TY - JOUR AU - Wu, Rong AU - Zhang, Yu AU - Huang, Peijie AU - Xie, Yiying AU - Wang, Jianxun AU - Wang, Shuangyong AU - Lin, Qiuxia AU - Bai, Yichen AU - Feng, Songfu AU - Cai, Nian AU - Lu, Xiaohe PY - 2025/4/23 TI - Prediction of Reactivation After Antivascular Endothelial Growth Factor Monotherapy for Retinopathy of Prematurity: Multimodal Machine Learning Model Study JO - J Med Internet Res SP - e60367 VL - 27 KW - retinopathy of prematurity KW - reactivation KW - prediction KW - machine learning KW - deep learning KW - anti-VEGF N2 - Background: Retinopathy of prematurity (ROP) is the leading preventable cause of childhood blindness. A timely intravitreal injection of antivascular endothelial growth factor (anti-VEGF) is required to prevent retinal detachment with consequent vision impairment and loss. However, anti-VEGF has been reported to be associated with ROP reactivation. Therefore, an accurate prediction of reactivation after treatment is urgently needed. Objective: To develop and validate prediction models for reactivation after anti-VEGF intravitreal injection in infants with ROP using multimodal machine learning algorithms. Methods: Infants with ROP undergoing anti-VEGF treatment were recruited from 3 hospitals, and conventional machine learning, deep learning, and fusion models were constructed. The areas under the curve (AUCs), accuracy, sensitivity, and specificity were used to show the performances of the prediction models. Results: A total of 239 cases with anti-VEGF treatment were recruited, including 90 (37.66%) with reactivation and 149 (62.34%) nonreactivation cases. The AUCs for the conventional machine learning model were 0.806 and 0.805 in the internal validation and test groups, respectively. The average AUC, sensitivity, and specificity in the test for the deep learning model were 0.787, 0.800, and 0.570, respectively. The specificity, AUC, and sensitivity for the fusion model were 0.686, 0.822, and 0.800 in a test, separately. Conclusions: We constructed 3 prediction models for ROP reactivation. The fusion model achieved the best performance. Using this prediction model, we could optimize strategies for treating ROP in infants and develop better screening plans after treatment. UR - https://www.jmir.org/2025/1/e60367 UR - http://dx.doi.org/10.2196/60367 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60367 ER - TY - JOUR AU - Amon, Daria AU - Leisser, Christoph AU - Schlatter, Andreas AU - Ruiss, Manuel AU - Pilwachs, Caroline AU - Bayer, Natascha AU - Huemer, Josef AU - Findl, Oliver PY - 2025/4/17 TI - Quantification of Metamorphopsia Using a Smartphone-Based Hyperacuity Test in Patients With Idiopathic Epiretinal Membranes: Prospective Observational Study JO - JMIR Perioper Med SP - e60959 VL - 8 KW - mobile health KW - smartphone KW - telemedicine KW - Alleye KW - M-chart KW - metamorphopsia KW - epiretinal membrane KW - vitrectomy with membrane peeling KW - visual acuity KW - home monitoring KW - hyperacuity test KW - hyperacuity KW - surgical intervention KW - distorted vision KW - vision KW - ocular pathology KW - ocular KW - retinal KW - retina KW - surgery KW - macular degeneration KW - tomography KW - vitrectomy KW - ophthalmology N2 - Background: Quality of vision in patients with idiopathic epiretinal membranes (iERMs) is closely linked to distorted vision (metamorphopsia), which is often underestimated in clinical settings. Current surgical decision-making relies heavily on visual acuity and optical coherence tomography findings, which do not adequately reflect the patient?s functional vision or the severity of metamorphopsia. There is a clinical need for tools that can reliably quantify this symptom to improve patient outcomes and streamline care pathways. Objectives: This study is the first to assess the use of a novel smartphone-based hyperacuity test (SHT) in quantifying metamorphopsia before and after surgical intervention for iERMs, comparing it with a conventional printed chart. Methods: This prospective observational study included 27 patients with iERMs with symptomatic metamorphopsia detected on the Amsler grid scheduled for vitrectomy with membrane peeling. The SHT (Alleye, Oculocare Medical Inc) and the horizontal (MH) and vertical (MV) M-chart (Inami & Co, Ltd) tests were performed 3 times before and 3 months after surgery. Pre- and postoperative metamorphopsia scores, changes in distance-corrected visual acuity, optical coherence tomography biomarkers, and subjective perception of metamorphopsia were evaluated. Results: The mean SHT score significantly (r=0.686; P<.001) improved from 55.2 (SD 18.9) before surgery to 63.5 (SD 16.3) after surgery while the improvement of the M-chart scores were insignificant (MH r=0.37, P=.06; MV r=0.18, P=.36). Pre- and postoperative SHT scores showed very weak and insignificant correlations with the MH, MV, and MH+MV scores. Both metamorphopsia tests showed good reliability (intraclass correlation coefficients >0.75). Conclusions: The SHT showed a significant improvement in postoperative metamorphopsia scores, indicating that it could be a valuable tool for quantifying visual distortion in patients with iERMs. While discrepancies with M-chart results were observed, both tests demonstrated good reliability. Clinically, the SHT may offer a practical solution for monitoring metamorphopsia and guiding complex surgical decision-making, particularly in telemedicine settings. Its accessibility could improve patient management, potentially enhancing preoperative triaging and reducing unnecessary visits. Trial Registration: ClinicalTrials.gov NCT05138315; https://clinicaltrials.gov/study/NCT05138315 UR - https://periop.jmir.org/2025/1/e60959 UR - http://dx.doi.org/10.2196/60959 ID - info:doi/10.2196/60959 ER - TY - JOUR AU - Wei, Bin AU - Yao, Lili AU - Hu, Xin AU - Hu, Yuxiang AU - Rao, Jie AU - Ji, Yu AU - Dong, Zhuoer AU - Duan, Yichong AU - Wu, Xiaorong PY - 2025/4/10 TI - Evaluating the Effectiveness of Large Language Models in Providing Patient Education for Chinese Patients With Ocular Myasthenia Gravis: Mixed Methods Study JO - J Med Internet Res SP - e67883 VL - 27 KW - LLM KW - large language models KW - ocular myasthenia gravis KW - patient education KW - China KW - effectiveness KW - deep learning KW - artificial intelligence KW - health care KW - accuracy KW - applicability KW - neuromuscular disorder KW - extraocular muscles KW - ptosis KW - diplopia KW - ophthalmology KW - ChatGPT KW - clinical practice KW - digital health N2 - Background: Ocular myasthenia gravis (OMG) is a neuromuscular disorder