a cardiometabolic health?focused intervention. Eating more amounts of favorable food groups and being more active were associated with normal lipid profiles. Among the participants who underwent remeasurement 9 months after intervention completion, 57% (17/30), 61% (19/31), 56% (15/27), 82% (9/11), and 100% (8/8) showed improvements at remeasurement for total, LDL, HDL, and non-HDL cholesterol, and triglycerides, respectively. Moreover, between 35.3% and 77.8% showed a return to normal levels. In those with high lipid levels at baseline, total cholesterol decreased by 0.5 mmol/L (7.5%), LDL cholesterol decreased by 0.39 mmol/L (10.0%), non-HDL cholesterol decreased by 0.44 mmol/L (8.3%), triglycerides decreased by 0.97 mmol/L (32.0%), and HDL increased by 0.17 mmol/L (15.6%), after the intervention. Conclusions: A cardiometabolic screening program in a general population cohort identified a significant portion of individuals with subclinical and clinical lipid levels. Individuals who, after screening, actively engaged in a cardiometabolic health?focused lifestyle program improved their lipid levels. UR - https://cardio.jmir.org/2022/1/e34946 UR - http://dx.doi.org/10.2196/34946 UR - http://www.ncbi.nlm.nih.gov/pubmed/35319473 ID - info:doi/10.2196/34946 ER - TY - JOUR AU - Larsen, Hoejkjaer Lisbeth AU - Lauritzen, Hedegaard Maja AU - Sinkjaer, Mikkel AU - Kjaer, W. Troels PY - 2022/3/15 TI - The Effect of Wearable Tracking Devices on Cardiorespiratory Fitness Among Inactive Adults: Crossover Study JO - JMIR Cardio SP - e31501 VL - 6 IS - 1 KW - activity tracking KW - cardiorespiratory fitness KW - mHealth KW - mobile health KW - motivation KW - physical activity KW - self-monitoring KW - wearable KW - cardio KW - fitness KW - cardiorespiratory KW - behavior change N2 - Background: Modern lifestyle is associated with a high prevalence of physical inactivity. Objective: This study aims to investigate the effect of a wearable tracking device on cardiorespiratory fitness among inactive adults and to explore if personal characteristics and health outcomes can predict adoption of the device. Methods: In total, 62 inactive adults were recruited for this study. A control period (4 weeks) was followed by an intervention period (8 weeks) where participants were instructed to register and follow their physical activity (PA) behavior on a wrist-worn tracking device. Data collected included estimated cardiorespiratory fitness, body composition, blood pressure, perceived stress levels, and self-reported adoption of using the tracking device. Results: In total, 50 participants completed the study (mean age 48, SD 13 years, 84% women). Relative to the control period, participants increased cardiorespiratory fitness by 1.52 mL/kg/minute (95% CI 0.82-2.22; P<.001), self-reported PA by 140 minutes per week (95% CI 93.3-187.1; P<.001), daily step count by 982 (95% CI 492-1471; P<.001), and participants? fat percentage decreased by 0.48% (95% CI ?0.84 to ?0.13; P=.009). No difference was observed in blood pressure (systolic: 95% CI ?2.16 to 3.57, P=.63; diastolic: 95% CI ?0.70 to 2.55; P=.27) or perceived stress (95% CI ?0.86 to 1.78; P=.49). No associations were found between adoption of the wearable tracking device and age, gender, personality, or education. However, participants with a low perceived stress at baseline were more likely to rate the use of a wearable tracking device highly motivating. Conclusions: Tracking health behavior using a wearable tracking device increases PA resulting in an improved cardiorespiratory fitness among inactive adults. UR - https://cardio.jmir.org/2022/1/e31501 UR - http://dx.doi.org/10.2196/31501 UR - http://www.ncbi.nlm.nih.gov/pubmed/35289763 ID - info:doi/10.2196/31501 ER - TY - JOUR AU - Ni, Zhao AU - Wu, Bei AU - Yang, Qing AU - Yan, L. Lijing AU - Liu, Changqing AU - Shaw, J. Ryan PY - 2022/3/9 TI - An mHealth Intervention to Improve Medication Adherence and Health Outcomes Among Patients With Coronary Heart Disease: Randomized Controlled Trial JO - J Med Internet Res SP - e27202 VL - 24 IS - 3 KW - mHealth KW - medication adherence KW - coronary disease KW - blood pressure KW - China KW - randomized controlled trial N2 - Background: The treatment of many chronic illnesses involves long-term pharmaceutical therapy, but it is an ongoing challenge to find effective ways to improve medication adherence to promote good health outcomes. Cardioprotective medications can prevent the enlargement of harmful clots, cardiovascular symptoms, and poor therapeutic outcomes, such as uncontrolled high blood pressure and hyperlipidemia, for patients with coronary heart disease. Poor adherence to cardioprotective medications, however, has been reported as a global health concern among patients with coronary heart disease, and it is particularly a concern in China. Objective: This study aimed to evaluate the efficacy of a mobile health (mHealth) intervention using 2 mobile apps to improve medication adherence and health outcomes. Methods: A randomized, placebo-controlled, 2-arm parallel study was conducted in a major university-affiliated medical center located in Chengdu, China. Participants were recruited by flyers and health care provider referrals. Each participant was observed for 90 days, including a 60-day period of mHealth intervention and a 30-day period of nonintervention follow-up. The study coordinator used WeChat and Message Express to send educational materials and reminders to take medication, respectively. Participants used WeChat to receive both the educational materials and reminders. Participants in the control group only received educational materials. This study received ethics approval from the Duke Health Institutional Review Board (Pro00073395) on May 5, 2018, and was approved by West China Hospital (20170331180037). Recruitment began on May 20, 2018. The pilot phase of this study was registered on June 8, 2016, and the current, larger-scale study was retrospectively registered on January 11, 2021 (ClinicalTrials.gov). Results: We recruited 230 patients with coronary heart disease. Of these patients, 196 completed the baseline survey and received the intervention. The majority of participants were married (181/196, 92.4%), male (157/196, 80.1%), and lived in urban China (161/196, 82.1%). Participants? average age was 61 years, and half were retired (103/191, 53.9%). More than half the participants (121/196, 61.7%) were prescribed at least 5 medications. The mean decrease in medication nonadherence score was statistically significant at both 60 days (t179=2.04, P=.04) and 90 days (t155=3.48, P<.001). Systolic blood pressure and diastolic blood pressure decreased in the experimental group but increased in the control group. The mean decrease in diastolic blood pressure was statistically significant at both 60 days (t160=2.07, P=.04) and 90 days (t164=2.21, P=.03). The mean decrease in systolic blood pressure was significantly different in the groups at 90 days (t165=3.12, P=.002). Conclusions: The proposed mHealth intervention can improve medication adherence and health outcomes, including systolic blood pressure and diastolic blood pressure. Trial Registration: ClinicalTrials.gov NCT02793830; https://clinicaltrials.gov/ct2/show/NCT02793830 and ClinicalTrials.gov NCT04703439; https://clinicaltrials.gov/ct2/show/NCT04703439 UR - https://www.jmir.org/2022/3/e27202 UR - http://dx.doi.org/10.2196/27202 UR - http://www.ncbi.nlm.nih.gov/pubmed/35262490 ID - info:doi/10.2196/27202 ER - TY - JOUR AU - Chen, Jinying AU - Wijesundara, G. Jessica AU - Enyim, E. Gabrielle AU - Lombardini, M. Lisa AU - Gerber, S. Ben AU - Houston, K. Thomas AU - Sadasivam, S. Rajani PY - 2022/3/7 TI - Understanding Patients? Intention to Use Digital Health Apps That Support Postdischarge Symptom Monitoring by Providers Among Patients With Acute Coronary Syndrome: Survey Study JO - JMIR Hum Factors SP - e34452 VL - 9 IS - 1 KW - coronary KW - monitor KW - elder KW - health app KW - symptom KW - eHealth KW - mobile health KW - intention KW - barrier KW - facilitator N2 - Background: After hospital discharge, patients with acute coronary syndrome (ACS) often experience symptoms that prompt them to seek acute medical attention. Early evaluation of postdischarge symptoms by health care providers may reduce unnecessary acute care utilization. However, hospital-initiated follow-up encounters are insufficient for timely detection and assessment of symptoms. While digital health tools can help address this issue, little is known about the intention to use such tools in ACS patients. Objective: This study aimed to assess ACS patients? intention to use digital health apps that support postdischarge symptom monitoring by health care providers and identify patient-perceived facilitators and barriers to app use. Methods: Using email invitations or phone calls, we recruited ACS patients discharged from a central Massachusetts health care system between December 2020 and April 2021, to participate in the study. Surveys were delivered online or via phone to individual participants. Demographics and access to technology were assessed. The intention to use a symptom monitoring app was assessed using 5-point Likert-type (from strongly agree to strongly disagree) items, such as ?If this app were available to me, I would use it.? Responses were compared across demographic subgroups and survey delivery methods. Two open-ended questions assessed perceived facilitators and barriers to app use, with responses analyzed using qualitative content analysis. Results: Among 100 respondents (response rate 8.1%), 45 (45%) completed the survey by phone. The respondents were on average 68 years old (SD 13 years), with 90% (90/100) White, 39% (39/100) women, and 88% (88/100) having access to the internet or a mobile phone. Most participants (65/100, 65%) agreed or strongly agreed that they would use the app, among which 53 (82%) would use the app as often as possible. The percentage of participants with the intention to use the app was 75% among those aged 65-74 years and dropped to 44% among those older than 75 years. The intention to use was higher in online survey respondents (vs phone survey respondents; odds ratio 3.07, 95% CI 1.20-7.88) after adjusting for age and access to technology. The analysis of open-ended questions identified the following 4 main facilitators (motivations): (1) easily reaching providers, (2) accessing or providing information, (3) quickly reaching providers, and (4) consulting providers for symptoms, and the following 4 main barriers: (1) privacy/security concerns, (2) uncomfortable using technology, (3) user-unfriendly app interface, and (4) preference for in-person/phone care. Conclusions: There was a strong intention to use a symptom monitoring app postdischarge among ACS patients. However, this intent decreased in patients older than 75 years. The survey identified barriers related to technology use, privacy/security, and the care delivery mode. Further research is warranted to determine if such intent translates into app use, and better symptom management and health care quality. UR - https://humanfactors.jmir.org/2022/1/e34452 UR - http://dx.doi.org/10.2196/34452 UR - http://www.ncbi.nlm.nih.gov/pubmed/35254269 ID - info:doi/10.2196/34452 ER - TY - JOUR AU - de Freitas Gonçalves, Shelry Kamila AU - Queiroz Godoy Daniel, Carolina Ana AU - Tatagiba Lamas, Luiz José AU - Ceretta Oliveira, Henrique AU - Silveira, P. Renata C. C. AU - Cloutier, Lyne AU - Velludo Veiga, Eugenia PY - 2022/3/4 TI - Device- and Nondevice-Guided Slow Breathing to Reduce Blood Pressure in Patients with Hypertension: Protocol for a Systematic Review and Meta-analysis JO - JMIR Res Protoc SP - e33579 VL - 11 IS - 3 KW - hypertension KW - breathing exercises KW - device-guided breathing KW - respirate KW - systematic review KW - physical therapy KW - blood pressure KW - clinical decision making KW - health care professional KW - physiotherapy N2 - Background: Physiotherapy can include both device-guided slow breathing (DGSB) and nondevice-guided slow breathing (NDGSB) in the treatment of systemic arterial hypertension. Objective: The aim of this study is to summarize the effects of DGSB on blood pressure levels of patients with hypertension based on the published literature to date. Methods: A systematic search of all published randomized controlled trials (RCTs) on the effects of device-guided and nondevice-guided slow breathing in patients with hypertension, without language restriction, was carried out up to a publication date of January 2020 in nine databases: PubMed/MEDLINE, Latin American and Caribbean Health Sciences Literature (LILACS), EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), Physiotherapy Evidence Database (PEDro), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Scopus, Web of Science, and Livivo. Clinical trial records databases (ClinicalTrials.gov), and bases for the open gray literature, including Gray Literature Report and ProQuest Central (Citation, Abstract or Indexing, and Dissertations and Theses), were also searched for potentially eligible RCTs. The quality assessment of the included studies will be performed using the Cochrane Risk of Bias Tool for Randomized Trials. The overall quality of the evidence for each outcome will be assessed using the GRADE (Grading of Recommendations, Development and Evaluation) system. Results: As of December 2021, the review was completed and all data from continuous variables referring to blood pressure values (mmHg) were synthesized. Conclusions: This systematic review will provide a summary of the current evidence on the effects of both DGSB and NDGSB on blood pressure levels. This information can contribute to decision-making by health professionals related to the use of these interventions in patients with hypertension. Trial Registration: PROSPERO (Prospective International Register of Systematic Reviews) CRD42020147554; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=147554 International Registered Report Identifier (IRRID): RR1-10.2196/33579 UR - https://www.researchprotocols.org/2022/3/e33579 UR - http://dx.doi.org/10.2196/33579 UR - http://www.ncbi.nlm.nih.gov/pubmed/35254284 ID - info:doi/10.2196/33579 ER - TY - JOUR AU - Dodson, A. John AU - Schoenthaler, Antoinette AU - Sweeney, Greg AU - Fonceva, Ana AU - Pierre, Alicia AU - Whiteson, Jonathan AU - George, Barbara AU - Marzo, Kevin AU - Drewes, Wendy AU - Rerisi, Elizabeth AU - Mathew, Reena AU - Aljayyousi, Haneen AU - Chaudhry, I. Sarwat AU - Hajduk, M. Alexandra AU - Gill, M. Thomas AU - Estrin, Deborah AU - Kovell, Lara AU - Jennings, A. Lee AU - Adhikari, Samrachana PY - 2022/3/3 TI - Rehabilitation Using Mobile Health for Older Adults With Ischemic Heart Disease in the Home Setting (RESILIENT): Protocol for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e32163 VL - 11 IS - 3 KW - mobile health KW - cardiac rehabilitation KW - clinical trial KW - rehabilitation KW - cardiology KW - heart disease KW - ambulatory care KW - mHealth KW - health outcomes KW - older adults N2 - Background: Participation in ambulatory cardiac rehabilitation remains low, especially among older adults. Although mobile health cardiac rehabilitation (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments may limit older adults? uptake, and efficacy data are currently lacking. Objective: This study aims to describe the design of the rehabilitation using mobile health for older adults with ischemic heart disease in the home setting (RESILIENT) trial. Methods: RESILIENT is a multicenter randomized clinical trial that is enrolling patients aged ?65 years with ischemic heart disease in a 3:1 ratio to either an intervention (mHealth-CR) or control (usual care) arm, with a target sample size of 400 participants. mHealth-CR consists of a commercially available mobile health software platform coupled with weekly exercise therapist sessions to review progress and set new activity goals. The primary outcome is a change in functional mobility (6-minute walk distance), which is measured at baseline and 3 months. Secondary outcomes are health status, goal attainment, hospital readmission, and mortality. Among intervention participants, engagement with the mHealth-CR platform will be analyzed to understand the characteristics that determine different patterns of use (eg, persistent high engagement and declining engagement). Results: As of December 2021, the RESILIENT trial had enrolled 116 participants. Enrollment is projected to continue until October 2023. The trial results are expected to be reported in 2024. Conclusions: The RESILIENT trial will generate important evidence about the efficacy of mHealth-CR among older adults in multiple domains and characteristics that determine the sustained use of mHealth-CR. These findings will help design future precision medicine approaches to mobile health implementation in older adults. This knowledge is especially important in light of the COVID-19 pandemic that has shifted much of health care to a remote, internet-based setting. Trial Registration: ClinicalTrials.gov NCT03978130; https://clinicaltrials.gov/ct2/show/NCT03978130 International Registered Report Identifier (IRRID): DERR1-10.2196/32163 UR - https://www.researchprotocols.org/2022/3/e32163 UR - http://dx.doi.org/10.2196/32163 UR - http://www.ncbi.nlm.nih.gov/pubmed/35238793 ID - info:doi/10.2196/32163 ER - TY - JOUR AU - Siebert, N. Johan AU - Gosetto, Laëtitia AU - Sauvage, Manon AU - Bloudeau, Laurie AU - Suppan, Laurent AU - Rodieux, Frédérique AU - Haddad, Kevin AU - Hugon, Florence AU - Gervaix, Alain AU - Lovis, Christian AU - Combescure, Christophe AU - Manzano, Sergio AU - Ehrler, Frederic AU - PY - 2022/3/1 TI - Usability Testing and Technology Acceptance of an mHealth App at the Point of Care During Simulated Pediatric In- and Out-of-Hospital Cardiopulmonary Resuscitations: Study Nested Within 2 Multicenter Randomized Controlled Trials JO - JMIR Hum Factors SP - e35399 VL - 9 IS - 1 KW - cardiopulmonary resuscitation KW - drugs KW - emergency medical services KW - medication errors KW - mobile health KW - mobile apps KW - out-of-hospital cardiac arrest KW - paramedics KW - pediatrics KW - System Usability Scale KW - Unified Theory of Acceptance and Use of Technology KW - smartphone KW - mobile phone N2 - Background: Mobile apps are increasingly being used in various domains of medicine. Few are evidence-based, and their benefits can only be achieved if end users intend to adopt and use them. To date, only a small fraction of mobile apps have published data on their field usability and end user acceptance results, especially in emergency medicine. Objective: This study aims to determine the usability and acceptance of an evidence-based mobile app while safely preparing emergency drugs at the point of care during pediatric in- and out-of-hospital cardiopulmonary resuscitations by frontline caregivers. Methods: In 2 multicenter randomized controlled parent trials conducted at 6 pediatric emergency departments from March 1 to December 31, 2017, and 14 emergency medical services from September 3, 2019, to January 21, 2020, the usability and technology acceptance of the PedAMINES (Pediatric Accurate Medication in Emergency Situations) app were evaluated among skilled pediatric emergency nurses and advanced paramedics when preparing continuous infusions of vasoactive drugs and direct intravenous emergency drugs at pediatric dosages during standardized, simulation-based, pediatric in- and out-of-hospital cardiac arrest scenarios, respectively. Usability was measured using the 10-item System Usability Scale. A 26-item technology acceptance self-administered survey (5-point Likert-type scales), adapted from the Unified Theory of Acceptance and Use of Technology model, was used to measure app acceptance and intention to use. Results: All 100% (128/128) of nurses (crossover trial) and 49.3% (74/150) of paramedics (parallel trial) were assigned to the mobile app. Mean total scores on the System Usability Scale were excellent and reached 89.5 (SD 8.8; 95% CI 88.0-91.1) for nurses and 89.7 (SD 8.7; 95% CI 87.7-91.7) for paramedics. Acceptance of the technology was very good and rated on average >4.5/5 for 5 of the 8 independent constructs evaluated. Only the image construct scored between 3.2 and 3.5 by both participant populations. Conclusions: The results provide evidence that dedicated mobile apps can be easy to use and highly accepted at the point of care during in- and out-of-hospital cardiopulmonary resuscitations by frontline emergency caregivers. These findings can contribute to the implementation and valorization of studies aimed at evaluating the usability and acceptance of mobile apps in the field by caregivers, even in critical situations. Trial Registration: ClinicalTrials.gov NCT03021122; https://clinicaltrials.gov/ct2/show/NCT03021122. ClinicalTrials.gov NCT03921346; https://clinicaltrials.gov/ct2/show/NCT03921346 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3726-4 UR - https://humanfactors.jmir.org/2022/1/e35399 UR - http://dx.doi.org/10.2196/35399 UR - http://www.ncbi.nlm.nih.gov/pubmed/35230243 ID - info:doi/10.2196/35399 ER - TY - JOUR AU - Ben Hafaiedh, Sonia AU - Ben Daya, Yosra AU - Radoui, Hadjer Amina AU - Bouchoucha, Mohamed AU - Razgallah, Rabie AU - Nouira, Semir PY - 2022/3/1 TI - Home Telemonitoring of Arterial Hypertension With Antihypertensive Treatment Titration: Protocol for a Randomized Controlled Prospective Trial (HOROSCOPE Study) JO - JMIR Res Protoc SP - e26184 VL - 11 IS - 3 KW - telemonitoring KW - arterial hypertension KW - primary care KW - ambulatory blood pressure monitoring KW - randomized controlled trial N2 - Background: Despite the availability of effective treatment, the control of hypertension remains insufficient. Telemonitoring in the management of hypertension would be an effective way to improve blood pressure control. Objective: The aim of our study will be to evaluate the effects of telemonitoring with antihypertensive treatment titration on blood pressure control in Tunisian patients with hypertension. Methods: Our trial will be a prospective, rater-blinded randomized controlled trial carried out with primary care physicians in the Sahel region of Tunisia. Patients will be eligible for enrollment if they are aged over 35 years, are newly diagnosed with hypertension, or are known to be poorly controlled on antihypertensive therapy. Participants will be randomly assigned in a 1:1 ratio to the telemonitoring arm or usual care arm. The telemonitoring arm will involve a weekly telephone call for the collection of the home blood pressure measurements, therapeutic education, and treatment compliance assessment as well as a monthly call for treatment titration and a side effect check. Randomization will be done via the use of an interactive web responsive system, and patients will be stratified by investigation center. Neither participants nor investigators will be masked to the group assignments. The primary outcome will be the change in mean 24-hour systolic blood pressure from baseline to the 6-month follow-up in the 2 groups. All randomized patients who attend the follow-up visit at 6 months and have no missing data for the primary outcome will be included in the analysis. Results: Recruitment to the trial started in July 2020. The study was initiated with 17 primary care physicians. We expect the inclusion period to last for approximately 6 months. We expect to complete data collection by the end of 2021 and plan to disseminate the results subsequently. Conclusions: The HOROSCOPE (Home Telemonitoring of Arterial Hypertension With Antihypertensive Treatment Titration: Randomized Controlled Prospective Trial) study will provide important new evidence that could shed some light on the feasibility and impact of telemonitoring and self-monitoring in a Tunisian population of patients with hypertension who consult primary care physicians. Trial Registration: ClinicalTrials.gov NCT04607239; https://clinicaltrials.gov/ct2/show/NCT04607239 International Registered Report Identifier (IRRID): DERR1-10.2196/26184 UR - https://www.researchprotocols.org/2022/3/e26184 UR - http://dx.doi.org/10.2196/26184 UR - http://www.ncbi.nlm.nih.gov/pubmed/35230254 ID - info:doi/10.2196/26184 ER - TY - JOUR AU - Zolk, Oliver AU - von dem Knesebeck, Annika AU - Graf, Norbert AU - Simon, Thorsten AU - Hero, Barbara AU - Abdul-Khaliq, Hashim AU - Abd El Rahman, Mohamed AU - Spix, Claudia AU - Mayer, Benjamin AU - Elsner, Susanne AU - Gebauer, Judith AU - Langer, Thorsten PY - 2022/2/17 TI - Cardiovascular Health Status And Genetic Risk In Survivors of Childhood Neuroblastoma and Nephroblastoma Treated With Doxorubicin: Protocol of the Pharmacogenetic Part of the LESS-Anthra Cross-Sectional Cohort Study JO - JMIR Res Protoc SP - e27898 VL - 11 IS - 2 KW - cardiotoxicity KW - anthracyclines KW - childhood cancer survivors KW - genetics KW - polymorphisms KW - cardiology KW - cardiac health KW - cancer KW - survivors KW - childhood KW - children KW - risk monitoring KW - cardiovascular health KW - pediatrics N2 - Background: In childhood cancer survivors (survival of 5 years or more after diagnosis), cardiac toxicity is the most common nonmalignant cause of death attributed to treatment-related consequences. Identifying patients at risk of developing late cardiac toxicity is therefore crucial to improving treatment outcomes. The use of genetic markers has been proposed, together with clinical risk factors, to predict individual risk of cardiac toxicity from cancer therapies, such as doxorubicin. Objective: The primary aim of this study is to evaluate the value of multimarker genetic testing for RARG rs2229774, UGT1A6 rs17863783, and SLC28A3 rs7853758 for predicting doxorubicin-induced cardiotoxicity. The secondary aim is to replicate previously described associations of candidate genetic markers with doxorubicin-induced cardiotoxicity. Moreover, we will evaluate the prevalence of cardiovascular dysfunction in childhood cancer survivors after neuroblastoma or nephroblastoma. Methods: This is the pharmacogenetic substudy of the research project Structural Optimization for Children With Cancer After Anthracycline Therapy (LESS-Anthra). We invited 2158 survivors of childhood neuroblastoma or nephroblastoma treated with doxorubicin according to the trial protocols of SIOP 9/GPOH, SIOP 93-01/GPOH, SIOP 2001/GPOH, NB 90, NB 97, or NB 2004 to participate in this prospective cross-sectional cohort study. The study participants underwent a cardiological examination and were asked to provide a blood or saliva sample for genotyping. The study participants' health statuses and cardiovascular diagnoses were recorded using a questionnaire completed by the cardiologist. Digital echocardiographic data were centrally evaluated to determine the contractile function parameters. Medical data on the tumor diagnosis and treatment protocol were taken from the study documentation. Survivors were screened for variants of several candidate genes by TaqMan genotyping. Results: This study includes 657 survivors treated with doxorubicin for childhood cancer, the largest German cohort assembled to date to investigate cardiovascular late effects. Data analyses are yet to be completed. Conclusions: This study will define the genetic risk related to 3 marker genes proposed in a pharmacogenetic guideline for risk assessment. Moreover, the results of this study will show the prevalence of cardiovascular dysfunction in survivors of pediatric neuroblastoma or nephroblastoma who were treated with doxorubicin. The results will help to improve primary treatment and follow-up care, thus reducing cardiovascular late effects in the growing population of childhood cancer survivors. Trial Registration: German Clinical Trials Register DRKS00015084; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00015084 International Registered Report Identifier (IRRID): DERR1-10.2196/27898 UR - https://www.researchprotocols.org/2022/2/e27898 UR - http://dx.doi.org/10.2196/27898 UR - http://www.ncbi.nlm.nih.gov/pubmed/35175211 ID - info:doi/10.2196/27898 ER - TY - JOUR AU - Morken, Margreta Ingvild AU - Storm, Marianne AU - Søreide, Arne Jon AU - Urstad, Hjorthaug Kristin AU - Karlsen, Bjørg AU - Husebø, Lunde Anne Marie PY - 2022/2/15 TI - Posthospitalization Follow-Up of Patients With Heart Failure Using eHealth Solutions: Restricted Systematic Review JO - J Med Internet Res SP - e32946 VL - 24 IS - 2 KW - adherence KW - eHealth KW - heart failure KW - posthospitalization follow-up KW - patient outcome KW - review N2 - Background: Heart failure (HF) is a clinical syndrome with high incidence rates, a substantial symptom and treatment burden, and a significant risk of readmission within 30 days after hospitalization. The COVID-19 pandemic has revealed the significance of using eHealth interventions to follow up on the care needs of patients with HF to support self-care, increase quality of life (QoL), and reduce readmission rates during the transition between hospital and home. Objective: The aims of this review are to summarize research on the content and delivery modes of HF posthospitalization eHealth interventions, explore patient adherence to the interventions, and examine the effects on the patient outcomes of self-care, QoL, and readmissions. Methods: A restricted systematic review study design was used. Literature searches and reviews followed the (PRISMA-S) Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension checklist, and the CINAHL, MEDLINE, Embase, and Cochrane Library databases were searched for studies published between 2015 and 2020. The review process involved 3 groups of researchers working in pairs. The Mixed Methods Appraisal Tool was used to assess the included studies? methodological quality. A thematic analysis method was used to analyze data extracted from the studies. Results: A total of 18 studies were examined in this review. The studies were published between 2015 and 2019, with 56% (10/18) of them published in the United States. Of the 18 studies, 16 (89%) were randomized controlled trials, and 14 (78%) recruited patients upon hospital discharge to eHealth interventions lasting from 14 days to 12 months. The studies involved structured telephone calls, interactive voice response, and telemonitoring and included elements of patient education, counseling, social and emotional support, and self-monitoring of symptoms and vital signs. Of the 18 studies, 11 (61%) provided information on patient adherence, and the adherence levels were 72%-99%. When used for posthospitalization follow-up of patients with HF, eHealth interventions can positively affect QoL, whereas its impact is less evident for self-care and readmissions. Conclusions: This review suggests that patients with HF should receive prompt follow-up after hospitalization and eHealth interventions have the potential to improve these patients? QoL. Patient adherence in eHealth follow-up trials shows promise for successful future interventions and adherence research. Further studies are warranted to examine the effects of eHealth interventions on self-care and readmissions among patients with HF. UR - https://www.jmir.org/2022/2/e32946 UR - http://dx.doi.org/10.2196/32946 UR - http://www.ncbi.nlm.nih.gov/pubmed/35166680 ID - info:doi/10.2196/32946 ER - TY - JOUR AU - Tahri Sqalli, Mohammed AU - Al-Thani, Dena AU - Elshazly, B. Mohamed AU - Al-Hijji, Mohammed AU - Alahmadi, Alaa AU - Sqalli Houssaini, Yahya PY - 2022/2/9 TI - Understanding Cardiology Practitioners? Interpretations of Electrocardiograms: An Eye-Tracking Study JO - JMIR Hum Factors SP - e34058 VL - 9 IS - 1 KW - eye tracking KW - electrocardiogram KW - ECG interpretation KW - cardiology practitioners KW - human-computer interaction KW - cardiology KW - ECG N2 - Background: Visual expertise refers to advanced visual skills demonstrated when performing domain-specific visual tasks. Prior research has emphasized the fact that medical experts rely on such perceptual pattern-recognition skills when interpreting medical images, particularly in the field of electrocardiogram (ECG) interpretation. Analyzing and modeling cardiology practitioners? visual behavior across different levels of expertise in the health care sector is crucial. Namely, understanding such acquirable visual skills may help train less experienced clinicians to interpret ECGs accurately. Objective: This study aims to quantify and analyze through the use of eye-tracking technology differences in the visual behavior and methodological practices for different expertise levels of cardiology practitioners such as medical students, cardiology nurses, technicians, fellows, and consultants when interpreting several types of ECGs. Methods: A total of 63 participants with different levels of clinical expertise took part in an eye-tracking study that consisted of interpreting 10 ECGs with different cardiac abnormalities. A counterbalanced within-subjects design was used with one independent variable consisting of the expertise level of the cardiology practitioners and two dependent variables of eye-tracking metrics (fixations count and fixation revisitations). The eye movements data revealed by specific visual behaviors were analyzed according to the accuracy of interpretation and the frequency with which interpreters visited different parts/leads on a standard 12-lead ECG. In addition, the median and SD in the IQR for the fixations count and the mean and SD for the ECG lead revisitations were calculated. Results: Accuracy of interpretation ranged between 98% among consultants, 87% among fellows, 70% among technicians, 63% among nurses, and finally 52% among medical students. The results of the eye fixations count, and eye fixation revisitations indicate that the less experienced cardiology practitioners need to interpret several ECG leads more carefully before making any decision. However, more experienced cardiology practitioners rely on their skills to recognize the visual signal patterns of different cardiac abnormalities, providing an accurate ECG interpretation. Conclusions: The results show that visual expertise for ECG interpretation is linked to the practitioner?s role within the health care system and the number of years of practical experience interpreting ECGs. Cardiology practitioners focus on different ECG leads and different waveform abnormalities according to their role in the health care sector and their expertise levels. UR - https://humanfactors.jmir.org/2022/1/e34058 UR - http://dx.doi.org/10.2196/34058 UR - http://www.ncbi.nlm.nih.gov/pubmed/35138258 ID - info:doi/10.2196/34058 ER - TY - JOUR AU - Fundoiano-Hershcovitz, ?Yifat AU - Bacher, Dror AU - Ritholz, D. Marilyn AU - Horwitz, L. David AU - Manejwala, Omar AU - Goldstein, Pavel PY - 2022/2/8 TI - Blood Pressure Monitoring as a Digital Health Tool for Improving Diabetes Clinical Outcomes: Retrospective Real-world Study JO - J Med Internet Res SP - e32923 VL - 24 IS - 2 KW - blood glucose KW - blood pressure KW - monitoring KW - digital therapeutic KW - diabetes KW - hypertension KW - app KW - model KW - chronic disease KW - health data N2 - Background: Remote data capture for blood glucose (BG) or blood pressure (BP) monitoring and the use of a supportive digital app are becoming the model in diabetes and hypertension chronic care. One of the goals in chronic condition management is to increase awareness and generate behavioral change in order to improve outcomes in diabetes and related comorbidities, such as hypertension. In addition, there is a lack of understanding of the association between BG and BP levels when using digital health tools. Objective: By applying a rigorous study framework to digital health data, this study investigated the relationship between BP monitoring and BG and BP levels, as well as a lagged association between BP and BG. We hypothesized that during the first 6 months of BP monitoring, BG and BP levels would decrease. Finally, we suggested a positive association between BP levels and the following month?s BG levels. Methods: In this retrospective, real-world case-control study, we extracted the data of 269 people with type 2 diabetes (T2D) who tracked their BG levels using the Dario digital platform for a chronic condition. We analyzed the digital data of the users who, in addition to BG, monitored their BP using the same app (BP-monitoring [BPM] group, n=137) 6 months before and after starting their BP monitoring. Propensity score matching established a control group, no blood pressure monitoring (NBPM, n=132), matched on demographic and baseline clinical measures to the BPM group. A piecewise mixed model was used for analyzing the time trajectories of BG, BP, and their lagged association. Results: Analysis revealed a significant difference in BG time trajectories associated with BP monitoring in BPM and NBPM groups (t=?2.12, P=.03). The BPM group demonstrated BG reduction improvement in the monthly average BG levels during the first 6 months (t=?3.57, P<.001), while BG did not change for the NBPM group (t=0.39, P=.70). Both groups showed similarly stable BG time trajectories (B=0.98, t=1.16, P=.25) before starting the use of the BP-monitoring system. In addition, the BPM group showed a significant reduction in systolic (t=?6.42, P<.001) and diastolic (t=?4.80, P<.001) BP during the first 6 months of BP monitoring. Finally, BG levels were positively associated with systolic (B=0.24, t=2.77, P=.001) and diastolic (B=0.30, t=2.41, P=.02) BP. Conclusions: The results of this study shed light on the association between BG and BP levels and on the role of BP self-monitoring in diabetes management. Our findings also underscore the need and provide a basis for a comprehensive approach to understanding the mechanism of BP regulation associated with BG. UR - https://www.jmir.org/2022/2/e32923 UR - http://dx.doi.org/10.2196/32923 UR - http://www.ncbi.nlm.nih.gov/pubmed/35133284 ID - info:doi/10.2196/32923 ER - TY - JOUR AU - Eastman, A. Jennifer AU - Kaup, R. Allison AU - Bahorik, L. Amber AU - Butcher, Xochitl AU - Attarha, Mouna AU - Marcus, M. Gregory AU - Pletcher, J. Mark AU - Olgin, E. Jeffrey AU - Barnes, E. Deborah AU - Yaffe, Kristine PY - 2022/2/2 TI - Remote Assessment of Cardiovascular Risk Factors and Cognition in Middle-Aged and Older Adults: Proof-of-Concept Study JO - JMIR Form Res SP - e30410 VL - 6 IS - 2 KW - mHealth KW - internet KW - mobile health KW - digital health KW - eHealth KW - cardiovascular KW - risk factors KW - cognition KW - cognitive impairment KW - remote cognitive assessment KW - aging N2 - Background: Adults with cardiovascular disease risk factors (CVRFs) are also at increased risk of developing cognitive decline and dementia. However, it is often difficult to study the relationships between CVRFs and cognitive function because cognitive assessment typically requires time-consuming in-person neuropsychological evaluations that may not be feasible for real-world situations. Objective: We conducted a proof-of-concept study to determine if the association between CVRFs and cognitive function could be detected using web-based, self-administered cognitive tasks and CVRF assessment. Methods: We recruited 239 participants aged ?50 years (mean age 62.7 years, SD 8.8; 42.7% [n=102] female, 88.7% [n=212] White) who were enrolled in the Health eHeart Study, a web-based platform focused on cardiac disease. The participants self-reported CVRFs (hypertension, high cholesterol, diabetes, and atrial fibrillation) using web-based health surveys between August 2016 and July 2018. After an average of 3 years of follow-up, we remotely evaluated episodic memory, working memory, and executive function via the web-based Posit Science platform, BrainHQ. Raw data were normalized and averaged into 3 domain scores. We used linear regression models to examine the association between CVRFs and cognitive function. Results: CVRF prevalence was 62.8% (n=150) for high cholesterol, 45.2% (n=108) for hypertension, 10.9% (n=26) for atrial fibrillation, and 7.5% (n=18) for diabetes. In multivariable models, atrial fibrillation was associated with worse working memory (?