primarily affecting the extraocular muscles, leading to ptosis and diplopia. Effective patient education is crucial for disease management; however, in China, limited health care resources often restrict patients? access to personalized medical guidance. Large language models (LLMs) have emerged as potential tools to bridge this gap by providing instant, AI-driven health information. However, their accuracy and readability in educating patients with OMG remain uncertain. Objective: The purpose of this study was to systematically evaluate the effectiveness of multiple LLMs in the education of Chinese patients with OMG. Specifically, the validity of these models in answering patients with OMG-related questions was assessed through accuracy, completeness, readability, usefulness, and safety, and patients? ratings of their usability and readability were analyzed. Methods: The study was conducted in two phases: 130 choice ophthalmology examination questions were input into 5 different LLMs. Their performance was compared with that of undergraduates, master?s students, and ophthalmology residents. In addition, 23 common patients with OMG-related patient questions were posed to 4 LLMs, and their responses were evaluated by ophthalmologists across 5 domains. In the second phase, 20 patients with OMG interacted with the 2 LLMs from the first phase, each asking 3 questions. Patients assessed the responses for satisfaction and readability, while ophthalmologists evaluated the responses again using the 5 domains. Results: ChatGPT o1-preview achieved the highest accuracy rate of 73% on 130 ophthalmology examination questions, outperforming other LLMs and professional groups like undergraduates and master?s students. For 23 common patients with OMG-related questions, ChatGPT o1-preview scored highest in correctness (4.44), completeness (4.44), helpfulness (4.47), and safety (4.6). GEMINI (Google DeepMind) provided the easiest-to-understand responses in readability assessments, while GPT-4o had the most complex responses, suitable for readers with higher education levels. In the second phase with 20 patients with OMG, ChatGPT o1-preview received higher satisfaction scores than Ernie 3.5 (Baidu; 4.40 vs 3.89, P=.002), although Ernie 3.5?s responses were slightly more readable (4.31 vs 4.03, P=.01). Conclusions: LLMs such as ChatGPT o1-preview may have the potential to enhance patient education. Addressing challenges such as misinformation risk, readability issues, and ethical considerations is crucial for their effective and safe integration into clinical practice. UR - https://www.jmir.org/2025/1/e67883 UR - http://dx.doi.org/10.2196/67883 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/67883 ER - TY - JOUR AU - Liu, Hongji AU - Dai, Yan AU - Yu, Ming AU - Zeng, Jian AU - Wang, Chao AU - Tan, Sa AU - Xiong, Ming AU - Zhang, Ran AU - Yu, Xuemeng AU - Shi, Mingsong AU - Yan, Xing AU - Lai, Fengming PY - 2025/4/1 TI - Effects and Safety of Press-Needle Therapy for Improving Visual Function and Eye Blood Circulation in Patients With Glaucoma With Controlled Intraocular Pressure: Study Protocol for a Multicenter Randomized Controlled Trial JO - JMIR Res Protoc SP - e67737 VL - 14 KW - press needle KW - press-needle therapy KW - needling technique KW - glaucoma KW - acupuncture KW - visual function KW - eye blood circulation KW - randomized controlled trial KW - traditional Chinese medecine N2 - Background: Glaucoma is the leading cause of irreversible blindness worldwide, causing continuous and progressively worsening damage to visual function, which leads to vision loss. Optic nerve protection is an important treatment for glaucoma with controlled intraocular pressure (GPCI), but to date, there is no universally accepted effective optic nerve protection agent. Acupuncture can protect the optic nerve by increasing blood flow to the eye. However, fear of pain or the limitations of treatment place and time lead to poor patient compliance. Press-needle therapy is a characteristic of traditional Chinese medicine (TCM) external treatment methods; its safety is high, the effect is fast and lasting, it is easy to conduct, and it has high patient compliance. Objective: The objective of the trial is to evaluate the safety and clinical efficacy of press-needle therapy and investigate whether it can improve visual function by regulating eye blood circulation in patients with GPCI. Methods: In total, 192 participants aged 18-75 years with GPCI from the Mianyang Central Hospital, the Mianyang Hospital of Traditional Chinese Medicine, and the Mianyang Wanjiang Eye Hospital will participate in this study. Participants will be allocated to 2 treatment groups (experimental and control groups) in a ratio of 1:1 and will undergo press-needle therapy and sham press-needle therapy, respectively, for the same 4-week period. Primary outcomes will include the best-corrected visual acuity (BCVA), optical coherence tomography angiography (OCTA), color Doppler flow imaging (CDFI), and visual field assessment results. Secondary outcomes will include the intraocular pressure (IOP) and traditional Chinese medicine (TCM) clinical symptom scales. The primary outcomes and safety assessments will be measured at baseline and 4 weeks thereafter, while the secondary outcomes will be measured at baseline and 1, 2, 3, and 4 weeks thereafter. Results: Recruitment and data collection began in February 2023. The final outcomes are expected in September 2025. As of October 2024, the project had recruited 220 eligible participants, of whom 192 (87.3%) will complete the study, exceeding initial projections for the study time frame. The remainder of the participants will provide the ability to explore cross-level interactions that could not be statistically powered at the outset. The strengths of the project include rigorous data collection, good retention rates, and high compliance rates. Conclusions: This study will provide data on the effects of press-needle therapy on visual function and ocular circulation in patients with GPCI, and these results will help demonstrate whether acupuncture can improve patients? visual function by regulating ocular circulation, thus providing a clinical and theoretical basis for the wider application of acupuncture therapy in GPCI. Trial Registration: Chinese Clinical Trial Registry ChiCTR2300067862?https://tinyurl.com/mrxd58x9 International Registered Report Identifier (IRRID): DERR1-10.2196/67737 UR - https://www.researchprotocols.org/2025/1/e67737 UR - http://dx.doi.org/10.2196/67737 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/67737 ER - TY - JOUR AU - Chauhan, Anshul AU - Goyal, Anju AU - Masih, Ritika AU - Kaur, Gagandeep AU - Kumar, Lakshay AU - Neha, ­. AU - Rastogi, Harsh AU - Kumar, Sonam AU - Singh, Lord Bidhi AU - Syal, Preeti AU - Gupta, Vishali AU - Vale, Luke AU - Duggal, Mona PY - 2025/3/31 TI - Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study JO - JMIR Form Res SP - e67047 VL - 9 KW - diabetic retinopathy KW - diabetes KW - gerontology KW - geriatric KW - old KW - aging KW - aged KW - artificial intelligence KW - retinopathy KW - retinal KW - referral KW - screening KW - optometry KW - ophthalmology KW - adherence KW - barriers N2 - Background: Diabetic retinopathy (DR) is a leading cause of blindness globally. DR has increasingly affected both individuals and health care systems as the population ages. Objective: This study aims to explore factors and identify barriers associated with nonadherence to referral recommendations among older adult participants after DR screening (DRS) during the COVID-19 pandemic. Method: This paper presents findings from a pilot study on artificial intelligence?enabled DRS conducted in two districts in Punjab, India (Moga and Mohali) during the COVID-19 pandemic. The screenings were conducted from March to June 2022 at community health center Badhani Kalan in Moga and from March to June 2021 in community settings (homes) in Block Boothgarh, Mohali. Participants were referred to the district hospital for an ophthalmological review based on artificial intelligence?enabled screening. After 1 month, the participants were contacted by telephone to assess adherence to the referral recommendations. Participants who did not adhere to the referral were then interviewed alongside health care providers to understand the barriers explaining their nonadherence. Results: We aimed to recruit 346 and 600 older adult participants from 2 sites but enrolled 390. Key challenges included health facility closures due to COVID-19, low motivation among health personnel for recruitment, incomplete nonparticipation data, and high participant workloads. Approximately 45% of the participants were male and 55% female. Most participants (62.6%) were between 60 and 69 years old, while 37.4% were 70 or older, with a mean age of 67.2 (SD 6.2) years. In total, 159 participants (40.8%) were referred, while 231 participants (59.2%) were not. Only 23 (14.5%) of those referred followed through and visited a health facility for ophthalmological review, while 136 (85.5%) did not pursue further evaluation. Our analysis revealed no significant differences in the characteristics between adherent and nonadherent participants, suggesting that demographic and health factors alone do not predict adherence behavior in patients with DR. Interviews identified limited knowledge about DR, logistical challenges, financial constraints, and attitudinal barriers as the primary challenges. Conclusions: This study, conducted during the COVID-19 pandemic, showed suboptimal adherence to referral recommendations among older adult patients due to knowledge gaps, logistical challenges, and health system issues. Quantifying and understanding adherence factors are crucial for targeted interventions addressing barriers to referral recommendations after DRS. Integrating teleophthalmology into and strengthening infrastructure for artificial intelligence?enabled diabetic retinopathy screening to enhance access and outcomes. UR - https://formative.jmir.org/2025/1/e67047 UR - http://dx.doi.org/10.2196/67047 ID - info:doi/10.2196/67047 ER - TY - JOUR AU - Mittal, Ajay AU - Sanchez, Victor AU - Azad, Singh Navjot AU - Zuyev, Yaroslav AU - Robles, Rafael AU - Sherwood, Mark PY - 2025/3/25 TI - The Utility of a Smartphone-Based Retinal Imaging Device as a Screening Tool in an Outpatient Clinic Setting: Protocol for an Observational Study JO - JMIR Res Protoc SP - e52650 VL - 14 KW - digital health KW - digital ophthalmoscope KW - ophthalmology KW - smartphone-based KW - mobile health KW - applications KW - screening tool KW - retinal imaging device KW - glaucoma KW - eye disease KW - visual problems KW - ophthalmoscope KW - ocular disease KW - cost-effective KW - mobile phone N2 - Background: Glaucoma, a disease leading to the degeneration of retinal ganglion cells, results in changes to the optic nerve head that are often diagnosed late when visual problems arise. With the prevalence of glaucoma surpassing 76 million adults worldwide and with glaucoma being the leading cause of irreversible blindness in the world, the early detection and management of glaucoma is imperative. Digital ophthalmoscopes, such as the D-EYE (D-EYE, Srl), have emerged as a technology that uses smartphone cameras with an attachment on the lens to visualize the retina and optic nerve head without the need for dilation. The purpose of this pilot study is to examine the acceptability and feasibility of a D-EYE digital ophthalmoscope to screen for ocular pathology involving the optic nerve, particularly glaucoma. Objective: This study aimed to demonstrate the effect of a smartphone-based ophthalmoscope as a potential vision screening tool for optic nerve head pathology in participants enrolled in this study. The first specific aim was to determine the ability of the D-EYE smartphone ophthalmoscope to gather high-quality imaging to be used for grading the fundus into low- and high-risk categories for eye pathology. The second specific aim was to determine the difference in the quality of data capture between still retinal images and 30-second retinal video recordings produced by D-EYE smartphone ophthalmoscopes. Methods: This observational pilot study enrolled 110 patients receiving routine eye care at the University of Florida Health from February 2019 to February 2022 to assess the use of the D-EYE device in capturing still images and 30-second videos of the bilateral retina and optic nerves of each participant. Study participants completed a survey to gather demographics and past medical history data with a particular focus on previous eye health history. Images were reviewed by 5 ophthalmology residents with interrater reliability analysis performed to assess findings. Results: Ophthalmology resident review indicated greater visualizability and clarity of the bilateral retina and optic nerves with 30-second videos of retinal imaging compared with still-image ophthalmic capture. Furthermore, an increase in visualizability and clarity allowed for a more accurate measurement of the cup-to-disc ratio, a diagnostic marker for glaucoma. In addition, the