=-.51, 95% CI -0.91 to -0.11) and worse episodic memory (?=-.31, 95% CI -0.59 to -0.04); hypertension was associated with worse episodic memory (?=-.27, 95% CI -0.44 to -0.11). Diabetes and high cholesterol were not associated with cognitive performance. Conclusions: Self-administered web-based tools can be used to detect both CVRFs and cognitive health. We observed that atrial fibrillation and hypertension were associated with worse cognitive function even in those in their 60s and 70s. The potential of mobile assessments to detect risk factors for cognitive aging merits further investigation. UR - https://formative.jmir.org/2022/2/e30410 UR - http://dx.doi.org/10.2196/30410 UR - http://www.ncbi.nlm.nih.gov/pubmed/35107430 ID - info:doi/10.2196/30410 ER - TY - JOUR AU - Mourad, Ghassan AU - Eriksson-Liebon, Magda AU - Karlström, Patric AU - Johansson, Peter PY - 2022/1/28 TI - The Effect of Internet-Delivered Cognitive Behavioral Therapy Versus Psychoeducation Only on Psychological Distress in Patients With Noncardiac Chest Pain: Randomized Controlled Trial JO - J Med Internet Res SP - e31674 VL - 24 IS - 1 KW - cardiac anxiety KW - cognitive behavioral therapy KW - health-related quality of life KW - internet delivered KW - noncardiac chest pain KW - psychological distress N2 - Background: Patients with recurrent episodes of noncardiac chest pain (NCCP) experience cardiac anxiety as they misinterpret the pain to be cardiac related and avoid physical activity that they think could threaten their lives. Psychological interventions, such as internet-delivered cognitive behavioral therapy (iCBT), targeting anxiety can be a feasible solution by supporting patients to learn how to perceive and handle their chest pain. Objective: This study aims to evaluate the effects of a nurse-led iCBT program on cardiac anxiety and other patient-reported outcomes in patients with NCCP. Methods: Patients with at least two health care consultations because of NCCP during the past 6 months, and who were experiencing cardiac anxiety (Cardiac Anxiety Questionnaire score ?24), were randomized into 5 weeks of iCBT (n=54) or psychoeducation (n=55). Patients were aged 54 (SD 17) years versus 57 (SD 16) years and were mainly women (32/54, 59% vs 35/55, 64%). The iCBT program comprised psychoeducation, mindfulness, and exposure to physical activity, with weekly homework assignments. The primary outcome was cardiac anxiety. The secondary outcomes were fear of bodily sensations, depressive symptoms, health-related quality of life, and chest pain frequency. Intention-to-treat analysis was applied, and the patients were followed up for 3 months. Mixed model analysis was used to determine between-group differences in primary and secondary outcomes. Results: No significant differences were found between the iCBT and psychoeducation groups regarding cardiac anxiety or any of the secondary outcomes in terms of the interaction effect of time and group over the 3-month follow-up. iCBT demonstrated a small effect size on cardiac anxiety (Cohen d=0.31). In the iCBT group, 36% (16/44) of patients reported a positive reliable change score (?11 points on the Cardiac Anxiety Questionnaire), and thus an improvement in cardiac anxiety, compared with 27% of (13/48) patients in the psychoeducation group. Within-group analysis showed further significant improvement in cardiac anxiety (P=.04) at the 3-month follow-up compared with the 5-week follow-up in the iCBT group but not in the psychoeducation group. Conclusions: iCBT was not superior to psychoeducation in decreasing cardiac anxiety in patients with NCCP. However, iCBT tends to have better long-term effects on psychological distress, including cardiac anxiety, health-related quality of life, and NCCP frequency than psychoeducation. The effects need to be followed up to draw more reliable conclusions. Trial Registration: ClinicalTrials.gov NCT03336112; https://www.clinicaltrials.gov/ct2/show/NCT03336112 UR - https://www.jmir.org/2022/1/e31674 UR - http://dx.doi.org/10.2196/31674 UR - http://www.ncbi.nlm.nih.gov/pubmed/35089153 ID - info:doi/10.2196/31674 ER - TY - JOUR AU - Thesen, Terje AU - Himle, A. Joseph AU - Martinsen, W. Egil AU - Walseth, T. Liv AU - Thorup, Frode AU - Gallefoss, Frode AU - Jonsbu, Egil PY - 2022/1/24 TI - Effectiveness of Internet-Based Cognitive Behavioral Therapy With Telephone Support for Noncardiac Chest Pain: Randomized Controlled Trial JO - J Med Internet Res SP - e33631 VL - 24 IS - 1 KW - noncardiac chest pain KW - internet-based treatment KW - internet-assisted treatment KW - cognitive behavioral therapy KW - psychosomatic medicine KW - randomized controlled trial KW - pain KW - treatment KW - internet-based cognitive behavioral therapy KW - effectiveness KW - support KW - intervention N2 - Background: Noncardiac chest pain has a high prevalence and is associated with reduced quality of life, anxiety, avoidance of physical activity, and high societal costs. There is a lack of an effective, low-cost, easy to distribute intervention to assist patients with noncardiac chest pain. Objective: In this study, we aimed to investigate the effectiveness of internet-based cognitive behavioral therapy with telephone support for noncardiac chest pain. Methods: We conducted a randomized controlled trial, with a 12-month follow-up period, to compare internet-based cognitive behavioral therapy to a control condition (treatment as usual). A total of 162 participants aged 18 to 70 years with a diagnosis of noncardiac chest pain were randomized to either internet-based cognitive behavioral therapy (n=81) or treatment as usual (n=81). The participants in the experimental condition received 6 weekly sessions of internet-based cognitive behavioral therapy. The sessions covered different topics related to coping with noncardiac chest pain (education about the heart, physical activity, interpretations/attention, physical reactions to stress, optional panic treatment, and maintaining change). Between sessions, the participants also engaged in individually tailored physical exercises with increasing intensity. In addition to internet-based cognitive behavioral therapy sessions, participants received a brief weekly call from a clinician to provide support, encourage adherence, and provide access to the next session. Participants in the treatment-as-usual group received standard care for their noncardiac chest pain without any restrictions. Primary outcomes were cardiac anxiety, measured with the Cardiac Anxiety Questionnaire, and fear of bodily sensations, measured with the Body Sensations Questionnaire. Secondary outcomes were depression, measured using the Patient Health Questionnaire; health-related quality of life, measured using the EuroQol visual analog scale; and level of physical activity, assessed with self-report question. Additionally, a subgroup analysis of participants with depressive symptoms at baseline (PHQ-9 score ?5) was conducted. Assessments were conducted at baseline, posttreatment, and at 3- and 12-month follow-ups. Linear mixed models were used to evaluate treatment effects. Cohen d was used to calculate effect sizes. Results: In the main intention-to-treat analysis at the 12-month follow-up time point, participants in the internet-based cognitive behavioral therapy group had significant improvements in cardiac anxiety (?3.4 points, 95% CI ?5.7 to ?1.1; P=.004, d=0.38) and a nonsignificant improvement in fear of bodily sensations (?2.7 points, 95% CI ?5.6 to 0.3; P=.07) compared with the treatment-as-usual group. Health-related quality of life at the 12-month follow-up improved with statistical and clinical significance in the internet-based cognitive behavioral therapy group (8.8 points, 95% CI 2.8 to 14.8; P=.004, d=0.48) compared with the treatment-as-usual group. Physical activity had significantly (P<.001) increased during the 6-week intervention period for the internet-based cognitive behavioral therapy group. Depression significantly improved posttreatment (P=.003) and at the 3-month follow-up (P=.03), but not at the 12-month follow-up (P=.35). Participants with depressive symptoms at baseline seemed to have increased effect of the intervention on cardiac anxiety (d=0.55) and health-related quality of life (d=0.71) at the 12-month follow-up. In the internet-based cognitive behavioral therapy group, 84% of the participants (68/81) completed at least 5 of the 6 sessions. Conclusions: This study provides evidence that internet-based cognitive behavioral therapy with minimal therapist contact and a focus on physical activity is effective in reducing cardiac anxiety and increasing health related quality of life in patients with noncardiac chest pain. Trial Registration: ClinicalTrials.gov NCT03096925; http://clinicaltrials.gov/ct2/show/NCT03096925 UR - https://www.jmir.org/2022/1/e33631 UR - http://dx.doi.org/10.2196/33631 UR - http://www.ncbi.nlm.nih.gov/pubmed/35072641 ID - info:doi/10.2196/33631 ER - TY - JOUR AU - Lairez, Olivier AU - Blanchard, Virginie AU - Balardy, Laurent AU - Vardon-Bounes, Fanny AU - Cazalbou, Stéphanie AU - Ruiz, Stéphanie AU - Collot, Samia AU - Houard, Valérie AU - Rolland, Yves AU - Conil, Jean-Marie AU - Minville, Vincent PY - 2022/1/6 TI - COCARDE Study?Cardiac Imaging Phenotype in Patients With COVID-19: Protocol for a Prospective Observational Study JO - JMIR Res Protoc SP - e24931 VL - 11 IS - 1 KW - COVID-19 KW - SARS-CoV-2 KW - cardiac imaging KW - echocardiography KW - cardiac MRI KW - hyperinflammation KW - inflammation N2 - Background: The effects of SARS-CoV-2 (COVID-19) on the myocardium and their role in the clinical course of infected patients are still unknown. The severity of SARS-CoV-2 is driven by hyperinflammation, and the effects of SARS-CoV-2 on the myocardium may be significant. This study proposes to use bedside observations and biomarkers to characterize the association of COVID-19 with myocardial injury. Objective: The aim of the study is to describe the myocardial function and its evolution over time in patients infected with SARS-CoV-2 and to investigate the link between inflammation and cardiac injury. Methods: This prospective, monocentric, observational study enrolled 150 patients with suspected or confirmed SARS-CoV-2 infection at Toulouse University Hospital, Toulouse, France. Patients admitted to the intensive care unit (ICU), regular cardiologic ward, and geriatric ward of our tertiary university hospital were included during the pandemic period. Blood sampling, electrocardiography, echocardiography, and morphometric and demographic data were prospectively collected. Results: A total of 100 patients were included. The final enrolment day was March 31, 2020, with first report of results at the end of the first quarter of 2021. The first echocardiographic results at admission of 31 patients of the COCARDE-ICU substudy population show that biological myocardial injury in COVID-19 has low functional impact on left ventricular systolic function. Conclusions: A better understanding of the effects of COVID-19 on myocardial function and its link with inflammation would improve patient follow-up and care. Trial Registration: Clinicaltrials.gov NCT04358952; https://clinicaltrials.gov/ct2/show/NCT04358952 International Registered Report Identifier (IRRID): DERR1-10.2196/24931 UR - https://www.researchprotocols.org/2022/1/e24931 UR - http://dx.doi.org/10.2196/24931 UR - http://www.ncbi.nlm.nih.gov/pubmed/34751159 ID - info:doi/10.2196/24931 ER - TY - JOUR AU - Elzinga, O. Willem AU - Prins, Samantha AU - Borghans, M. Laura G. J. AU - Gal, Pim AU - Vargas, A. Gabriel AU - Groeneveld, J. Geert AU - Doll, J. Robert PY - 2021/12/30 TI - Detection of Clenbuterol-Induced Changes in Heart Rate Using At-Home Recorded Smartwatch Data: Randomized Controlled Trial JO - JMIR Form Res SP - e31890 VL - 5 IS - 12 KW - photoplethysmography KW - smartwatch KW - wearable KW - at-home KW - heart rate KW - RCT KW - wearable device KW - digital health KW - cardiovascular KW - cardiology KW - sensors KW - heart rate sensor KW - smart technology N2 - Background: Although electrocardiography is the gold standard for heart rate (HR) recording in clinical trials, the increasing availability of smartwatch-based HR monitors opens up possibilities for drug development studies. Smartwatches allow for inexpensive, unobtrusive, and continuous HR estimation for potential detection of treatment effects outside the clinic, during daily life. Objective: The aim of this study is to evaluate the repeatability and sensitivity of smartwatch-based HR estimates collected during a randomized clinical trial. Methods: The data were collected as part of a multiple-dose, investigator-blinded, randomized, placebo-controlled, parallel-group study of 12 patients with Parkinson disease. After a 6-day baseline period, 4 and 8 patients were treated for 7 days with an ascending dose of placebo and clenbuterol, respectively. Throughout the study, the smartwatch provided HR and sleep state estimates. The HR estimates were quantified as the 2.5th, 50th, and 97.5th percentiles within awake and asleep segments. Linear mixed models were used to calculate the following: (1) the intraclass correlation coefficient (ICC) of estimated sleep durations, (2) the ICC and minimum detectable effect (MDE) of the HR estimates, and (3) the effect sizes of the HR estimates. Results: Sleep duration was moderately repeatable (ICC=0.64) and was not significantly affected by study day (P=.83), clenbuterol (P=.43), and study day by clenbuterol (P=.73). Clenbuterol-induced changes were detected in the asleep HR as of the first night (+3.79 beats per minute [bpm], P=.04) and in the awake HR as of the third day (+8.79 bpm, P=.001). The median HR while asleep had the highest repeatability (ICC=0.70). The MDE (N=12) was found to be smaller when patients were asleep (6.8 bpm to 11.7 bpm) than while awake (10.7 bpm to 22.1 bpm). Overall, the effect sizes for clenbuterol-induced changes were higher while asleep (0.49 to 2.75) than while awake (0.08 to 1.94). Conclusions: We demonstrated the feasibility of using smartwatch-based HR estimates to detect clenbuterol-induced changes during clinical trials. The asleep HR estimates were most repeatable and sensitive to treatment effects. We conclude that smartwatch-based HR estimates obtained during daily living in a clinical trial can be used to detect and track treatment effects. Trial Registration: Netherlands Trials Register NL8002; https://www.trialregister.nl/trial/8002 UR - https://formative.jmir.org/2021/12/e31890 UR - http://dx.doi.org/10.2196/31890 UR - http://www.ncbi.nlm.nih.gov/pubmed/34967757 ID - info:doi/10.2196/31890 ER - TY - JOUR AU - Rogerson, C. Michelle AU - Jackson, C. Alun AU - Navaratnam, S. Hema AU - Le Grande, R. Michael AU - Higgins, O. Rosemary AU - Clarke, Joanne AU - Murphy, M. Barbara PY - 2021/12/23 TI - Getting ?Back on Track? After a Cardiac Event: Protocol for a Randomized Controlled Trial of a Web-Based Self-management Program JO - JMIR Res Protoc SP - e34534 VL - 10 IS - 12 KW - coronary heart disease KW - heart disease KW - coronary KW - cardiovascular KW - prevention KW - RCT KW - randomized control trial KW - secondary prevention KW - self-management KW - online KW - randomised controlled trial KW - health behaviours KW - health behaviour KW - health behavior KW - depression KW - cognitive behaviour therapy KW - motivational interviewing N2 - Background: After a cardiac event, a large majority of patients with cardiac conditions do not achieve recommended behavior change targets for secondary prevention. Mental health issues can also impact the ability to engage in health behavior change. There is a need for innovative, flexible, and theory-driven eHealth programs, which include evidence-based strategies to assist patients with cardiac conditions with their recovery, especially in behavioral and emotional self-management. Objective: The aim of this study is to determine the short- and longer-term behavioral and emotional well-being outcomes of the Back on Track web-based self-management program. In addition, this study will test whether there is enhanced benefit of providing one-on-one telephone support from a trained lifestyle counselor, over and above benefit obtained through completing the web-based program alone. Methods: People who have experienced a cardiac event in the previous 12 months and have access to the internet will be eligible for this study (N=120). Participants will be randomly assigned to one of the two study conditions: either ?self-directed? completion of the Back on Track program (without assistance) or ?supported? completion of the Back on Track program (additional 2 telephone sessions with a lifestyle counselor). All participants will have access to the web-based Back on Track program for 2 months. Telephone sessions with the supported arm participants will occur at approximately 2 and 6 weeks post enrollment. Measures will be assessed at baseline, and then 2 and 6 months later. Outcome measures assessed at all 3 timepoints include dietary intake, physical activity and sitting time, smoking status, anxiety and depression, stage of change, and self-efficacy in relation to behavioral and emotional self-management, quality of life, and self-rated health and well-being. A demographic questionnaire will be included at baseline only and program acceptability at 2 months only. Results: Recruitment began in May 2020 and concluded in August 2021. Data collection for the 6-month follow-up will be completed by February 2022, and data analysis and publication of results will be completed by June 2022. A total of 122 participants were enrolled in this study. Conclusions: The Back on Track trial will enable us to quantify the behavioral and emotional improvements obtained and maintained for patients with cardiac conditions and, in particular, to compare two modes of delivery: (1) fully self-directed delivery and (2) supported by a lifestyle counselor. We anticipate that the web-based Back on Track program will assist patients in their recovery and self-management after an acute event, and represents an effective, flexible, and easily accessible adjunct to center-based rehabilitation programs. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12620000102976; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378920&isReview=true International Registered Report Identifier (IRRID): DERR1-10.2196/34534 UR - https://www.researchprotocols.org/2021/12/e34534 UR - http://dx.doi.org/10.2196/34534 UR - http://www.ncbi.nlm.nih.gov/pubmed/34941550 ID - info:doi/10.2196/34534 ER - TY - JOUR AU - Ghorbani, Banafsheh AU - Jackson, C. Alun AU - Noorchenarboo, Mohammad AU - Mandegar, H. Mohammad AU - Sharifi, Farshad AU - Mirmoghtadaie, Zohrehsadat AU - Bahramnezhad, Fatemeh PY - 2021/12/10 TI - Comparing the Effects of Gamification and Teach-Back Training Methods on Adherence to a Therapeutic Regimen in Patients After Coronary Artery Bypass Graft Surgery: Randomized Clinical Trial JO - J Med Internet Res SP - e22557 VL - 23 IS - 12 KW - teach back KW - gamification KW - treatment regimen KW - coronary artery bypass graft KW - patient training N2 - Background: Patients undergoing coronary artery bypass graft surgery (CABGS) may fail to adhere to their treatment regimen for many reasons. Among these, one of the most important reasons for nonadherence is the inadequate training of such patients or training using inappropriate methods. Objective: This study aimed to compare the effect of gamification and teach-back training methods on adherence to a therapeutic regimen in patients after CABGS. Methods: This randomized clinical trial was conducted on 123 patients undergoing CABGS in Tehran, Iran, in 2019. Training was provided to the teach-back group individually. In the gamification group, an app developed for the purpose was installed on each patient?s smartphone, with training given via this device. The control group received usual care, or routine training. Adherence to the therapeutic regimen was assessed using a questionnaire on adherence to a therapeutic regimen (physical activity and dietary regimen) and an adherence scale as a pretest and a 1-month posttest. Results: One-way analysis of variance (ANOVA) for comparing the mean scores of teach-back and gamification training methods showed that the mean normalized scores for the dietary regimen (P<.001, F=71.80), movement regimen (P<.001, F=124.53), and medication regimen (P<.001, F=9.66) before and after intervention were significantly different between the teach-back, gamification, and control groups. In addition, the results of the Dunnett test showed that the teach-back and gamification groups were significantly different from the control group in all three treatment regimen methods. There was no statistically significant difference in adherence to the therapeutic regimen between the teach-back and control groups. Conclusions: Based on the results of this study, the use of teach-back and gamification training approaches may be suggested for patients after CABGS to facilitate adherence to the therapeutic regimen. Trial Registration: Iranian Registry of Clinical Trials IRCT20111203008286N8; https://en.irct.ir/trial/41507 UR - https://www.jmir.org/2021/12/e22557 UR - http://dx.doi.org/10.2196/22557 UR - http://www.ncbi.nlm.nih.gov/pubmed/34890346 ID - info:doi/10.2196/22557 ER - TY - JOUR AU - DeLaughter, L. Kathryn AU - Fix, M. Gemmae AU - McDannold, E. Sarah AU - Pope, Charlene AU - Bokhour, G. Barbara AU - Shimada, L. Stephanie AU - Calloway, Rodney AU - Gordon, S. Howard AU - Long, A. Judith AU - Miano, A. Danielle AU - Cutrona, L. Sarah PY - 2021/12/1 TI - Incorporating African American Veterans? Success Stories for Hypertension Management: Developing a Behavioral Support Texting Protocol JO - JMIR Res Protoc SP - e29423 VL - 10 IS - 12 KW - texting KW - African American KW - hypertension KW - self-management KW - mobile phone N2 - Background: Peer narratives engage listeners through personally relevant content and have been shown to promote lifestyle change and effective self-management among patients with hypertension. Incorporating key quotations from these stories into follow-up text messages is a novel way to continue the conversation, providing reinforcement of health behaviors in the patients? daily lives. Objective: In our previous work, we developed and tested videos in which African American Veterans shared stories of challenges and success strategies related to hypertension self-management. This study aims to describe our process for developing a text-messaging protocol intended for use after viewing videos that incorporate the voices of these Veterans. Methods: We used a multistep process, transforming video-recorded story excerpts from 5 Veterans into 160-character texts. We then integrated these into comprehensive 6-month texting protocols. We began with an iterative review of story transcripts to identify vernacular features and key self-management concepts emphasized by each storyteller. We worked with 2 Veteran consultants who guided our narrative text message development in substantive ways, as we sought to craft culturally sensitive content for texts. Informed by Veteran input on timing and integration, supplementary educational and 2-way interactive assessment text messages were also developed. Results: Within the Veterans Affairs texting system Annie, we programmed five 6-month text-messaging protocols that included cycles of 3 text message types: narrative messages, nonnarrative educational messages, and 2-way interactive messages assessing self-efficacy and behavior related to hypertension self-management. Each protocol corresponds to a single Veteran storyteller, allowing Veterans to choose the story that most resonates with their own life experiences. Conclusions: We crafted a culturally sensitive text-messaging protocol using narrative content referenced in Veteran stories to support effective hypertension self-management. Integrating narrative content into a mobile health texting intervention provides a low-cost way to support longitudinal behavior change. A randomized trial is underway to test its impact on the lifestyle changes and blood pressure of African American Veterans. Trial Registration: ClinicalTrials.gov NCT03970590; https://clinicaltrials.gov/ct2/show/NCT03970590 International Registered Report Identifier (IRRID): DERR1-10.2196/29423 UR - https://www.researchprotocols.org/2021/12/e29423 UR - http://dx.doi.org/10.2196/29423 UR - http://www.ncbi.nlm.nih.gov/pubmed/34855617 ID - info:doi/10.2196/29423 ER - TY - JOUR AU - Chudyk, M. Anna AU - Ragheb, Sandra AU - Kent, David AU - Duhamel, A. Todd AU - Hyra, Carole AU - Dave, G. Mudra AU - Arora, C. Rakesh AU - Schultz, SH Annette PY - 2021/11/30 TI - Patient Engagement in the Design of a Mobile Health App That Supports Enhanced Recovery Protocols for Cardiac Surgery: Development Study JO - JMIR Perioper Med SP - e26597 VL - 4 IS - 2 KW - cardiac surgery KW - perioperative care KW - enhanced recovery protocols KW - mobile app KW - smartphone app KW - mHealth KW - development KW - patient and public involvement KW - patient engagement in research N2 - Background: Despite the importance of their perspectives, end users (eg, patients, caregivers) are not typically engaged by academic researchers in the development of mobile health (mHealth) apps for perioperative cardiac surgery settings. Objective: The aim of this study was to describe a process for and the impact of patient engagement in the development of an mHealth app that supports patient and caregiver involvement with enhanced recovery protocols during the perioperative period of cardiac surgery. Methods: Engagement occurred at the level of consultation and took the form of an advisory panel. Patients who underwent cardiac surgery (2017-2018) at St. Boniface Hospital (Winnipeg, Manitoba) and their caregivers were approached for participation. A qualitative exploration determined the impact of patient engagement on the development (ie, design and content) of the mHealth app. This included a description of (1) the key messages generated by the advisory panel, (2) how key messages were incorporated into the development of the mHealth app, and (3) feedback from the developers of the mHealth app about the key messages generated by the advisory panel. Results: The advisory panel (N=10) generated 23 key messages to guide the development of the mHealth app. Key design-specific messages (n=7) centered around access, tracking, synchronization, and reminders. Key content-specific messages (n=16) centered around medical terms, professional roles, cardiac surgery procedures and recovery, educational videos, travel, nutrition, medications, resources, and physical activity. This information was directly incorporated into the design of the mHealth app as long as it was supported by the existing functionalities of the underlying platform. For example, the platform did not support the scheduling of reminders by users, identifying drug interactions, or synchronizing with other devices. The developers of the mHealth app noted that key messages resulted in the integration of a vast range and volume of information and resources instead of ones primarily focused on surgical information, content geared toward expectations management, and an expanded focus to include caregivers and other family members, so that these stakeholders may be directly included in the provision of information, allowing them to be better informed, prepare along with the patient, and be involved in recovery planning. Conclusions: Patient engagement may facilitate the development of a detail-oriented and patient-centered mHealth app whose design and content are driven by the lived experiences of end users. UR - https://periop.jmir.org/2021/2/e26597 UR - http://dx.doi.org/10.2196/26597 UR - http://www.ncbi.nlm.nih.gov/pubmed/34851299 ID - info:doi/10.2196/26597 ER - TY - JOUR AU - Alessa, Tourkiah AU - Hawley, Mark AU - de Witte, Luc PY - 2021/11/17 TI - Identification of the Most Suitable App to Support the Self-Management of Hypertension: Systematic Selection Approach and Qualitative Study JO - JMIR Mhealth Uhealth SP - e29207 VL - 9 IS - 11 KW - app KW - hypertension KW - self-management KW - mHealth KW - blood pressure KW - support KW - Saudi Arabia KW - cardiology KW - heart KW - effective KW - security N2 - Background: Smartphone apps are increasingly being used to aid in hypertension self-management, and a large and ever-growing number of self-management apps have been commercially released. However, very few of these are potentially effective and secure, and researchers have yet to establish the suitability of specific hypertension apps to particular contexts. Objective: The aim of this study is to identify the most suitable hypertension app in the context of Saudi Arabia and its health system. Methods: This study used a 2-stage approach to selecting the most suitable app for hypertension self-management. First, a systematic selection approach was followed to identify a shortlist of the most suitable apps according to the criteria of potential effectiveness, theoretical underpinning, and privacy and security. Second, an exploratory qualitative study was conducted to select the most suitable from the shortlist: 12 doctors were interviewed, and 22 patients participated in 4 focus groups. These explored participants? attitudes towards self-management apps in general, and their views towards the apps identified via the systematic selection process. The qualitative data were analyzed using framework analysis. Results: In the first stage, only 5 apps were found to be potentially effective while also having a theoretical underpinning and protecting users? data. In the second stage, both doctors and patients were generally interested in using hypertension apps, but most had no experience with these apps due to a lack of awareness of their availability and suitability. Patients and doctors liked apps that combine intuitive interfaces with a pleasant and clear visual design, in-depth features (eg, color-coded feedback accompanied with textual explanations), activity-specific reminders, and educational content regarding hypertension and potential complications. When the pros and cons of the 5 apps were discussed, 3 apps were identified as being more suitable, with Cora Health rated the highest by the participants. Conclusions: Only 5 apps were deemed potentially effective and secure. Patients? and doctors? discussions of the pros and cons of these 5 apps revealed that 3 out of the 5 are clearly more suitable, with the Cora Health app being judged most suitable overall. UR - https://mhealth.jmir.org/2021/11/e29207 UR - http://dx.doi.org/10.2196/29207 UR - http://www.ncbi.nlm.nih.gov/pubmed/34787586 ID - info:doi/10.2196/29207 ER - TY - JOUR AU - Stunden, Chelsea AU - Zakani, Sima AU - Martin, Avery AU - Moodley, Shreya AU - Jacob, John PY - 2021/11/17 TI - Replicating Anatomical Teaching Specimens Using 3D Modeling Embedded Within a Multimodal e-Learning Course: Pre-Post Study Exploring the Impact on Medical Education During COVID-19 JO - JMIR Med Educ SP - e30533 VL - 7 IS - 4 KW - congenital heart disease KW - cardiac anatomy, pathologic anatomy KW - education KW - learning aids KW - 3D models N2 - Background: The COVID-19 pandemic has had significant effects on anatomy education. During the pandemic, students have had no access to cadavers, which has been the principal method of learning anatomy. We created and tested a customized congenital heart disease e-learning course for medical students that contained interactive 3D models of anonymized pediatric congenital heart defects. Objective: The aim of this study is to assess whether a multimodal e-learning course contributed to learning outcomes in a cohort of first-year undergraduate medical students studying congenital heart diseases. The secondary aim is to assess student attitudes and experiences associated with multimodal e-learning. Methods: The pre-post study design involved 290 first-year undergraduate medical students. Recruitment was conducted by course instructors. Data were collected before and after using the course. The primary outcome was knowledge acquisition (test scores). The secondary outcomes included attitudes and experiences, time to complete the modules, and browser metadata. Results: A total of 141 students were included in the final analysis. Students? knowledge significantly improved by an average of 44.6% (63/141) when using the course (SD 1.7%; Z=?10.287; P<.001). Most students (108/122, 88.3%) were highly motivated to learn with the course, and most (114/122, 93.5%) reported positive experiences with the course. There was a strong correlation between attitudes and experiences, which was statistically significant (rs=0.687; P<.001; n=122). No relationships were found between the change in test scores and attitudes (P=.70) or experiences (P=.47). Students most frequently completed the e-learning course with Chrome (109/141, 77.3%) and on Apple macOS (86/141, 61%) or Windows 10 (52/141, 36.9%). Most students (117/141, 83%) had devices with high-definition screens. Most students (83/141, 58.9%) completed the course in <3 hours. Conclusions: Multimodal e-learning could be a viable solution in improving learning outcomes and experiences for undergraduate medical students who do not have access to cadavers. Future research should focus on validating long-term learning outcomes. UR - https://mededu.jmir.org/2021/4/e30533 UR - http://dx.doi.org/10.2196/30533 UR - http://www.ncbi.nlm.nih.gov/pubmed/34787589 ID - info:doi/10.2196/30533 ER - TY - JOUR AU - Amin, Shiraz AU - Gupta, Vedant AU - Du, Gaixin AU - McMullen, Colleen AU - Sirrine, Matthew AU - Williams, V. Mark AU - Smyth, S. Susan AU - Chadha, Romil AU - Stearley, Seth AU - Li, Jing PY - 2021/11/16 TI - Developing and Demonstrating the Viability and Availability of the Multilevel Implementation Strategy for Syncope Optimal Care Through Engagement (MISSION) Syncope App: Evidence-Based Clinical Decision Support Tool JO - J Med Internet Res SP - e25192 VL - 23 IS - 11 KW - cardiology KW - medical diagnosis KW - medicine KW - mobile applications KW - prognostics and health KW - syncope N2 - Background: Syncope evaluation and management is associated with testing overuse and unnecessary hospitalizations. The 2017 American College of Cardiology/American Heart Association (ACC/AHA) Syncope Guideline aims to standardize clinical practice and reduce unnecessary services. The use of clinical decision support (CDS) tools offers the potential to successfully implement evidence-based clinical guidelines. However, CDS tools that provide an evidence-based differential diagnosis (DDx) of syncope at the point of care are currently lacking. Objective: With input from diverse health systems, we developed and demonstrated the viability of a mobile app, the Multilevel Implementation Strategy for Syncope optImal care thrOugh eNgagement (MISSION) Syncope, as a CDS tool for syncope diagnosis and prognosis. Methods: Development of the app had three main goals: (1) reliable generation of an accurate DDx, (2) incorporation of an evidence-based clinical risk tool for prognosis, and (3) user-based design and technical development. To generate a DDx that incorporated assessment recommendations, we reviewed guidelines and the literature to determine clinical assessment questions (variables) and likelihood ratios (LHRs) for each variable in predicting etiology. The creation and validation of the app diagnosis occurred through an iterative clinician review and application to actual clinical cases. The review of available risk score calculators focused on identifying an easily applied and valid evidence-based clinical risk stratification tool. The review and decision-making factors included characteristics of the original study, clinical variables, and validation studies. App design and development relied on user-centered design principles. We used observations of the emergency department workflow, storyboard demonstration, multiple mock review sessions, and beta-testing to optimize functionality and usability. Results: The MISSION Syncope app is consistent with guideline recommendations on evidence-based practice (EBP), and its user interface (UI) reflects steps in a real-world patient evaluation: assessment, DDx, risk stratification, and recommendations. The app provides flexible clinical decision making, while emphasizing a care continuum; it generates recommendations for diagnosis and prognosis based on user input. The DDx in the app is deemed a pragmatic model that more closely aligns with real-world clinical practice and was validated using actual clinical cases. The beta-testing of the app demonstrated well-accepted functionality and usability of this syncope CDS tool. Conclusions: The MISSION Syncope app development integrated the current literature and clinical expertise to provide an evidence-based DDx, a prognosis using a validated scoring system, and recommendations based on clinical guidelines. This app demonstrates the importance of using research literature in the development of a CDS tool and applying clinical experience to fill the gaps in available research. It is essential for a successful app to be deliberate in pursuing a practical clinical model instead of striving for a perfect mathematical model, given available published evidence. This hybrid methodology can be applied to similar CDS tool development. UR - https://www.jmir.org/2021/11/e25192 UR - http://dx.doi.org/10.2196/25192 UR - http://www.ncbi.nlm.nih.gov/pubmed/34783669 ID - info:doi/10.2196/25192 ER - TY - JOUR AU - Bonner, Carissa AU - Batcup, Carys AU - Cornell, Samuel AU - Fajardo, Anthony Michael AU - Hawkes, L. Anna AU - Trevena, Lyndal AU - Doust, Jenny PY - 2021/11/5 TI - Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects JO - JMIR Cardio SP - e31056 VL - 5 IS - 2 KW - heart age KW - cardiovascular disease KW - risk assessment KW - risk communication KW - prevention N2 - Background: Cardiovascular disease (CVD) risk communication is a challenge for clinical practice, where physicians find it difficult to explain the absolute risk of a CVD event to patients with varying health literacy. Converting the probability to heart age is increasingly used to promote lifestyle change, but a rapid review of biological age interventions found no clear evidence that they motivate behavior