likelihood of referral of the glaucomatous and healthy sample groups to ophthalmologists indicated a greater sensitivity of digital ophthalmoscopes in being able to detect retinal abnormalities requiring early intervention and management, supporting the technology?s use as a screening tool. Conclusions: This investigation suggests that the use of smartphone-based digital ophthalmoscopes can be more effectively applied as a screening tool by capturing 30-second videos compared with still images alone. This novel assessment of an emerging technology in the field of ophthalmology may better equip further research as smartphone camera technology advances. International Registered Report Identifier (IRRID): DERR1-10.2196/52650 UR - https://www.researchprotocols.org/2025/1/e52650 UR - http://dx.doi.org/10.2196/52650 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/52650 ER - TY - JOUR AU - Xu, Lijuan AU - Li, Hanjia AU - Li, Fang AU - Zhang, Tinghui AU - Yan, Jingyan AU - Yan, Hong AU - He, Lu AU - Yu, Bin PY - 2025/2/18 TI - Investigating the Trajectories of Poor Vision in Children and Adolescents in Wuhan, China From 2016 to 2019: Prospective Cohort Study JO - JMIR Public Health Surveill SP - e53028 VL - 11 KW - children and adolescents KW - poor vision KW - group-based trajectory model KW - myopia KW - gender difference KW - China KW - normal vision group KW - vision decline group KW - moderate poor vision group KW - prevalence N2 - Background: Poor vision is a challenging public health problem among children and adolescents globally and in China. It is well-recognized that early onset of poor vision and progressing to moderate and severe poor vision will increase the risk of irreversible blinding complications. To achieve the national goal of poor vision control and prevention, it is essential to investigate and understand the development of poor vision among children and adolescents in China. Objective: This study aims to investigate the progression of poor vision among children and adolescents in Wuhan, China, based on a prospective cohort and to provide scientific evidence for the development and implementation of effective poor vision prevention and control programs. Methods: Data were derived from a 4-year prospective cohort (2016?2019) of primary and middle school students (N=108,585) in Wuhan, China. Vision condition was measured using the standard logarithmic visual acuity charts. A group-based trajectory model was used to identify trajectories of poor vision overall and by gender and region. Results: The mean age of the study subjects was 11.13 (SD 3.33) years, 200,110 (53.91%) were male and the majority (354404, 95.48%) were from urban areas. The prevalence of poor vision was 58.51% in 2016, 58.95% in 2017, 53.83% in 2018, and 54.79% in 2019. Group-based trajectory model identified 3 groups, including normal vision group (NVG) (27.4%), vision decline group (VDG) (17.8%), and moderate poor vision group (MPVG) (54.8%). A higher proportion of girls (57.8%) were in the MPV group compared to boys (50.5%), and the VDG showed greater changes in girls compared to boys. Furthermore, urban students (55.3%) had a higher proportion of MPV compared to rural students (47.5%), while urban students (17.2%) had a smaller proportion in the VDG compared to rural students (24%). Further analyses showed that as age increased, the likelihood of being categorized in the NVG decreased (?=?.417, P<.001), while the likelihood of being in the VDG (?=.058, P<.001) increased. Compared with boys, girls were more likely to be categorized in the VDG (?=.597, P<.001) and MPV group (?=.362, P<.001). Rural students were less likely than urban students to be categorized in the VDG (?=?.311, P<.001). Conclusions: The prevalence of poor vision among children and adolescents in Wuhan has remained high over the years, with a slight decrease in recent years. The study identified three groups: normal vision, vision decline, and moderate poor vision. Girls and students from urban areas were more likely to have moderate poor vision, while boys and rural students had a higher proportion of vision decline. These findings provide valuable information for implementing poor vision prevention and control policies in the region. UR - https://publichealth.jmir.org/2025/1/e53028 UR - http://dx.doi.org/10.2196/53028 ID - info:doi/10.2196/53028 ER - TY - JOUR AU - Zhu, Wenqing AU - Gu, Shuneng AU - Li, Jian AU - Lin, Jin AU - Hu, Chanling AU - Liu, Rui PY - 2025/1/16 TI - Transformative Gamified Binocular Therapy for Unilateral Amblyopia in Young Children: Pilot Prospective Efficacy and Safety Study JO - JMIR Serious Games SP - e63384 VL - 13 KW - amblyopia KW - binocular treatment KW - digital therapy KW - game KW - stereoacuity KW - visual acuity N2 - Background: Amblyopia is a common cause of visual impairment in children. Compliance with traditional treatments for amblyopia is challenging due to negative psychosocial impacts. Recent shifts in amblyopia treatment have moved from suppressing the dominant eye to enhancing binocular visual function. Binocular digital therapy has become a promising approach. Objective: The aim of this study was to evaluate the effects of binocular gamified digital therapy on visual acuity and stereoacuity (SA) in children with unilateral amblyopia. Methods: This pilot prospective study enrolled 11 children aged 4-6 years with unilateral amblyopia. Following at least 8 weeks of refractive correction, participants underwent binocular gamified digital therapy for 60 minutes per day, 5 days a week. The therapy used a roguelike shooting game delivered under binocular conditions through two independent channels with a real-time artificial intelligence visual engine. Assessments of distance visual acuity (DVA), near visual acuity (NVA), and SA were conducted at baseline and again at 4, 8, and 12 weeks. Results: At 12 weeks, the following significant improvements were noted: amblyopic eye DVA improved by 1.0 line (P=.01; d=0.77), binocular DVA improved by 0.7 lines (P=.006; d=1.00), and SA improved by 0.3 logarithm (log) arcseconds (P=.01; d=0.97). At 8 weeks, improvements included amblyopic eye DVA by 0.9 lines (P=.046; d=1.00) and SA by 0.28 log arcseconds (P=.02; d=0.90). No significant adverse events were observed, although one participant developed progressive esotropia. Conclusions: Binocular gamified digital therapy is effective and safe for improving visual outcomes in children aged 4-6 years with unilateral amblyopia. Trial Registration: Chinese Clinical Trial Registry ChiCTR2300072066; https://www.chictr.org.cn/showproj.html?proj=198625 UR - https://games.jmir.org/2025/1/e63384 UR - http://dx.doi.org/10.2196/63384 ID - info:doi/10.2196/63384 ER - TY - JOUR AU - Zuo, Huiyi AU - Huang, Baoyu AU - He, Jian AU - Fang, Liying AU - Huang, Minli PY - 2025/1/3 TI - Machine Learning Approaches in High Myopia: Systematic Review and Meta-Analysis JO - J Med Internet Res SP - e57644 VL - 27 KW - high myopia KW - pathological myopia KW - high myopia-associated glaucoma KW - machine learning KW - deep learning N2 - Background: In recent years, with the rapid development of machine learning (ML), it has gained widespread attention from researchers in clinical practice. ML models appear to demonstrate promising accuracy in the diagnosis of complex diseases, as well as in predicting disease progression and prognosis. Some studies have applied it to ophthalmology, primarily for the diagnosis of pathologic myopia and high myopia-associated glaucoma, as well as for predicting the progression of high myopia. ML-based detection still requires evidence-based validation to prove its accuracy and feasibility. Objective: This study aims to discern the performance of ML methods in detecting high myopia and pathologic myopia in clinical practice, thereby providing evidence-based support for the future development and refinement of intelligent diagnostic or predictive tools. Methods: PubMed, Cochrane, Embase, and Web of Science were thoroughly retrieved up to September 3, 2023. The prediction model risk of bias assessment tool was leveraged to appraise the risk of bias in the eligible studies. The meta-analysis was implemented using a bivariate mixed-effects model. In the validation set, subgroup analyses were conducted based on the ML target events (diagnosis and prediction of high myopia and diagnosis of pathological myopia and high myopia-associated glaucoma) and modeling methods. Results: This study ultimately included 45 studies, of which 32 were used for quantitative meta-analysis. The meta-analysis results unveiled that for the diagnosis of pathologic myopia, the summary receiver operating characteristic (SROC), sensitivity, and specificity of ML were 0.97 (95% CI 0.95-0.98), 0.91 (95% CI 0.89-0.92), and 0.95 (95% CI 0.94-0.97), respectively. Specifically, deep learning (DL) showed an SROC of 0.97 (95% CI 0.95-0.98), sensitivity of 0.92 (95% CI 0.90-0.93), and specificity of 0.96 (95% CI 0.95-0.97), while conventional ML (non-DL) showed an SROC of 0.86 (95% CI 0.75-0.92), sensitivity of 0.77 (95% CI 0.69-0.84), and specificity of 0.85 (95% CI 0.75-0.92). For the diagnosis and prediction of high myopia, the SROC, sensitivity, and specificity of ML were 0.98 (95% CI 0.96-0.99), 0.94 (95% CI 0.90-0.96), and 0.94 (95% CI 0.88-0.97), respectively. For the diagnosis of high myopia-associated glaucoma, the SROC, sensitivity, and specificity of ML were 0.96 (95% CI 0.94-0.97), 0.92 (95% CI 0.85-0.96), and 0.88 (95% CI 0.67-0.96), respectively. Conclusions: ML demonstrated highly promising accuracy in diagnosing high myopia and pathologic myopia. Moreover, based on the limited evidence available, we also found that ML appeared to have favorable accuracy in predicting the risk of developing high myopia in the future. DL can be used as a potential method for intelligent image processing and intelligent recognition, and intelligent examination tools can be developed in subsequent research to provide help for areas where medical resources are scarce. Trial Registration: PROSPERO CRD42023470820; https://tinyurl.com/2xexp738 UR - https://www.jmir.org/2025/1/e57644 UR - http://dx.doi.org/10.2196/57644 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/57644 ER - TY - JOUR AU - Zhao, Ziwei AU - Zhang, Weiyi AU - Chen, Xiaolan AU - Song, Fan AU - Gunasegaram, James AU - Huang, Wenyong AU - Shi, Danli AU - He, Mingguang AU - Liu, Na PY - 2024/12/30 TI - Slit Lamp Report Generation and Question Answering: Development and Validation of a Multimodal Transformer Model with Large Language Model Integration JO - J Med Internet Res SP - e54047 VL - 26 KW - large language model KW - slit lamp KW - medical report generation KW - question answering N2 - Background: Large language models have shown remarkable efficacy in various medical research and clinical applications. However, their skills in medical image recognition and subsequent report generation or question answering (QA) remain limited. Objective: We aim to finetune a multimodal, transformer-based model for generating medical reports from slit lamp images and develop a QA system using Llama2. We term this entire process slit lamp?GPT. Methods: Our research used a dataset of 25,051 slit lamp images from 3409 participants, paired with their corresponding physician-created medical reports. We used these data, split into training, validation, and test sets, to finetune the Bootstrapping Language-Image Pre-training framework toward report generation. The generated text reports and human-posed questions were then input into Llama2 for subsequent QA. We evaluated performance using qualitative metrics (including BLEU [bilingual evaluation understudy], CIDEr [consensus-based image description evaluation], ROUGE-L [Recall-Oriented Understudy for Gisting Evaluation?Longest Common Subsequence], SPICE [Semantic Propositional Image Caption Evaluation], accuracy, sensitivity, specificity, precision, and F1-score) and the subjective assessments of two experienced ophthalmologists on a 1-3 scale (1 referring to high quality). Results: We identified 50 conditions related to diseases or postoperative complications through keyword matching in initial reports. The refined slit lamp?GPT model demonstrated BLEU scores (1-4) of 0.67, 0.66, 0.65, and 0.65, respectively, with a CIDEr score of 3.24, a ROUGE (Recall-Oriented Understudy for Gisting Evaluation) score of 0.61, and a Semantic Propositional Image Caption Evaluation score of 0.37. The most frequently identified conditions were cataracts (22.95%), age-related cataracts (22.03%), and conjunctival concretion (13.13%). Disease classification metrics demonstrated an overall accuracy of 0.82 and an F1-score of 0.64, with high accuracies (?0.9) observed for intraocular lens, conjunctivitis, and chronic conjunctivitis, and high F1-scores (?0.9) observed for cataract and age-related cataract. For both report generation and QA components, the two evaluating ophthalmologists reached substantial agreement, with ? scores between 0.71 and 0.84. In assessing 100 generated reports, they awarded scores of 1.36 for both completeness and correctness; 64% (64/100) were