change. Objective: In this review, we aim to identify the content and effects of heart age interventions. Methods: We conducted a systematic review of studies presenting heart age interventions to adults for CVD risk communication in April 2020 (later updated in March 2021). The Johanna Briggs risk of bias assessment tool was applied to randomized studies. Behavior change techniques described in the intervention methods were coded. Results: From a total of 7926 results, 16 eligible studies were identified; these included 5 randomized web-based experiments, 5 randomized clinical trials, 2 mixed methods studies with quantitative outcomes, and 4 studies with qualitative analysis. Direct comparisons between heart age and absolute risk in the 5 web-based experiments, comprising 5514 consumers, found that heart age increased positive or negative emotional responses (4/5 studies), increased risk perception (4/5 studies; but not necessarily more accurate) and recall (4/4 studies), reduced credibility (2/3 studies), and generally had no effect on lifestyle intentions (4/5 studies). One study compared heart age and absolute risk to fitness age and found reduced lifestyle intentions for fitness age. Heart age combined with additional strategies (eg, in-person or phone counseling) in applied settings for 9582 patients improved risk control (eg, reduced cholesterol levels and absolute risk) compared with usual care in most trials (4/5 studies) up to 1 year. However, clinical outcomes were no different when directly compared with absolute risk (1/1 study). Mixed methods studies identified consultation time and content as important outcomes in actual consultations using heart age tools. There were differences between people receiving an older heart age result and those receiving a younger or equal to current heart age result. The heart age interventions included a wide range of behavior change techniques, and conclusions were sometimes biased in favor of heart age with insufficient supporting evidence. The risk of bias assessment indicated issues with all randomized clinical trials. Conclusions: The findings of this review provide little evidence that heart age motivates lifestyle behavior change more than absolute risk, but either format can improve clinical outcomes when combined with other behavior change strategies. The label for the heart age concept can affect outcomes and should be pretested with the intended audience. Future research should consider consultation time and differentiate between results of older and younger heart age. International Registered Report Identifier (IRRID): NPRR2-10.1101/2020.05.03.20089938 UR - https://cardio.jmir.org/2021/2/e31056 UR - http://dx.doi.org/10.2196/31056 UR - http://www.ncbi.nlm.nih.gov/pubmed/34738908 ID - info:doi/10.2196/31056 ER - TY - JOUR AU - Abid, Leila AU - Kammoun, Ikram AU - Ben Halima, Manel AU - Charfeddine, Salma AU - Ben Slima, Hedi AU - Drissa, Meriem AU - Mzoughi, Khadija AU - Mbarek, Dorra AU - Riahi, Leila AU - Antit, Saoussen AU - Ben Halima, Afef AU - Ouechtati, Wejdene AU - Allouche, Emna AU - Mechri, Mehdi AU - Yousfi, Chedi AU - Khorchani, Ali AU - Abid, Omar AU - Sammoud, Kais AU - Ezzaouia, Khaled AU - Gtif, Imen AU - Ouali, Sana AU - Triki, Feten AU - Hamdi, Sonia AU - Boudiche, Selim AU - Chebbi, Marwa AU - Hentati, Mouna AU - Farah, Amani AU - Triki, Habib AU - Ghardallou, Houda AU - Raddaoui, Haythem AU - Zayed, Sofien AU - Azaiez, Fares AU - Omri, Fadwa AU - Zouari, Akram AU - Ben Ali, Zine AU - Najjar, Aymen AU - Thabet, Houssem AU - Chaker, Mouna AU - Mohamed, Samar AU - Chouaieb, Marwa AU - Ben Jemaa, Abdelhamid AU - Tangour, Haythem AU - Kammoun, Yassmine AU - Bouhlel, Mahmoud AU - Azaiez, Seifeddine AU - Letaief, Rim AU - Maskhi, Salah AU - Amri, Aymen AU - Naanaa, Hela AU - Othmani, Raoudha AU - Chahbani, Iheb AU - Zargouni, Houcine AU - Abid, Syrine AU - Ayari, Mokdad AU - ben Ameur, Ines AU - Gasmi, Ali AU - ben Halima, Nejeh AU - Haouala, Habib AU - Boughzela, Essia AU - Zakhama, Lilia AU - ben Youssef, Soraya AU - Nasraoui, Wided AU - Boujnah, Rachid Mohamed AU - Barakett, Nadia AU - Kraiem, Sondes AU - Drissa, Habiba AU - Ben Khalfallah, Ali AU - Gamra, Habib AU - Kachboura, Salem AU - Bezdah, Leila AU - Baccar, Hedi AU - Milouchi, Sami AU - Sdiri, Wissem AU - Ben Omrane, Skander AU - Abdesselem, Salem AU - Kanoun, Alifa AU - Hezbri, Karima AU - Zannad, Faiez AU - Mebazaa, Alexandre AU - Kammoun, Samir AU - Mourali, Sami Mohamed AU - Addad, Faouzi PY - 2021/10/27 TI - Design and Rationale of the National Tunisian Registry of Heart Failure (NATURE-HF): Protocol for a Multicenter Registry Study JO - JMIR Res Protoc SP - e12262 VL - 10 IS - 10 KW - heart failure KW - acute heart failure KW - chronic heart failure KW - diagnosis KW - prognosis KW - treatment N2 - Background: The frequency of heart failure (HF) in Tunisia is on the rise and has now become a public health concern. This is mainly due to an aging Tunisian population (Tunisia has one of the oldest populations in Africa as well as the highest life expectancy in the continent) and an increase in coronary artery disease and hypertension. However, no extensive data are available on demographic characteristics, prognosis, and quality of care of patients with HF in Tunisia (nor in North Africa). Objective: The aim of this study was to analyze, follow, and evaluate patients with HF in a large nation-wide multicenter trial. Methods: A total of 1700 patients with HF diagnosed by the investigator will be included in the National Tunisian Registry of Heart Failure study (NATURE-HF). Patients must visit the cardiology clinic 1, 3, and 12 months after study inclusion. This follow-up is provided by the investigator. All data are collected via the DACIMA Clinical Suite web interface. Results: At the end of the study, we will note the occurrence of cardiovascular death (sudden death, coronary artery disease, refractory HF, stroke), death from any cause (cardiovascular and noncardiovascular), and the occurrence of a rehospitalization episode for an HF relapse during the follow-up period. Based on these data, we will evaluate the demographic characteristics of the study patients, the characteristics of pathological antecedents, and symptomatic and clinical features of HF. In addition, we will report the paraclinical examination findings such as the laboratory standard parameters and brain natriuretic peptides, electrocardiogram or 24-hour Holter monitoring, echocardiography, and coronarography. We will also provide a description of the therapeutic environment and therapeutic changes that occur during the 1-year follow-up of patients, adverse events following medical treatment and intervention during the 3- and 12-month follow-up, the evaluation of left ventricular ejection fraction during the 3- and 12-month follow-up, the overall rate of rehospitalization over the 1-year follow-up for an HF relapse, and the rate of rehospitalization during the first 3 months after inclusion into the study. Conclusions: The NATURE-HF study will fill a significant gap in the dynamic landscape of HF care and research. It will provide unique and necessary data on the management and outcomes of patients with HF. This study will yield the largest contemporary longitudinal cohort of patients with HF in Tunisia. Trial Registration: ClinicalTrials.gov NCT03262675; https://clinicaltrials.gov/ct2/show/NCT03262675 International Registered Report Identifier (IRRID): DERR1-10.2196/12262 UR - https://www.researchprotocols.org/2021/10/e12262 UR - http://dx.doi.org/10.2196/12262 UR - http://www.ncbi.nlm.nih.gov/pubmed/34704958 ID - info:doi/10.2196/12262 ER - TY - JOUR AU - Bente, E. Britt AU - Wentzel, Jobke AU - Groeneveld, GH Rik AU - IJzerman, VH Renée AU - de Buisonjé, R. David AU - Breeman, D. Linda AU - Janssen, R. Veronica AU - Kraaijenhagen, Roderik AU - Pieterse, E. Marcel AU - Evers, WM Andrea AU - van Gemert-Pijnen, EWC Julia PY - 2021/10/22 TI - Values of Importance to Patients With Cardiovascular Disease as a Foundation for eHealth Design and Evaluation: Mixed Methods Study JO - JMIR Cardio SP - e33252 VL - 5 IS - 2 KW - patient values KW - health behavior KW - lifestyle KW - mobile app KW - user-centered design KW - eHealth KW - cardiovascular disease KW - behavior KW - app KW - design KW - cardiovascular KW - evaluation KW - platform KW - support KW - intervention N2 - Background: eHealth interventions are developed to support and facilitate patients with lifestyle changes and self-care tasks after being diagnosed with a cardiovascular disease (CVD). Creating long-lasting effects on lifestyle change and health outcomes with eHealth interventions is challenging and requires good understanding of patient values. Objective: The aim of the study was to identify values of importance to patients with CVD to aid in designing a technological lifestyle platform. Methods: A mixed method?design was applied,?combining?data from usability testing?with an additional online survey study, to validate?the outcomes of the usability tests. Results: A total of 11 relevant patient values were identified, including the need for security, support, not wanting to feel anxious, tailoring of treatment, and personalized, accessible care. The validation survey shows that all values but one (value 9: To have extrinsic motivation to accomplish goals or activities [related to health/lifestyle]) were regarded as important/very important. A rating of very unimportant or unimportant was given by less than 2% of the respondents (value 1: 4/641, 0.6%; value 2: 10/641, 1.6%; value 3: 9/641, 1.4%; value 4: 5/641, 0.8%; value 5: 10/641, 1.6%; value 6: 4/641, 0.6%; value 7: 10/639, 1.6%; value 8: 4/639, 0.6%; value 10: 3/636, 0.5%; value 11: 4/636, 0.6%) to all values except but one (value 9: 56/636, 8.8%). Conclusions: There is a high consensus among patients regarding the identified values reflecting goals and themes central to their lives, while living with or managing their CVD. The identified values can serve as a foundation for future research to translate and integrate these values into the design of the eHealth technology. This may call for prioritization of values, as not all values can be met equally. UR - https://cardio.jmir.org/2021/2/e33252 UR - http://dx.doi.org/10.2196/33252 UR - http://www.ncbi.nlm.nih.gov/pubmed/34677130 ID - info:doi/10.2196/33252 ER - TY - JOUR AU - Tahri Sqalli, Mohammed AU - Al-Thani, Dena AU - Elshazly, B. Mohamed AU - Al-Hijji, ?Mohammed PY - 2021/10/14 TI - Interpretation of a 12-Lead Electrocardiogram by Medical Students: Quantitative Eye-Tracking Approach JO - JMIR Med Educ SP - e26675 VL - 7 IS - 4 KW - eye tracking KW - electrocardiogram KW - ECG interpretation KW - medical education KW - human-computer interaction KW - medical student KW - eye KW - tracking KW - interpretation KW - ECG N2 - Background: Accurate interpretation of a 12-lead electrocardiogram (ECG) demands high levels of skill and expertise. Early training in medical school plays an important role in building the ECG interpretation skill. Thus, understanding how medical students perform the task of interpretation is important for improving this skill. Objective: We aimed to use eye tracking as a tool to research how eye fixation can be used to gain a deeper understanding of how medical students interpret ECGs. Methods: In total, 16 medical students were recruited to interpret 10 different ECGs each. Their eye movements were recorded using an eye tracker. Fixation heatmaps of where the students looked were generated from the collected data set. Statistical analysis was conducted on the fixation count and duration using the Mann-Whitney U test and the Kruskal-Wallis test. Results: The average percentage of correct interpretations was 55.63%, with an SD of 4.63%. After analyzing the average fixation duration, we found that medical students study the three lower leads (rhythm strips) the most using a top-down approach: lead II (mean=2727 ms, SD=456), followed by leads V1 (mean=1476 ms, SD=320) and V5 (mean=1301 ms, SD=236). We also found that medical students develop a personal system of interpretation that adapts to the nature and complexity of the diagnosis. In addition, we found that medical students consider some leads as their guiding point toward finding a hint leading to the correct interpretation. Conclusions: The use of eye tracking successfully provides a quantitative explanation of how medical students learn to interpret a 12-lead ECG. UR - https://mededu.jmir.org/2021/4/e26675 UR - http://dx.doi.org/10.2196/26675 UR - http://www.ncbi.nlm.nih.gov/pubmed/34647899 ID - info:doi/10.2196/26675 ER - TY - JOUR AU - Schukraft, Sara AU - Boukhayma, Assim AU - Cook, Stéphane AU - Caizzone, Antonino PY - 2021/10/7 TI - Remote Blood Pressure Monitoring With a Wearable Photoplethysmographic Device (Senbiosys): Protocol for a Single-Center Prospective Clinical Trial JO - JMIR Res Protoc SP - e30051 VL - 10 IS - 10 KW - continuous blood pressure monitoring KW - photoplethysmography KW - arterial line KW - Senbiosys KW - wearable devices KW - blood pressure KW - remote monitoring KW - continuous monitoring KW - mHealth KW - mobile health N2 - Background: Wearable devices can provide user-friendly, accurate, and continuous blood pressure (BP) monitoring to assess patients? vital signs and achieve remote patient management. Remote BP monitoring can substantially improve BP control. The newest cuffless BP monitoring devices have emerged in patient care using photoplethysmography. Objective: The Senbiosys trial aims to compare BP measurements of a new device capturing a photoplethysmography signal on the finger versus invasive measurements performed in patients with an arterial catheter in the intensive care unit (ICU) or referred for a coronarography at the Hospital of Fribourg. Methods: The Senbiosys study is a single-center, single-arm, prospective trial. The study population consists of adult patients undergoing coronarography or patients in the ICU with an arterial catheter in place. This study will enroll 35 adult patients, including 25 patients addressed for a coronarography and 10 patients in the ICU. The primary outcome is the assessment of mean bias (95% CI) for systolic BP, diastolic BP, and mean BP between noninvasive and invasive BP measurements. Secondary outcomes include a reliability index (Qualification Index) for BP epochs and count of qualified epochs. Results: Patient recruitment started in June 2021. Results are expected to be published by December 2021. Conclusions: The findings of the Senbiosys trial are expected to improve remote BP monitoring. The diagnosis and treatment of hypertension should benefit from these advancements. Trial Registration: ClinicalTrials.gov NCT04379986; https://clinicaltrials.gov/ct2/show/NCT04379986 International Registered Report Identifier (IRRID): PRR1-10.2196/30051 UR - https://www.researchprotocols.org/2021/10/e30051 UR - http://dx.doi.org/10.2196/30051 UR - http://www.ncbi.nlm.nih.gov/pubmed/34617912 ID - info:doi/10.2196/30051 ER - TY - JOUR AU - Roberts, J. Derek AU - Nagpal, K. Sudhir AU - Stelfox, T. Henry AU - Brandys, Tim AU - Corrales-Medina, Vicente AU - Dubois, Luc AU - McIsaac, I. Daniel PY - 2021/9/16 TI - Risk Factors for Surgical Site Infection After Lower Limb Revascularization Surgery in Adults With Peripheral Artery Disease: Protocol for a Systematic Review and Meta-analysis JO - JMIR Res Protoc SP - e28759 VL - 10 IS - 9 KW - lower limb revascularization surgery KW - peripheral artery disease KW - risk factors KW - surgical site infection KW - systematic review N2 - Background: Surgical site infections (SSIs) are common, costly, and associated with increased morbidity and potential mortality after lower limb revascularization surgery (ie, arterial bypass, endarterectomy, and patch angioplasty). Identifying evidence-informed risk factors for SSI in patients undergoing these surgeries is therefore important. Objective: The aim of this study is to conduct a systematic review and meta-analysis of prognostic studies to identify, synthesize, and determine the certainty in the cumulative evidence associated with reported risk factors for early and delayed SSI after lower limb revascularization surgery in adults with peripheral artery disease. Methods: We will search MEDLINE, Embase, the seven databases in Evidence-Based Medicine Reviews, review articles identified during the search, and included article bibliographies. We will include studies of adults (aged ?18 years) with peripheral artery disease that report odds ratios, risk ratios, or hazard ratios adjusted for the presence of other risk factors or confounding variables and relating the potential risk factor of interest to the development of SSI after lower limb revascularization surgery. We will exclude studies that did not adjust for confounding, exclusively examined certain high-risk patient cohorts, or included >20% of patients who underwent surgery for indications other than peripheral artery disease. The primary outcomes will be early (in-hospital or ?30 days) SSI and Szilagyi grade I (cellulitis involving the wound), grade II (infection involving subcutaneous tissue), and grade III (infection involving the vascular graft) SSI. Two investigators will independently extract data and evaluate the study risk of bias using the Quality in Prognosis Studies tool. Adjusted risk factor estimates with similar definitions will be pooled using DerSimonian and Laird random-effects models. Heterogeneity will be explored using stratified meta-analyses and meta-regression. Finally, we will use the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to determine certainty in the estimates of association between reported risk factors and the development of SSI. Results: The protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews). We will execute the peer-reviewed search strategy on June 30, 2021, and then complete the review of titles and abstracts and full-text articles by July 30, 2021, and September 15, 2021, respectively. We will complete the full-text study data extraction and risk of bias assessment by November 15, 2021. We anticipate that we will be able to submit the manuscript for peer review by January 30, 2022. Conclusions: This study will identify, synthesize, and determine the certainty in the cumulative evidence associated with risk factors for early and delayed SSI after lower limb revascularization surgery in patients with peripheral artery disease. The results will be used to inform practice, clinical practice statements and guidelines, and subsequent research. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021242557; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=242557 International Registered Report Identifier (IRRID): PRR1-10.2196/28759 UR - https://www.researchprotocols.org/2021/9/e28759 UR - http://dx.doi.org/10.2196/28759 UR - http://www.ncbi.nlm.nih.gov/pubmed/34161251 ID - info:doi/10.2196/28759 ER - TY - JOUR AU - Chi, Chien-Yu AU - Ao, Shuang AU - Winkler, Adrian AU - Fu, Kuan-Chun AU - Xu, Jie AU - Ho, Yi-Lwun AU - Huang, Chien-Hua AU - Soltani, Rohollah PY - 2021/9/13 TI - Predicting the Mortality and Readmission of In-Hospital Cardiac Arrest Patients With Electronic Health Records: A Machine Learning Approach JO - J Med Internet Res SP - e27798 VL - 23 IS - 9 KW - in-hospital cardiac arrest KW - 30-day mortality KW - 30-day readmission KW - machine learning KW - imbalanced dataset N2 - Background: In-hospital cardiac arrest (IHCA) is associated with high mortality and health care costs in the recovery phase. Predicting adverse outcome events, including readmission, improves the chance for appropriate interventions and reduces health care costs. However, studies related to the early prediction of adverse events of IHCA survivors are rare. Therefore, we used a deep learning model for prediction in this study. Objective: This study aimed to demonstrate that with the proper data set and learning strategies, we can predict the 30-day mortality and readmission of IHCA survivors based on their historical claims. Methods: National Health Insurance Research Database claims data, including 168,693 patients who had experienced IHCA at least once and 1,569,478 clinical records, were obtained to generate a data set for outcome prediction. We predicted the 30-day mortality/readmission after each current record (ALL-mortality/ALL-readmission) and 30-day mortality/readmission after IHCA (cardiac arrest [CA]-mortality/CA-readmission). We developed a hierarchical vectorizer (HVec) deep learning model to extract patients? information and predict mortality and readmission. To embed the textual medical concepts of the clinical records into our deep learning model, we used Text2Node to compute the distributed representations of all medical concept codes as a 128-dimensional vector. Along with the patient?s demographic information, our novel HVec model generated embedding vectors to hierarchically describe the health status at the record-level and patient-level. Multitask learning involving two main tasks and auxiliary tasks was proposed. As CA-mortality and CA-readmission were rare, person upsampling of patients with CA and weighting of CA records were used to improve prediction performance. Results: With the multitask learning setting in the model learning process, we achieved an area under the receiver operating characteristic of 0.752 for CA-mortality, 0.711 for ALL-mortality, 0.852 for CA-readmission, and 0.889 for ALL-readmission. The area under the receiver operating characteristic was improved to 0.808 for CA-mortality and 0.862 for CA-readmission after solving the extremely imbalanced issue for CA-mortality/CA-readmission by upsampling and weighting. Conclusions: This study demonstrated the potential of predicting future outcomes for IHCA survivors by machine learning. The results showed that our proposed approach could effectively alleviate data imbalance problems and train a better model for outcome prediction. UR - https://www.jmir.org/2021/9/e27798 UR - http://dx.doi.org/10.2196/27798 UR - http://www.ncbi.nlm.nih.gov/pubmed/34515639 ID - info:doi/10.2196/27798 ER - TY - JOUR AU - Kim, Woong Ji AU - Ha, Juhyung AU - Kim, Taerim AU - Yoon, Hee AU - Hwang, Yeon Sung AU - Jo, Joon Ik AU - Shin, Gun Tae AU - Sim, Seob Min AU - Kim, Kyunga AU - Cha, Chul Won PY - 2021/7/5 TI - Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea JO - J Med Internet Res SP - e28361 VL - 23 IS - 7 KW - out-of-hospital cardiac arrest KW - Republic of Korea KW - machine learning KW - artificial intelligence KW - prognosis KW - cardiology KW - prediction model N2 - Background: Out-of-hospital cardiac arrest (OHCA) is a serious public health issue, and predicting the prognosis of OHCA patients can assist clinicians in making decisions about the treatment of patients, use of hospital resources, or termination of resuscitation. Objective: This study aimed to develop a time-adaptive conditional prediction model (TACOM) to predict clinical outcomes every minute. Methods: We performed a retrospective observational study using data from the Korea OHCA Registry in South Korea. In this study, we excluded patients with trauma, those who experienced return of spontaneous circulation before arriving in the emergency department (ED), and those who did not receive cardiopulmonary resuscitation (CPR) in the ED. We selected patients who received CPR in the ED. To develop the time-adaptive prediction model, we organized the training data set as ongoing CPR patients by the minute. A total of 49,669 patients were divided into 39,602 subjects for training and 10,067 subjects for validation. We compared random forest, LightGBM, and artificial neural networks as the prediction model methods. Model performance was quantified using the prediction probability of the model, area under the receiver operating characteristic curve (AUROC), and area under the precision recall curve. Results: Among the three algorithms, LightGBM showed the best performance. From 0 to 30 min, the AUROC of the TACOM for predicting good neurological outcomes ranged from 0.910 (95% CI 0.910-0.911) to 0.869 (95% CI 0.865-0.871), whereas that for survival to hospital discharge ranged from 0.800 (95% CI 0.797-0.800) to 0.734 (95% CI 0.736-0.740). The prediction probability of the TACOM showed similar flow with cohort data based on a comparison with the conventional model?s prediction probability. Conclusions: The TACOM predicted the clinical outcome of OHCA patients per minute. This model for predicting patient outcomes by the minute can assist clinicians in making rational decisions for OHCA patients. UR - https://www.jmir.org/2021/7/e28361/ UR - http://dx.doi.org/10.2196/28361 UR - http://www.ncbi.nlm.nih.gov/pubmed/36260382 ID - info:doi/10.2196/28361 ER - TY - JOUR AU - Keim-Malpass, Jessica AU - Ratcliffe, J. Sarah AU - Moorman, P. Liza AU - Clark, T. Matthew AU - Krahn, N. Katy AU - Monfredi, J. Oliver AU - Hamil, Susan AU - Yousefvand, Gholamreza AU - Moorman, Randall J. AU - Bourque, M. Jamieson PY - 2021/7/2 TI - Predictive Monitoring?Impact in Acute Care Cardiology Trial (PM-IMPACCT): Protocol for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e29631 VL - 10 IS - 7 KW - predictive analytics monitoring KW - AI KW - randomized controlled trial KW - risk estimation KW - clinical deterioration KW - visual analytics KW - artificial intelligence KW - monitoring KW - risk KW - prediction KW - impact KW - cardiology KW - acute care N2 - Background: Patients in acute care wards who deteriorate and are emergently transferred to intensive care units (ICUs) have poor outcomes. Early identification of patients who are decompensating might allow for earlier clinical intervention and reduced morbidity and mortality. Advances in bedside continuous predictive analytics monitoring (ie, artificial intelligence [AI]?based risk prediction) have made complex data easily available to health care providers and have provided early warning of potentially catastrophic clinical events. We present a dynamic, visual, predictive analytics monitoring tool that integrates real-time bedside telemetric physiologic data into robust clinical models to estimate and communicate risk of imminent events. This tool, Continuous Monitoring of Event Trajectories (CoMET), has been shown in retrospective observational studies to predict clinical decompensation on the acute care ward. There is a need to more definitively study this advanced predictive analytics or AI monitoring system in a prospective, randomized controlled, clinical trial. Objective: The goal of this trial is to determine the impact of an AI-based visual risk analytic, CoMET, on improving patient outcomes related to clinical deterioration, response time to proactive clinical action, and costs to the health care system. Methods: We propose a cluster randomized controlled trial to test the impact of using the CoMET display in an acute care cardiology and cardiothoracic surgery hospital floor. The number of admissions to a room undergoing cluster randomization was estimated to be 10,424 over the 20-month study period. Cluster randomization based on bed number will occur every 2 months. The intervention cluster will have the CoMET score displayed (along with standard of care), while the usual care group will receive standard of care only. Results: The primary outcome will be hours free from events of clinical deterioration. Hours of acute clinical events are defined as time when one or more of the following occur: emergent ICU transfer, emergent surgery prior to ICU transfer, cardiac arrest prior to ICU transfer, emergent intubation, or death. The clinical trial began randomization in January 2021. Conclusions: Very few AI-based health analytics have been translated from algorithm to real-world use. This study will use robust, prospective, randomized controlled, clinical trial methodology to assess the effectiveness of an advanced AI predictive analytics monitoring system in incorporating real-time telemetric data for identifying clinical deterioration on acute care wards. This analysis will strengthen the ability of health care organizations to evolve as learning health systems, in which bioinformatics data are applied to improve patient outcomes by incorporating AI into knowledge tools that are successfully integrated into clinical practice by health care providers. Trial Registration: ClinicalTrials.gov NCT04359641; https://clinicaltrials.gov/ct2/show/NCT04359641 International Registered Report Identifier (IRRID): DERR1-10.2196/29631 UR - https://www.researchprotocols.org/2021/7/e29631 UR - http://dx.doi.org/10.2196/29631 UR - http://www.ncbi.nlm.nih.gov/pubmed/34043525 ID - info:doi/10.2196/29631 ER - TY - JOUR AU - Kerr, M. Kim AU - Elliott, Greg C. AU - Benza, L. Raymond AU - Channick, N. Richard AU - Chin, M. Kelly AU - Davis, Duane R. AU - Jain, Sonia AU - LaCroix, Z. Andrea AU - Madani, M. Michael AU - McLaughlin, V. Vallerie AU - Park, H. Myung AU - Tapson, F. Victor AU - Auger, R. William PY - 2021/5/25 TI - The United States Chronic Thromboembolic Pulmonary Hypertension Registry: Protocol for a Prospective, Longitudinal Study JO - JMIR Res Protoc SP - e25397 VL - 10 IS - 5 KW - CTEPH KW - pulmonary hypertension KW - pulmonary embolism KW - registry KW - surgical KW - nonsurgical KW - therapy KW - treatment N2 - Background: Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare sequela of acute pulmonary embolism that is treatable when recognized. Awareness of this disease has increased with recent advancements in therapeutic options, but delays in diagnosis remain common, and diagnostic and treatment guidelines are often not followed. Data gathered from international registries have improved our understanding of CTEPH, but these data may not be applicable to the US population owing to differences in demographics and medical practice patterns. Objective: The US CTEPH Registry (US-CTEPH-R) was developed to provide essential information to better understand the demographics, risk factors, evaluation, and treatment of CTEPH in the United States, as well as the short- and long-term outcomes of surgical and nonsurgical therapies in the modern treatment era. Methods: Thirty sites throughout the United States enrolled 750 subjects in this prospective, longitudinal, observational registry of patients newly diagnosed with CTEPH. Enrollment criteria included a mean pulmonary artery pressure ?25 mmHg by right heart catheterization and radiologic confirmation of CTEPH by a multidisciplinary adjudication committee. Following enrollment, subjects were followed biannually until the conclusion of the study. Quality of life surveys were administered at enrollment and biannually, and all other testing was at the discretion of the treating clinician. Details regarding surgical therapy, balloon pulmonary angioplasty, and medical therapy were collected at enrollment and at follow-up, as well as information related to health care utilization and survival. Results: Data from this registry will improve understanding of the demographics, risk factors, and treatment patterns of patients with CTEPH, and the longitudinal impact of therapies on quality of life, health care utilization, and survival. Conclusions: This manuscript details the methodology and design of the first large, prospective, longitudinal registry of patients with CTEPH in the United States. Trial Registration: ClinicalTrials.gov NCT02429284; https://www.clinicaltrials.gov/ct2/show/NCT02429284 International Registered Report Identifier (IRRID): DERR1-10.2196/25397 UR - https://www.researchprotocols.org/2021/5/e25397 UR - http://dx.doi.org/10.2196/25397 UR - http://www.ncbi.nlm.nih.gov/pubmed/33848258 ID - info:doi/10.2196/25397 ER - TY - JOUR AU - Remmele, Julia AU - Helm, Christian Paul AU - Oberhoffer-Fritz, Renate AU - Bauer, MM Ulrike AU - Pickardt, Thomas AU - Ewert, Peter AU - Tutarel, Oktay PY - 2021/5/13 TI - A National Comparative Investigation of Twins With Congenital Heart Defects for Neurodevelopmental Outcomes and Quality of Life (Same Same, but Different?): Protocol for a Prospective Observational Study JO - JMIR Res Protoc SP - e26404 VL - 10 IS - 5 KW - congenital heart defect KW - twin siblings with CHD KW - twin study KW - neurodevelopmental outcome KW - same same KW - cardiology KW - heart defect KW - twin N2 - Background: Due to the increased survival rates of patients with congenital heart defects (CHD), associated disorders are an increasing focus of research. Existing studies figured out an association between CHD and its treatment, and neurodevelopmental outcomes including motor competence impairments. All these studies, however, compared their test results with reference values or results of healthy control groups. This comparison is influenced by socioeconomic and genetic aspects, which do have a known impact on neurodevelopmental outcomes. Objective: This study protocol describes a setting that aims to find out the role of CHD and its treatments on neurodevelopmental outcomes, excluding socioeconomic and genetic aspects. Only a twin comparison provides the possibility to exclude these confounding factors. Methods: In a German-wide prospective cohort study, 129 twin siblings registered in the National Register for Congenital Heart Defects will undergo testing on cognitive function (Wechsler Intelligence Tests age-dependent: Wechsler Adult Intelligence Scale, fourth edition; Wechsler Intelligence Scale for Children, fifth edition; and Wechsler Preschool and Primary Scale of Intelligence, fourth edition) and motor competence (Movement Assessment Battery for Children, second edition). Additionally, the self-reported health-related quality of life (KINDL-R for children, Short Form 36 for adults) and the parent-reported strength and difficulties of the children (Strength and Difficulties Questionnaire, German version) will be assessed by standardized questionnaires. CHD data on the specific diagnosis, surgeries, transcatheter procedures, and additional medical information will be received from patient records. Results: The approval of the Medical Ethics Committee Charité Mitte was obtained in June 2018. After getting funded in April 2019, the first enrollment was in August 2019. The study is still ongoing until June 2022. Final results are expected in 2022. Conclusions: This study protocol provides an overview of the study design?s technical details, offering an option to exclude confounding factors on neurodevelopmental outcomes in patients with CHD. This will enable a specific analysis focusing on CHD and clinical treatments to differentiate in terms of neurodevelopmental outcomes of patients with CHD compared to twin siblings with healthy hearts. Finally, we aim to clearly define what is important to prevent patients with CHD in terms of neurodevelopmental impairments to be able to develop targeted prevention strategies for patients with CHD. Trial Registration: German Clinical Trials Register DRKS00021087; https://tinyurl.com/2rdw8w67 International Registered Report Identifier (IRRID): DERR1-10.2196/26404 UR - https://www.researchprotocols.org/2021/5/e26404 UR - http://dx.doi.org/10.2196/26404 UR - http://www.ncbi.nlm.nih.gov/pubmed/33983133 ID - info:doi/10.2196/26404 ER - TY - JOUR AU - Fraticelli, Laurie AU - Freyssenge, Julie AU - Claustre, Clément AU - Martinez, Mikaël AU - Redjaline, Abdesslam AU - Serre, Patrice AU - Bochaton, Thomas AU - El Khoury, Carlos PY - 2021/4/27 TI - Estimating the Proportion of COVID-19 Contacts Among Households Based on Individuals With Myocardial Infarction History: Cross-sectional Telephone Survey JO - JMIR Form Res SP - e26955 VL - 5 IS - 4 KW - COVID-19 KW - survey KW - myocardial infarction KW - cases KW - contacts KW - household KW - estimate KW - cross-sectional KW - cardiovascular KW - risk KW - symptom N2 - Background: Adults with cardiovascular diseases were disproportionately associated with an increased risk of a severe form of COVID-19 and all-cause mortality. Objective: The aims of this study are to report the associated symptoms for COVID-19 cases, to estimate the proportion of contacts, and to describe the clinical signs and behaviors among individuals with and without myocardial infarction history among cases and contacts. Methods: A 2-week cross-sectional telephone survey was conducted during the first lockdown period in France, from May 4 to 15, 2020. A total of 668 households participated, representing 703 individuals with pre-existing cardiovascular disease in the past 2 years and 849 individuals without myocardial infarction history. Results: High rates of compliance with health measures were self-reported, regardless of age or risk factors. There were 4 confirmed COVID-19 cases that were registered from 4 different households. Based on deductive assumptions of the 1552 individuals, 9.73% (n=151) were identified as contacts, of whom 71.52% (108/151) were asymptomatic. Among individuals with a myocardial infarction history, 2 were COVID-19 cases, and the estimated proportion of contacts was 8.68% (61/703), of whom 68.85% (42/61) were asymptomatic. The cases and contacts presented different symptoms, with more respiratory signs in those with a myocardial infarction history. Conclusions: The telephone survey could be a relevant tool for reporting the number of contacts during a limited period and in a limited territory based on the presence of associated symptoms and COVID-19 cases in the households. This study advanced our knowledge to better prepare for future crises. UR - https://formative.jmir.org/2021/4/e26955 UR - http://dx.doi.org/10.2196/26955 UR - http://www.ncbi.nlm.nih.gov/pubmed/33855968 ID - info:doi/10.2196/26955 ER - TY - JOUR AU - Zhang, Yaqi AU - Han, Yongxia AU - Gao, Peng AU - Mo, Yifu AU - Hao, Shiying AU - Huang, Jia AU - Ye, Fangfan AU - Li, Zhen AU - Zheng, Le AU - Yao, Xiaoming AU - Li, Xiaodong AU - Wang, Xiaofang AU - Huang, Chao-Jung AU - Jin, Bo AU - Zhang, Yani AU - Yang, Gabriel AU - Alfreds, T. Shaun AU - Kanov, Laura AU - Sylvester, G. Karl AU - Widen, Eric AU - Li, Licheng AU - Ling, Xuefeng PY - 2021/2/17 TI - Electronic Health Record?Based Prediction of 1-Year Risk of Incident Cardiac Dysrhythmia: Prospective Case-Finding Algorithm Development and Validation Study JO - JMIR Med Inform SP - e23606 VL - 9 IS - 2 KW - cardiac dysrhythmia KW - prospective case finding KW - risk stratification KW - electronic health records N2 - Background: Cardiac dysrhythmia is currently an extremely common disease. Severe arrhythmias often cause a series of complications, including congestive heart failure, fainting or syncope, stroke, and sudden death. Objective: The aim of this study was to predict incident arrhythmia prospectively within a 1-year period to provide early warning of impending arrhythmia. Methods: Retrospective (1,033,856 individuals enrolled between October 1, 2016, and October 1, 2017) and prospective (1,040,767 individuals enrolled between October 1, 2017, and October 1, 2018) cohorts were constructed from integrated electronic health records in Maine, United States. An ensemble learning workflow was built through multiple machine learning algorithms. Differentiating features, including acute and chronic diseases, procedures, health status, laboratory tests, prescriptions, clinical utilization indicators, and socioeconomic determinants, were compiled for incident arrhythmia assessment. The predictive model was retrospectively trained and calibrated using an isotonic regression method and was prospectively validated. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Results: The cardiac dysrhythmia case-finding algorithm (retrospective: AUROC 0.854; prospective: AUROC 0.827) stratified the population into 5 risk groups: 53.35% (555,233/1,040,767), 44.83% (466,594/1,040,767), 1.76% (18,290/1,040,767), 0.06% (623/1,040,767), and 0.003% (27/1,040,767) were in the very low-risk, low-risk, medium-risk, high-risk, and very high-risk groups, respectively; 51.85% (14/27) patients in the very high-risk subgroup were confirmed to have incident cardiac dysrhythmia within the subsequent 1 year. Conclusions: Our case-finding algorithm is promising for prospectively predicting 1-year incident cardiac dysrhythmias in a general population, and we believe that our case-finding algorithm can serve as an early warning system to allow statewide population-level screening and surveillance to improve cardiac dysrhythmia care. UR - http://medinform.jmir.org/2021/2/e23606/ UR - http://dx.doi.org/10.2196/23606 UR - http://www.ncbi.nlm.nih.gov/pubmed/33595452 ID - info:doi/10.2196/23606 ER - TY - JOUR AU - Stengl, Helena AU - Ganeshan, Ramanan AU - Hellwig, Simon AU - Blaszczyk, Edyta AU - Fiebach, B. Jochen AU - Nolte, H. Christian AU - Bauer, Axel AU - Schulz-Menger, Jeanette AU - Endres, Matthias AU - Scheitz, F. Jan PY - 2021/2/5 TI - Cardiomyocyte Injury Following Acute Ischemic Stroke: Protocol for a Prospective Observational Cohort Study JO - JMIR Res Protoc SP - e24186 VL - 10 IS - 2 KW - ischemic stroke KW - troponin T KW - myocardial ischemia KW - myocardial injury KW - stroke-heart syndrome KW - cardiac imaging techniques KW - magnetic resonance imaging KW - Takotsubo syndrome KW - autonomic nervous system N2 - Background: Elevated cardiac troponin, which indicates cardiomyocyte injury, is common after acute ischemic stroke and is associated with poor functional outcome. Myocardial injury is part of a broad spectrum of cardiac complications that may occur after acute ischemic stroke. Previous studies have shown that in most patients, the underlying mechanism of stroke-associated myocardial injury may not be a concomitant acute coronary syndrome. Evidence from animal research and clinical and neuroimaging studies suggest that functional and structural alterations in the central autonomic network leading to stress-mediated neurocardiogenic injury may be a key underlying mechanism (ie, stroke-heart syndrome). However, the exact pathophysiological cascade remains unclear, and the diagnostic and therapeutic implications are unknown. Objective: The aim of this CORONA-IS (Cardiomyocyte injury following Acute Ischemic Stroke) study is to quantify autonomic dysfunction and to decipher downstream cardiac mechanisms leading to myocardial injury after acute ischemic stroke. Methods: In this prospective, observational, single-center cohort study, 300 patients with acute ischemic stroke, confirmed via cerebral magnetic resonance imaging (MRI) and presenting within 48 hours of symptom onset, will be recruited during in-hospital stay. On the basis of high-sensitivity cardiac troponin levels and corresponding to the fourth universal definition of myocardial infarction, 3 groups are defined (ie, no myocardial injury [no cardiac troponin elevation], chronic myocardial injury [stable elevation], and acute myocardial injury [dynamic rise/fall pattern]). Each group will include approximately 100 patients. Study patients will receive routine diagnostic care. In addition, they will receive 3 Tesla cardiovascular MRI and transthoracic echocardiography within 5 days of symptom onset to provide myocardial tissue characterization and assess cardiac function, 20-min high-resolution electrocardiogram for analysis of cardiac autonomic function, and extensive biobanking. A follow-up for cardiovascular events will be conducted 3 and 12 months after inclusion. Results: After a 4-month pilot phase, recruitment began in April 2019. We estimate a recruitment period of approximately 3 years to include 300 patients with a complete cardiovascular MRI protocol. Conclusions: Stroke-associated myocardial injury is a common and relevant complication. Our study has the potential to provide a better mechanistic understanding of heart and brain interactions in the setting of acute stroke. Thus, it is essential to develop algorithms for recognizing patients at risk and to refine diagnostic and therapeutic procedures. Trial Registration: Clinicaltrials.gov NCT03892226; https://www.clinicaltrials.gov/ct2/show/NCT03892226. International Registered Report Identifier (IRRID): DERR1-10.2196/24186 UR - http://www.researchprotocols.org/2021/2/e24186/ UR - http://dx.doi.org/10.2196/24186 UR - http://www.ncbi.nlm.nih.gov/pubmed/33544087 ID - info:doi/10.2196/24186 ER - TY - JOUR AU - Lee, Seungwon AU - Doktorchik, Chelsea AU - Martin, Asher Elliot AU - D'Souza, Giles Adam AU - Eastwood, Cathy AU - Shaheen, Aziz Abdel AU - Naugler, Christopher AU - Lee, Joon AU - Quan, Hude PY - 2021/2/1 TI - Electronic Medical Record?Based Case Phenotyping for the Charlson Conditions: Scoping Review JO - JMIR Med Inform SP - e23934 VL - 9 IS - 2 KW - electronic medical records KW - Charlson comorbidity KW - EMR phenotyping KW - health services research N2 - Background: Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research. Objective: This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions. Methods: A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines. Results: A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule?based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance. Conclusions: Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed. UR - https://medinform.jmir.org/2021/2/e23934 UR - http://dx.doi.org/10.2196/23934 UR - http://www.ncbi.nlm.nih.gov/pubmed/33522976 ID - info:doi/10.2196/23934 ER - TY - JOUR AU - Fundikira, Said Lulu AU - Chillo, Pilly AU - van Laake, W. Linda AU - Mutagaywa, Kato Reuben AU - Schmidt, Floriaan Amand AU - Kamuhabwa, Appolinary AU - Kwesigabo, Gideon AU - Asselbergs, W. Folkert PY - 2021/1/21 TI - Risk Factors and Prevalence of Dilated Cardiomyopathy in Sub-Saharan Africa: Protocol for a Systematic Review JO - JMIR Res Protoc SP - e18229 VL - 10 IS - 1 KW - dilated cardiomyopathy KW - cardiomyopathy KW - heart failure KW - cardiovascular risk factors KW - sub-Saharan Africa N2 - Background: Cardiomyopathies, defined as diseases involving mainly the heart muscles, are linked to an estimated 5.9 of 100,000 deaths globally. In sub-Saharan Africa, cardiomyopathies constitute 21.4% of heart failure cases, with dilated cardiomyopathy (DCM) being the most common form. The etiology of DCM is heterogeneous and is broadly categorized as genetic or nongenetic, as well as a mixed disease in which genetics interact with intrinsic and environmental factors. Factors such as age, gender, family history, and ethnicity are nonmodifiable, whereas modifiable risk factors include poor nutrition, physical inactivity, and excessive alcohol consumption, among others. However, the relative contribution of the different risk factors to the etiology of DCM is not known in sub-Saharan Africa, and the prevalence of DCM among heart failure patients has not been systematically studied in the region. Objective: The aim of this review is to synthesize available literature from sub-Saharan Africa on the prevalence of DCM among patients with heart failure, as well as the literature on factors associated with DCM. This paper outlines the protocol that will be followed to conduct the systematic review. Methods: A limited search of the PubMed database will be performed to identify relevant keywords contained in the title, abstract, and subject descriptors using initial search terms ?heart failure,? ?cardiomyopathy,? and ?sub-Saharan Africa.? These search terms and their synonyms will then be used in an extensive search in PubMed, and will address the first research question on prevalence. To address the second research question on risk factors, the terms ?heart failure,? ?cardiomyopathy,? and ?cardiovascular risk factors? in ?Sub-Saharan Africa? will be used, listing them one by one. Articles published from 2000 and in the English language will be included. Indexed articles in PubMed and Embase will be included, as well as the first 300 articles retrieved from a Google Scholar search. Collected data will be organized in Endnote and then uploaded to the Rayyan web app for systematic reviews. Two reviewers will independently select articles against the inclusion criteria. Discrepancies in reviewer selections will be resolved by an arbitrator. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting systematic reviews will be applied. A map of sub-Saharan Africa with colors to show disease prevalence in each country will be included. For quantitative data, where possible, odds ratios (for categorical outcome data) or standardized mean differences (for continuous data) and their 95% CIs will be calculated. Results: The primary outcomes will be the prevalence of DCM among patients with heart failure and cardiovascular risk factors associated with DCM in sub-Saharan Africa. The literature search will begin on January 1, 2021, and data analysis is expected to be completed by April 30, 2021. Conclusions: This review will provide information on the current status of the prevalence and associated factors of DCM, and possibly identify gaps, including paucity of data or conflicting results that need to be addressed to improve our understanding of DCM in sub-Saharan Africa. International Registered Report Identifier (IRRID): PRR1-10.2196/18229 UR - http://www.researchprotocols.org/2021/1/e18229/ UR - http://dx.doi.org/10.2196/18229 UR - http://www.ncbi.nlm.nih.gov/pubmed/33475522 ID - info:doi/10.2196/18229 ER - TY - JOUR AU - Nozari, Younes AU - Geraiely, Babak AU - Alipasandi, Kian AU - Mortazavi, Hamideh Seyedeh AU - Omidi, Negar AU - Aghajani, Hassan AU - Amirzadegan, Alireza AU - Pourhoseini, Hamidreza AU - Salarifar, Mojtaba AU - Alidoosti, Mohammad AU - Haji-Zeinali, Ali-Mohammad AU - Nematipour, Ebrahim AU - Nomali, Mahin PY - 2020/12/16 TI - Time to Treatment and In-Hospital Major Adverse Cardiac Events Among Patients With ST-Segment Elevation Myocardial Infarction Who Underwent Primary Percutaneous Coronary Intervention (PCI) According to the 24/7 Primary PCI Service Registry in Iran: Cross-Sectional Study JO - Interact J Med Res SP - e20352 VL - 9 IS - 4 KW - ST-segment elevation myocardial infarction KW - time to treatment KW - percutaneous coronary intervention KW - registries KW - Iran N2 - Background: Performing primary percutaneous coronary intervention (PCI) as a preferred reperfusion strategy for patients with ST-segment elevation myocardial infarction (STEMI) may be associated with major adverse cardiocerebrovascular events (MACCEs). Thus, timely primary PCI has been emphasized in order to improve outcomes. Despite guideline recommendations on trying to reduce the door-to-balloon time to <90 minutes in order to reduce mortality, less attention has been paid to other components of time to treatment, such as the symptom-to-balloon time, as an indicator of the total ischemic time, which includes the symptom-to-door time and door-to-balloon time, in terms of clinical outcomes of patients with STEMI undergoing primary PCI. Objective: We aimed to determine the association between each component of time to treatment (ie, symptom-to-door time, door-to-balloon time, and symptom-to-balloon time) and in-hospital MACCEs among patients with STEMI who underwent primary PCI. Methods: In this observational study, according to a prospective primary PCI 24/7 service registry, adult patients with STEMI who underwent primary PCI in one of six catheterization laboratories of Tehran Heart Center from November 2015 to August 2019, were studied. The primary outcome was in-hospital MACCEs, which was a composite index consisting of cardiac death, revascularization (ie, target vessel revascularization/target lesion revascularization), myocardial infarction, and stroke. It was compared at different levels of time to treatment (ie, symptom-to-door and door-to-balloon time <90 and ?90 minutes, and symptom-to-balloon time <180 and ?180 minutes). Data were analyzed using SPSS software version 24 (IBM Corp), with descriptive statistics, such as frequency, percentage, mean, and standard deviation, and statistical tests, such as chi-square test, t test, and univariate and multivariate logistic regression analyses, and with a significance level of <.05 and 95% CIs for odds ratios (ORs). Results: Data from 2823 out of 3204 patients were analyzed (mean age of 59.6 years, SD 11.6 years; 79.5% male [n=2243]; completion rate: 88.1%). Low proportions of symptom-to-door time ?90 minutes and symptom-to-balloon time ?180 minutes were observed among the study patients (579/2823, 20.5% and 691/2823, 24.5%, respectively). Overall, 2.4% (69/2823) of the patients experienced in-hospital MACCEs, and cardiac death (45/2823, 1.6%) was the most common cardiac outcome. In the univariate analysis, the symptom-to-balloon time predicted in-hospital MACCEs (OR 2.2, 95% CI 1.1-4.4; P=.03), while the symptom-to-door time (OR 1.4, 95% CI 0.7-2.6; P=.34) and door-to-balloon time (OR 1.1, 95% CI 0.6-1.8, P=.77) were not associated with in-hospital MACCEs. In the multivariate analysis, only symptom-to-balloon time ?180 minutes was associated with in-hospital MACCEs and was a predictor of in-hospital MACCEs (OR 2.3, 95% CI 1.1-5.2; P=.04). Conclusions: A longer symptom-to-balloon time was the only component associated with higher in-hospital MACCEs in the present study. Efforts should be made to shorten the symptom-to-balloon time in order to improve in-hospital MACCEs. International Registered Report Identifier (IRRID): RR2-10.2196/13161 UR - http://www.i-jmr.org/2020/4/e20352/ UR - http://dx.doi.org/10.2196/20352 UR - http://www.ncbi.nlm.nih.gov/pubmed/33325826 ID - info:doi/10.2196/20352 ER - TY - JOUR AU - Reljin, Natasa AU - Posada-Quintero, F. Hugo AU - Eaton-Robb, Caitlin AU - Binici, Sophia AU - Ensom, Emily AU - Ding, Eric AU - Hayes, Anna AU - Riistama, Jarno AU - Darling, Chad AU - McManus, David AU - Chon, H. Ki PY - 2020/8/27 TI - Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study JO - JMIR Med Inform SP - e18715 VL - 8 IS - 8 KW - heart failure KW - transthoracic bioimpedance KW - heart rate variability KW - fluid accumulation KW - autonomic nervous system KW - machine learning KW - cardiology N2 - Background: Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, an assessment of autonomic function, can be used for detection of fluid accumulation in patients with acute decompensated heart failure. Objective: We aimed to evaluate the performance of transthoracic bioimpedance and heart rate variability parameters obtained using a fluid accumulation vest with carbon black?polydimethylsiloxane dry electrodes in a prospective clinical study (System for Heart Failure Identification Using an External Lung Fluid Device; SHIELD). Methods: We computed 15 parameters: 8 were calculated from the model to fit Cole-Cole plots from transthoracic bioimpedance measurements (extracellular, intracellular, intracellular-extracellular difference, and intracellular-extracellular parallel circuit resistances as well as fitting error, resonance frequency, tissue heterogeneity, and cellular membrane capacitance), and 7 were based on linear (mean heart rate, low-frequency components of heart rate variability, high-frequency components of heart rate variability, normalized low-frequency components of heart rate variability, normalized high-frequency components of heart rate variability) and nonlinear (principal dynamic mode index of sympathetic function, and principal dynamic mode index of parasympathetic function) analysis of heart rate variability. We compared the values of these parameters between 3 participant data sets: control (n=32, patients who did not have heart failure), baseline (n=23, patients with acute decompensated heart failure taken at the time of admittance to the hospital), and discharge (n=17, patients with acute decompensated heart failure taken at the time of discharge from hospital). We used several machine learning approaches to classify participants with fluid accumulation (baseline) and without fluid accumulation (control and discharge), termed with fluid and without fluid groups, respectively. Results: Among the 15 parameters, 3 transthoracic bioimpedance (extracellular resistance, R0; difference in extracellular-intracellular resistance, R0 ? R?, and tissue heterogeneity, ?) and 3 heart rate variability (high-frequency, normalized low-frequency, and normalized high-frequency components) parameters were found to be the most discriminatory between groups (patients with and patients without heart failure). R0 and R0 ? R? had significantly lower values for patients with heart failure than for those without heart failure (R0: P=.006; R0 ? R?: P=.001), indicating that a higher volume of fluids accumulated in the lungs of patients with heart failure. A cubic support vector machine model using the 5 parameters achieved an accuracy of 92% for with fluid and without fluid group classification. The transthoracic bioimpedance parameters were related to intra- and extracellular fluid, whereas the heart rate variability parameters were mostly related to sympathetic activation. Conclusions: This is useful, for instance, for an in-home diagnostic wearable to detect fluid accumulation. Results suggest that fluid accumulation, and subsequently acute decompensated heart failure detection, could be performed using transthoracic bioimpedance and heart rate variability measurements acquired with a wearable vest. UR - http://medinform.jmir.org/2020/8/e18715/ UR - http://dx.doi.org/10.2196/18715 UR - http://www.ncbi.nlm.nih.gov/pubmed/32852277 ID - info:doi/10.2196/18715 ER - TY - JOUR AU - Essay, Patrick AU - Balkan, Baran AU - Subbian, Vignesh PY - 2020/8/7 TI - Decompensation in Critical Care: Early Prediction of Acute Heart Failure Onset JO - JMIR Med Inform SP - e19892 VL - 8 IS - 8 KW - critical care KW - heart failure KW - intensive care units KW - machine learning KW - time series KW - heart KW - cardiology KW - prediction KW - chronic disease KW - ICU KW - intensive care unit N2 - Background: Heart failure is a leading cause of mortality and morbidity worldwide. Acute heart failure, broadly defined as rapid onset of new or worsening signs and symptoms of heart failure, often requires hospitalization and admission to the intensive care unit (ICU). This acute condition is highly heterogeneous and less well-understood as compared to chronic heart failure. The ICU, through detailed and continuously monitored patient data, provides an opportunity to retrospectively analyze decompensation and heart failure to evaluate physiological states and patient outcomes. Objective: The goal of this study is to examine the prevalence of cardiovascular risk factors among those admitted to ICUs and to evaluate combinations of clinical features that are predictive of decompensation events, such as the onset of acute heart failure, using machine learning techniques. To accomplish this objective, we leveraged tele-ICU data from over 200 hospitals across the United States. Methods: We evaluated the feasibility of predicting decompensation soon after ICU admission for 26,534 patients admitted without a history of heart failure with specific heart failure risk factors (ie, coronary artery