considered ?entirely good,? and 93% (93/100) were ?acceptable.? In the evaluation of 300 generated answers to questions, the scores were 1.33 for completeness, 1.14 for correctness, and 1.15 for possible harm, with 66.3% (199/300) rated as ?entirely good? and 91.3% (274/300) as ?acceptable.? Conclusions: This study introduces the slit lamp?GPT model for report generation and subsequent QA, highlighting the potential of large language models to assist ophthalmologists and patients. UR - https://www.jmir.org/2024/1/e54047 UR - http://dx.doi.org/10.2196/54047 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/54047 ER - TY - JOUR AU - Kianian, Reza AU - Sun, Deyu AU - Rojas-Carabali, William AU - Agrawal, Rupesh AU - Tsui, Edmund PY - 2024/12/24 TI - Large Language Models May Help Patients Understand Peer-Reviewed Scientific Articles About Ophthalmology: Development and Usability Study JO - J Med Internet Res SP - e59843 VL - 26 KW - uveitis KW - artificial intelligence KW - ChatGPT KW - readability KW - peer review KW - large language models KW - LLMs KW - health literacy KW - patient education KW - medical information KW - ophthalmology N2 - Background: Adequate health literacy has been shown to be important for the general health of a population. To address this, it is recommended that patient-targeted medical information is written at a sixth-grade reading level. To make well-informed decisions about their health, patients may want to interact directly with peer-reviewed open access scientific articles. However, studies have shown that such text is often written with highly complex language above the levels that can be comprehended by the general population. Previously, we have published on the use of large language models (LLMs) in easing the readability of patient-targeted health information on the internet. In this study, we continue to explore the advantages of LLMs in patient education. Objective: This study aimed to explore the use of LLMs, specifically ChatGPT (OpenAI), to enhance the readability of peer-reviewed scientific articles in the field of ophthalmology. Methods: A total of 12 open access, peer-reviewed papers published by the senior authors of this study (ET and RA) were selected. Readability was assessed using the Flesch-Kincaid Grade Level and Simple Measure of Gobbledygook tests. ChatGPT 4.0 was asked ?I will give you the text of a peer-reviewed scientific paper. Considering that the recommended readability of the text is 6th grade, can you simplify the following text so that a layperson reading this text can fully comprehend it? - Insert Manuscript Text -?. Appropriateness was evaluated by the 2 uveitis-trained ophthalmologists. Statistical analysis was performed in Microsoft Excel. Results: ChatGPT significantly lowered the readability and length of the selected papers from 15th to 7th grade (P<.001) while generating responses that were deemed appropriate by expert ophthalmologists. Conclusions: LLMs show promise in improving health literacy by enhancing the accessibility of peer-reviewed scientific articles and allowing the general population to interact directly with medical literature. UR - https://www.jmir.org/2024/1/e59843 UR - http://dx.doi.org/10.2196/59843 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/59843 ER - TY - JOUR AU - Chen, Xiaolan AU - Zhao, Ziwei AU - Zhang, Weiyi AU - Xu, Pusheng AU - Wu, Yue AU - Xu, Mingpu AU - Gao, Le AU - Li, Yinwen AU - Shang, Xianwen AU - Shi, Danli AU - He, Mingguang PY - 2024/12/11 TI - EyeGPT for Patient Inquiries and Medical Education: Development and Validation of an Ophthalmology Large Language Model JO - J Med Internet Res SP - e60063 VL - 26 KW - large language model KW - generative pretrained transformer KW - generative artificial intelligence KW - ophthalmology KW - retrieval-augmented generation KW - medical assistant KW - EyeGPT KW - generative AI N2 - Background: Large language models (LLMs) have the potential to enhance clinical flow and improve medical education, but they encounter challenges related to specialized knowledge in ophthalmology. Objective: This study aims to enhance ophthalmic knowledge by refining a general LLM into an ophthalmology-specialized assistant for patient inquiries and medical education. Methods: We transformed Llama2 into an ophthalmology-specialized LLM, termed EyeGPT, through the following 3 strategies: prompt engineering for role-playing, fine-tuning with publicly available data sets filtered for eye-specific terminology (83,919 samples), and retrieval-augmented generation leveraging a medical database and 14 ophthalmology textbooks. The efficacy of various EyeGPT variants was evaluated by 4 board-certified ophthalmologists through comprehensive use of 120 diverse category questions in both simple and complex question-answering scenarios. The performance of the best EyeGPT model was then compared with that of the unassisted human physician group and the EyeGPT+human group. We proposed 4 metrics for assessment: accuracy, understandability, trustworthiness, and empathy. The proportion of hallucinations was also reported. Results: The best fine-tuned model significantly outperformed the original Llama2 model at providing informed advice (mean 9.30, SD 4.42 vs mean 13.79, SD 5.70; P<.001) and mitigating hallucinations (97/120, 80.8% vs 53/120, 44.2%, P<.001). Incorporating information retrieval from reliable sources, particularly ophthalmology textbooks, further improved the model's response compared with solely the best fine-tuned model (mean 13.08, SD 5.43 vs mean 15.14, SD 4.64; P=.001) and reduced hallucinations (71/120, 59.2% vs 57/120, 47.4%, P=.02). Subgroup analysis revealed that EyeGPT showed robustness across common diseases, with consistent performance across different users and domains. Among the variants, the model integrating fine-tuning and book retrieval ranked highest, closely followed by the combination of fine-tuning and the manual database, standalone fine-tuning, and pure role-playing methods. EyeGPT demonstrated competitive capabilities in understandability and empathy when compared with human ophthalmologists. With the assistance of EyeGPT, the performance of the ophthalmologist was notably enhanced. Conclusions: We pioneered and introduced EyeGPT by refining a general domain LLM and conducted a comprehensive comparison and evaluation of different strategies to develop an ophthalmology-specific assistant. Our results highlight EyeGPT?s potential to assist ophthalmologists and patients in medical settings. UR - https://www.jmir.org/2024/1/e60063 UR - http://dx.doi.org/10.2196/60063 UR - http://www.ncbi.nlm.nih.gov/pubmed/39661433 ID - info:doi/10.2196/60063 ER - TY - JOUR AU - Miladinovi?, Aleksandar AU - Quaia, Christian AU - Kresevic, Simone AU - Aj?evi?, Milo? AU - Diplotti, Laura AU - Michieletto, Paola AU - Accardo, Agostino AU - Pensiero, Stefano PY - 2024/12/9 TI - High-Resolution Eye-Tracking System for Accurate Measurement of Short-Latency Ocular Following Responses: Development and Observational Study JO - JMIR Pediatr Parent SP - e64353 VL - 7 KW - ocular following response KW - stereopsis KW - video-oculography KW - ocular KW - tracker KW - vision KW - pediatric KW - children KW - youth KW - infrared KW - algorithm KW - eye tracking N2 - Background: Ocular following responses (OFRs)?small-amplitude, short-latency reflexive eye movements?have been used to study visual motion processing, with potential diagnostic applications. However, they are difficult to record with commercial, video-based eye trackers, especially in children. Objective: We aimed to design and develop a noninvasive eye tracker specialized for measuring OFRs, trading off lower temporal resolution and a smaller range for higher spatial resolution. Methods: We developed a high-resolution eye-tracking system based on a high-resolution camera operating in the near-infrared spectral range, coupled with infrared illuminators and a dedicated postprocessing pipeline, optimized to measure OFRs in children. To assess its performance, we: (1) evaluated our algorithm for compensating small head movements in both artificial and real-world settings, (2) compared OFRs measured simultaneously by our system and a reference scleral search coil eye-tracking system, and (3) tested the system?s ability to measure OFRs in a clinical setting with children. Results: The simultaneous measurement by our system and a reference system showed that our system achieved an in vivo resolution of approximately 0.06°, which is sufficient for recording OFRs. Head motion compensation was successfully tested, showing a displacement error of less than 5 ?m. Finally, robust OFRs were detected in 16 children during recording sessions lasting less than 5 minutes. Conclusions: Our high-resolution, noninvasive eye-tracking system successfully detected OFRs with minimal need for subject cooperation. The system effectively addresses the limits of other OFR measurement methods and offers a versatile solution suitable for clinical applications, particularly in children, where eye tracking is more challenging. The system could potentially be suitable for diagnostic applications, particularly in pediatric populations where early detection of visual disorders like stereodeficiencies is critical. UR - https://pediatrics.jmir.org/2024/1/e64353 UR - http://dx.doi.org/10.2196/64353 ID - info:doi/10.2196/64353 ER - TY - JOUR AU - Varghese, Julian AU - Schuster, Alexander AU - Poschkamp, Broder AU - Yildirim, Kemal AU - Oehm, Johannes AU - Berens, Philipp AU - Müller, Sarah AU - Gervelmeyer, Julius AU - Koch, Lisa AU - Hoffmann, Katja AU - Sedlmayr, Martin AU - Kakkassery, Vinodh AU - Kohlbacher, Oliver AU - Merle, David AU - Bartz-Schmidt, Ulrich Karl AU - Ueffing, Marius AU - Stahl, Dana AU - Leddig, Torsten AU - Bialke, Martin AU - Hampf, Christopher AU - Hoffmann, Wolfgang AU - Berthe, Sebastian AU - Waltemath, Dagmar AU - Walter, Peter AU - Lipprandt, Myriam AU - Röhrig, Rainer AU - Storp, Julian Jens AU - Zimmermann, Alexander Julian AU - Holtrup, Lea AU - Brix, Tobias AU - Stahl, Andreas AU - Eter, Nicole PY - 2024/12/5 TI - EyeMatics: An Ophthalmology Use Case Within the German Medical Informatics Initiative JO - JMIR Med Inform SP - e60851 VL - 12 KW - digital ophthalmology KW - interoperability KW - precision ophthalmology KW - patient engagement KW - Germany KW - clinical use KW - intravitreal KW - injections KW - eye KW - treatment KW - patient data KW - framework KW - AI KW - artificial intelligence KW - biomarker KW - retinal KW - scan KW - user-centered KW - observational UR - https://medinform.jmir.org/2024/1/e60851 UR - http://dx.doi.org/10.2196/60851 ID - info:doi/10.2196/60851 ER - TY - JOUR AU - Ming, Shuai AU - Yao, Xi AU - Guo, Xiaohong AU - Guo, Qingge AU - Xie, Kunpeng AU - Chen, Dandan AU - Lei, Bo PY - 2024/11/14 TI - Performance of ChatGPT in Ophthalmic Registration and Clinical Diagnosis: Cross-Sectional Study JO - J Med Internet Res SP - e60226 VL - 26 KW - artificial intelligence KW - chatbot KW - ChatGPT KW - ophthalmic registration KW - clinical diagnosis KW - AI KW - cross-sectional study KW - eye disease KW - eye disorder KW - ophthalmology KW - health care KW - outpatient registration KW - clinical KW - decision-making KW - generative AI KW - vision impairment N2 - Background: Artificial intelligence (AI) chatbots such as ChatGPT are expected to impact vision health care significantly. Their potential to optimize the consultation process and diagnostic capabilities across range of ophthalmic subspecialties have yet to be fully explored. Objective: This study aims to investigate the performance of AI chatbots in recommending ophthalmic outpatient registration and diagnosing eye diseases within clinical case profiles. Methods: This cross-sectional study used clinical cases from Chinese Standardized Resident Training?Ophthalmology (2nd Edition). For each case, 2 profiles were created: patient with history (Hx) and patient with history and examination (Hx+Ex). These profiles served as independent queries for GPT-3.5 and GPT-4.0 (accessed from March 5 to 18, 2024). Similarly, 3 ophthalmic residents were posed the same profiles in a questionnaire format. The accuracy of recommending ophthalmic subspecialty registration was primarily evaluated using Hx profiles. The accuracy of the top-ranked diagnosis and the accuracy of the diagnosis within the top 3 suggestions (do-not-miss diagnosis) were assessed using Hx+Ex profiles. The gold standard for judgment was the published, official diagnosis. Characteristics of incorrect diagnoses by ChatGPT were also analyzed. Results: A total of 208 clinical profiles from 12 ophthalmic subspecialties were analyzed (104 Hx and 104 Hx+Ex profiles). For Hx profiles, GPT-3.5, GPT-4.0, and residents showed comparable accuracy in registration suggestions (66/104, 63.5%; 81/104, 77.9%; and 72/104, 69.2%, respectively; P=.07), with ocular trauma, retinal diseases, and strabismus and amblyopia achieving the top 3 accuracies. For Hx+Ex profiles, both GPT-4.0 and residents demonstrated higher diagnostic accuracy than GPT-3.5 (62/104, 59.6% and 63/104, 60.6% vs 41/104, 