disease, hypertension, and myocardial infarction) and 96,350 patients admitted without risk factors using remotely monitored laboratory, vital signs, and discrete physiological measurements. Multivariate logistic regression and random forest models were applied to predict decompensation and highlight important features from combinations of model inputs from dissimilar data. Results: The most prevalent risk factor in our data set was hypertension, although most patients diagnosed with heart failure were admitted to the ICU without a risk factor. The highest heart failure prediction accuracy was 0.951, and the highest area under the receiver operating characteristic curve was 0.9503 with random forest and combined vital signs, laboratory values, and discrete physiological measurements. Random forest feature importance also highlighted combinations of several discrete physiological features and laboratory measures as most indicative of decompensation. Timeline analysis of aggregate vital signs revealed a point of diminishing returns where additional vital signs data did not continue to improve results. Conclusions: Heart failure risk factors are common in tele-ICU data, although most patients that are diagnosed with heart failure later in an ICU stay presented without risk factors making a prediction of decompensation critical. Decompensation was predicted with reasonable accuracy using tele-ICU data, and optimal data extraction for time series vital signs data was identified near a 200-minute window size. Overall, results suggest combinations of laboratory measurements and vital signs are viable for early and continuous prediction of patient decompensation. UR - http://medinform.jmir.org/2020/8/e19892/ UR - http://dx.doi.org/10.2196/19892 UR - http://www.ncbi.nlm.nih.gov/pubmed/32663162 ID - info:doi/10.2196/19892 ER - TY - JOUR AU - Montvida, Olga AU - Dibato, Epoh John AU - Paul, Sanjoy PY - 2020/6/3 TI - Evaluating the Representativeness of US Centricity Electronic Medical Records With Reports From the Centers for Disease Control and Prevention: Comparative Study on Office Visits and Cardiometabolic Conditions JO - JMIR Med Inform SP - e17174 VL - 8 IS - 6 KW - electronic medical records KW - observational study KW - epidemiology KW - population health N2 - Background: Electronic medical record (EMR)?based clinical and epidemiological research has dramatically increased over the last decade, although establishing the generalizability of such big databases for conducting epidemiological studies has been an ongoing challenge. To draw meaningful inferences from such studies, it is essential to fully understand the characteristics of the underlying population and potential biases in EMRs. Objective: This study aimed to assess the generalizability and representativity of the widely used US Centricity Electronic Medical Record (CEMR), a primary and ambulatory care EMR for population health research, using data from the National Ambulatory Medical Care Surveys (NAMCS) and the National Health and Nutrition Examination Surveys (NHANES). Methods: The number of office visits reported in the NAMCS, designed to meet the need for objective and reliable information about the provision and the use of ambulatory medical care services, was compared with similar data from the CEMR. The distribution of major cardiometabolic diseases in the NHANES, designed to assess the health and nutritional status of adults and children in the United States, was compared with similar data from the CEMR. Results: Gender and ethnicity distributions were similar between the NAMCS and the CEMR. Younger patients (aged <15 years) were underrepresented in the CEMR compared with the NAMCS. The number of office visits per 100 persons per year was similar: 277.9 (95% CI 259.3-296.5) in the NAMCS and 284.6 (95% CI 284.4-284.7) in the CEMR. However, the number of visits for males was significantly higher in the CEMR (CEMR: 270.8 and NAMCS: 239.0). West and South regions were underrepresented and overrepresented, respectively, in the CEMR. The overall prevalence of diabetes along with age and gender distribution was similar in the CEMR and the NHANES: overall prevalence, 10.1% and 9.7%; male, 11.5% and 10.8%; female, 9.1% and 8.8%; age 20 to 40 years, 2.5% and 1.8%; and age 40 to 60 years, 9.4% and 11.1%, respectively. The prevalence of obesity was similar: 42.1% and 39.6%, with similar age and female distribution (41.5% and 41.1%) but different male distribution (42.7% and 37.9%). The overall prevalence of high cholesterol along with age and female distribution was similar in the CEMR and the NHANES: overall prevalence, 12.4% and 12.4%; and female, 14.8% and 13.2%, respectively. The overall prevalence of hypertension was significantly higher in the CEMR (33.5%) than in the NHANES (95% CI: 27.0%-31.0%). Conclusions: The distribution of major cardiometabolic diseases in the CEMR is comparable with the national survey results. The CEMR represents the general US population well in terms of office visits and major chronic conditions, whereas the potential subgroup differences in terms of age and gender distribution and prevalence may differ and, therefore, should be carefully taken care of in future studies. UR - https://medinform.jmir.org/2020/6/e17174 UR - http://dx.doi.org/10.2196/17174 UR - http://www.ncbi.nlm.nih.gov/pubmed/32490850 ID - info:doi/10.2196/17174 ER - TY - JOUR AU - Lin, Chin-Sheng AU - Lin, Chin AU - Fang, Wen-Hui AU - Hsu, Chia-Jung AU - Chen, Sy-Jou AU - Huang, Kuo-Hua AU - Lin, Wei-Shiang AU - Tsai, Chien-Sung AU - Kuo, Chih-Chun AU - Chau, Tom AU - Yang, JH Stephen AU - Lin, Shih-Hua PY - 2020/3/5 TI - A Deep-Learning Algorithm (ECG12Net) for Detecting Hypokalemia and Hyperkalemia by Electrocardiography: Algorithm Development JO - JMIR Med Inform SP - e15931 VL - 8 IS - 3 KW - artificial intelligence KW - sudden cardiac death KW - electrocardiogram KW - machine learning KW - potassium homeostasis N2 - Background: The detection of dyskalemias?hypokalemia and hyperkalemia?currently depends on laboratory tests. Since cardiac tissue is very sensitive to dyskalemia, electrocardiography (ECG) may be able to uncover clinically important dyskalemias before laboratory results. Objective: Our study aimed to develop a deep-learning model, ECG12Net, to detect dyskalemias based on ECG presentations and to evaluate the logic and performance of this model. Methods: Spanning from May 2011 to December 2016, 66,321 ECG records with corresponding serum potassium (K+) concentrations were obtained from 40,180 patients admitted to the emergency department. ECG12Net is an 82-layer convolutional neural network that estimates serum K+ concentration. Six clinicians?three emergency physicians and three cardiologists?participated in human-machine competition. Sensitivity, specificity, and balance accuracy were used to evaluate the performance of ECG12Net with that of these physicians. Results: In a human-machine competition including 300 ECGs of different serum K+ concentrations, the area under the curve for detecting hypokalemia and hyperkalemia with ECG12Net was 0.926 and 0.958, respectively, which was significantly better than that of our best clinicians. Moreover, in detecting hypokalemia and hyperkalemia, the sensitivities were 96.7% and 83.3%, respectively, and the specificities were 93.3% and 97.8%, respectively. In a test set including 13,222 ECGs, ECG12Net had a similar performance in terms of sensitivity for severe hypokalemia (95.6%) and severe hyperkalemia (84.5%), with a mean absolute error of 0.531. The specificities for detecting hypokalemia and hyperkalemia were 81.6% and 96.0%, respectively. Conclusions: A deep-learning model based on a 12-lead ECG may help physicians promptly recognize severe dyskalemias and thereby potentially reduce cardiac events. UR - https://medinform.jmir.org/2020/3/e15931 UR - http://dx.doi.org/10.2196/15931 UR - http://www.ncbi.nlm.nih.gov/pubmed/32134388 ID - info:doi/10.2196/15931 ER - TY - JOUR AU - Napa, Sandeep AU - Moore, Michael AU - Bardyn, Tania PY - 2019/01/16 TI - Advancing Cardiac Surgery Case Planning and Case Review Conferences Using Virtual Reality in Medical Libraries: Evaluation of the Usability of Two Virtual Reality Apps JO - JMIR Hum Factors SP - e12008 VL - 6 IS - 1 KW - virtual reality KW - cardiac surgery KW - usability study KW - system usability score KW - NASA-Task Load Index KW - medical libraries KW - case planning KW - presurgical planning N2 - Background: Care providers and surgeons prepare for cardiac surgery using case conferences to review, discuss, and run through the surgical procedure. Surgeons visualize a patient?s anatomy to decide the right surgical approach using magnetic resonance imaging and echocardiograms in a presurgical case planning session. Previous studies have shown that surgical errors can be reduced through the effective use of immersive virtual reality (VR) to visualize patient anatomy. However, inconsistent user interfaces, delegation of view control, and insufficient depth information cause user disorientation and interaction difficulties in using VR apps for case planning. Objective: The objective of the study was to evaluate and compare the usability of 2 commercially available VR apps?Bosc (Pyrus Medical systems) and Medical Holodeck (Nooon Web & IT GmbH)?using the Vive VR headset (HTC Corporation) to evaluate ease of use, physician attitudes toward VR technology, and viability for presurgical case planning. The role of medical libraries in advancing case planning is also explored. Methods: After screening a convenience sample of surgeons, fellows, and residents, ethnographic interviews were conducted to understand physician attitudes and experience with VR. Gaps in current case planning methods were also examined. We ran a usability study, employing a concurrent think-aloud protocol. To evaluate user satisfaction, we used the system usability scale (SUS) and the National Aeronautics and Space Administration-Task Load Index (NASA-TLX). A poststudy questionnaire was used to evaluate the VR experience and explore the role of medical libraries in advancing presurgical case planning. Semistructured interview data were analyzed using content analysis with feedback categorization. Results: Participants were residents, fellows, and surgeons from the University of Washington with a mean age of 41.5 (SD 11.67) years. A total of 8 surgeons participated in the usability study, 3 of whom had prior exposure to VR. Users found Medical Holodeck easier to use than Bosc. Mean adjusted NASA-TLX score for Medical Holodeck was 62.71 (SD 18.25) versus Bosc?s 40.87 (SD 13.90). Neither app passed the mean SUS score of 68 for an app to be considered usable, though Medical Holodeck (66.25 [SD 12.87]) scored a higher mean SUS than Bosc (37.19 [SD 22.41]). One user rated the Bosc usable, whereas 3 users rated Medical Holodeck usable. Conclusions: Interviews highlighted the importance of precise anatomical conceptualization in presurgical case planning and teaching, identifying it as the top reason for modifying a surgical procedure. The importance of standardized user interaction features such as labeling is justified. The study also sheds light on the new roles medical librarians can play in curating VR content and promoting interdisciplinary collaboration. UR - http://humanfactors.jmir.org/2019/1/e12008/ UR - http://dx.doi.org/10.2196/12008 UR - http://www.ncbi.nlm.nih.gov/pubmed/30664469 ID - info:doi/10.2196/12008 ER - TY - JOUR AU - Alexander, P. Karen AU - Stadnyuk, Olena AU - Arnold, V. Suzanne AU - Mark, B. Daniel AU - Ohman, Magnus E. AU - Anstrom, J. Kevin PY - 2016/04/28 TI - Assessing Quality of Life and Medical Care in Chronic Angina: An Internet Survey JO - Interact J Med Res SP - e12 VL - 5 IS - 2 KW - Angina KW - Surveys and Questionnaires KW - Internet KW - Quality of Life N2 - Background: Angina is a clinical syndrome whose recognition relies heavily on self-report, so its identification can be challenging. Most data come from cohorts identified by physicians and nurses at the point of care; however, current widespread access to the Internet makes identification of community cohorts feasible and offers a complementary picture of angina. Objective: To describe a population self-identified as experiencing chronic angina by use of an Internet survey. Methods: Using email and an Internet portal, we invited individuals with a diagnosis of angina and recent symptoms to complete an Internet survey on treatment and quality of life (QOL). In total, 1147 surveys were received. The main analysis was further limited to those reporting a definite coronary heart disease (CHD) history (N=646, 56% of overall). Results: Overall, about 15% reported daily angina and 40% weekly angina. Those with more frequent angina were younger, more often depressed, and reported a shorter time since diagnosis. They also had substantially worse treatment satisfaction, physical function, and overall QOL. Fewer than 40% were on ? 2 anti-anginals, even with daily angina. The subjects without a history of definite CHD had unexpectedly low use of antianginal and evidence-based medicines, suggesting either a lack of specificity in the use of self-reported angina to identify patients with CHD or lack of access to care. Conclusions: Use of inexpensive electronic tools can identify community-based angina cohorts for clinical research. Limitation to subjects with a definite history of CHD lends diagnostic face validity to the approach; however, other symptomatic individuals are also identified. UR - http://www.i-jmr.org/2016/2/e12/ UR - http://dx.doi.org/10.2196/ijmr.4971 UR - http://www.ncbi.nlm.nih.gov/pubmed/27125492 ID - info:doi/10.2196/ijmr.4971 ER - TY - JOUR AU - Disler, T. Rebecca AU - Inglis, C. Sally AU - Newton, J. Phillip AU - Currow, C. David AU - Macdonald, S. Peter AU - Glanville, R. Allan AU - Donesky, DorAnne AU - Carrieri-Kohlman, Virginia AU - Davidson, M. Patricia PY - 2015/03/06 TI - Patterns of Technology Use in Patients Attending a Cardiopulmonary Outpatient Clinic: A Self-Report Survey JO - Interact J Med Res SP - e5 VL - 4 IS - 1 KW - chronic obstructive pulmonary disease KW - chronic disease KW - self-management KW - self-care KW - telemedicine, eHealth KW - mHealth N2 - Background: Self-management education for cardiopulmonary diseases is primarily provided through time-limited, face-to-face programs, with access limited to a small percentage of patients. Telecommunication tools will increasingly be an important component of future health care delivery. Objective: The purpose of this study was to describe the patterns of technology use in patients attending a cardiopulmonary clinic in an academic medical center. Methods: A prevalence survey was developed to collect data on participant demographics (age in years, sex, and socioeconomic status); access to computers, Internet, and mobile phones; and use of current online health support sites or programs. Surveys were offered by reception staff to all patients attending the outpatient clinic. Results: A total of 123 surveys were collected between March and April 2014. Technological devices were a pervasive part of everyday life with respondents engaged in regular computer (102/123, 82.9%), mobile telephone (115/117, 98.3%), and Internet (104/121, 86.0%) use. Emailing (101/121, 83.4%), researching and reading news articles (93/121, 76.9%), social media (71/121, 58.7%), and day-to-day activities (65/121, 53.7%) were the most common telecommunication activities. The majority of respondents reported that access to health support programs and assistance through the Internet (82/111, 73.9%) would be of use, with benefits reported as better understanding of health information (16/111, 22.5%), avoidance of difficult travel requirements and time-consuming face-to-face appointments (13/111, 18.3%), convenient and easily accessible help and information (12/111, 16.9%), and access to peer support and sharing (9/111, 12.7%). The majority of patients did not have concerns over participating in the online environment (87/111, 78.4%); the few concerns noted related to privacy and security (10/15), information accuracy (2/15), and computer literacy and access (2/15). Conclusions: Chronic disease burden and long-term self-management tasks provide a compelling argument for accessible and convenient avenues to obtaining ongoing treatment and peer support. Online access to health support programs and assistance was reported as useful and perceived as providing convenient, timely, and easily accessible health support and information. Distance from the health care facility and a lack of information provision through traditional health sources were both barriers and enablers to telehealth. This is particularly important in the context of a cardiopulmonary clinic that attracts patients from a large geographical area, and in patients who are most likely to have high health care utilization needs in the future. Telecommunication interfaces will be an increasingly important adjunct to traditional forms of health care delivery. UR - http://www.i-jmr.org/2015/1/e5/ UR - http://dx.doi.org/10.2196/ijmr.3955 UR - http://www.ncbi.nlm.nih.gov/pubmed/25798814 ID - info:doi/10.2196/ijmr.3955 ER - TY - JOUR AU - Luzi, Mario AU - De Simone, Antonio AU - Leoni, Loira AU - Amellone, Claudia AU - Pisanò, Ennio AU - Favale, Stefano AU - Iacoviello, Massimo AU - Luise, Raffaele AU - Bongiorni, Grazia Maria AU - Stabile, Giuseppe AU - La Rocca, Vincenzo AU - Folino, Franco AU - Capucci, Alessandro AU - D'Onofrio, Antonio AU - Accardi, Francesco AU - Valsecchi, Sergio AU - Buia, Gianfranco PY - 2013/09/20 TI - Remote Monitoring for Implantable Defibrillators: A Nationwide Survey in Italy JO - Interact J Med Res SP - e27 VL - 2 IS - 2 KW - implantable defibrillator KW - remote monitoring KW - follow-up N2 - Background: Remote monitoring (RM) permits home interrogation of implantable cardioverter defibrillator (ICD) and provides an alternative option to frequent in-person visits. Objective: The Italia-RM survey aimed to investigate the current practice of ICD follow-up in Italy and to evaluate the adoption and routine use of RM. Methods: An ad hoc questionnaire on RM adoption and resource use during in-clinic and remote follow-up sessions was completed in 206 Italian implanting centers. Results: The frequency of routine in-clinic ICD visits was 2 per year in 158/206 (76.7%) centers, 3 per year in 37/206 (18.0%) centers, and 4 per year in 10/206 (4.9%) centers. Follow-up examinations were performed by a cardiologist in 203/206 (98.5%) centers, and by more than one health care worker in 184/206 (89.3%) centers. There were 137/206 (66.5%) responding centers that had already adopted an RM system, the proportion of ICD patients remotely monitored being 15% for single- and dual-chamber ICD and 20% for cardiac resynchronization therapy ICD. Remote ICD interrogations were scheduled every 3 months, and were performed by a cardiologist in 124/137 (90.5%) centers. After the adoption of RM, the mean time between in-clinic visits increased from 5 (SD 1) to 8 (SD 3) months (P<.001). Conclusions: In current clinical practice, in-clinic ICD follow-up visits consume a large amount of health care resources. The results of this survey show that RM has only partially been adopted in Italy and, although many centers have begun to implement RM in their clinical practice, the majority of their patients continue to be routinely followed-up by means of in-clinic visits. UR - http://www.i-jmr.org/2013/2/e27/ UR - http://dx.doi.org/10.2196/ijmr.2824 UR - http://www.ncbi.nlm.nih.gov/pubmed/24055720 ID - info:doi/10.2196/ijmr.2824 ER -