39.4%; P=.003 and P=.001, respectively). Accuracy for do-not-miss diagnoses also improved (79/104, 76% and 68/104, 65.4% vs 51/104, 49%; P<.001 and P=.02, respectively). The highest diagnostic accuracies were observed in glaucoma; lens diseases; and eyelid, lacrimal, and orbital diseases. GPT-4.0 recorded fewer incorrect top-3 diagnoses (25/42, 60% vs 53/63, 84%; P=.005) and more partially correct diagnoses (21/42, 50% vs 7/63 11%; P<.001) than GPT-3.5, while GPT-3.5 had more completely incorrect (27/63, 43% vs 7/42, 17%; P=.005) and less precise diagnoses (22/63, 35% vs 5/42, 12%; P=.009). Conclusions: GPT-3.5 and GPT-4.0 showed intermediate performance in recommending ophthalmic subspecialties for registration. While GPT-3.5 underperformed, GPT-4.0 approached and numerically surpassed residents in differential diagnosis. AI chatbots show promise in facilitating ophthalmic patient registration. However, their integration into diagnostic decision-making requires more validation. UR - https://www.jmir.org/2024/1/e60226 UR - http://dx.doi.org/10.2196/60226 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60226 ER - TY - JOUR AU - Hertel, Kay Amanda AU - Ajlan, S. Radwan PY - 2024/11/13 TI - Impact of Ophthalmic Knowledge Assessment Program Scores and Surgical Volume on Subspecialty Fellowship Application in Ophthalmology Residency: Retrospective Cohort Study JO - JMIR Med Educ SP - e60940 VL - 10 KW - residency KW - fellowship KW - ophthalmology KW - OKAP KW - surgical training KW - ophthalmology resident KW - ophthalmology residency program KW - examination KW - surgical volume exposure KW - fellowship training KW - surgical volume KW - exposure KW - Ophthalmic Knowledge Assessment Program N2 - Background: Ophthalmology residents take the Ophthalmic Knowledge Assessment Program (OKAP) exam annually, which provides percentile rank for multiple categories and the total score. In addition, ophthalmology residency training programs have multiple subspecialty rotations with defined minimum procedure requirements. However, residents? surgical volumes vary, with some residents exceeding their peers in specific subspecialty rotations. Objective: This study aims to identify if there is a difference in OKAP examination scores and surgical volume exposure during ophthalmology residency training between nonfellowship and fellowship applicants and among various subspecialties. Methods: A retrospective review of OKAP scores and surgical procedure numbers of graduating residents in an accredited academic ophthalmology residency program in the Midwest United States was conducted. Data were collected from 2012 to 2022. Results: A total of 31 residents were identified. Most residents decided to pursue fellowship training upon graduation (20/31, 65% residents), and the rest chose to practice comprehensive ophthalmology (11/31, 35% residents). A total of 18/31 residents had OKAP score reports available. The fellowship group outperformed the nonfellowship group in multiple subsections and the total exam (P=.04). Those pursuing fellowship training in glaucoma performed higher on the Glaucoma section (P=.004) and the total exam (P=.005). Residents pursuing cornea performed higher on nearly all subsections, including External Disease and Cornea (P=.02) and the total exam (P=.007). The majority of the surgical volume exposure was identical between fellowship and nonfellowship groups. Those who pursued glaucoma fellowship performed more glaucoma filtering and shunting procedures (P=.03). Residents going into pediatrics fellowship were primary surgeons in more strabismus cases (P=.01), assisted in fewer strabismus cases (P<.001), and had no difference in the total number of strabismus surgeries. Conclusions: In our program, residents pursuing fellowship training had higher OKAP scores on multiple sections and the total exam. There was no significant difference in the overall surgical volume averages between fellowship and nonfellowship groups, but few differences existed in subspecialty procedures among fellowship applicants. Larger multicenter studies are needed to clarify the relationship between OKAP scores and ophthalmology fellowship decisions nationwide. UR - https://mededu.jmir.org/2024/1/e60940 UR - http://dx.doi.org/10.2196/60940 ID - info:doi/10.2196/60940 ER - TY - JOUR AU - Choi, Kyungseon AU - Park, Jun Sang AU - Yoon, Hyuna AU - Choi, Seoyoon AU - Mun, Yongseok AU - Kim, Seok AU - Yoo, Sooyoung AU - Woo, Joon Se AU - Park, Hyung Kyu AU - Na, Junghyun AU - Suh, Sun Hae PY - 2024/10/8 TI - Patient-Centered Economic Burden of Diabetic Macular Edema: Retrospective Cohort Study JO - JMIR Public Health Surveill SP - e56741 VL - 10 KW - diabetic macular edema KW - economic burden KW - cost of illness KW - retrospective cohort study KW - patient-centered care KW - Observational Medical Outcomes Partnership Common Data Model N2 - Background: Diabetic macular edema (DME), a leading cause of blindness, requires treatment with costly drugs, such as anti?vascular endothelial growth factor (VEGF) agents. The prolonged use of these effective but expensive drugs results in an incremental economic burden for patients with DME compared with those with diabetes mellitus (DM) without DME. However, there are no studies on the long-term patient-centered economic burden of DME after reimbursement for anti-VEGFs. Objective: This retrospective cohort study aims to estimate the 3-year patient-centered economic burden of DME compared with DM without DME, using the Common Data Model. Methods: We used medical data from 1,903,603 patients (2003-2020), transformed and validated using the Observational Medical Outcomes Partnership Common Data Model from Seoul National University Bundang Hospital. We defined the group with DME as patients aged >18 years with nonproliferative diabetic retinopathy and intravitreal anti-VEGF or steroid prescriptions. As control, we defined the group with DM without DME as patients aged >18 years with DM or diabetic retinopathy without intravitreal anti-VEGF or steroid prescriptions. Propensity score matching, performed using a regularized logistic regression with a Laplace prior, addressed selection bias. We estimated direct medical costs over 3 years categorized into total costs, reimbursement costs, nonreimbursement costs, out-of-pocket costs, and costs covered by insurance, as well as healthcare resource utilization. An exponential conditional model and a count model estimated unbiased incremental patient-centered economic burden using generalized linear models and a zero-inflation model. Results: In a cohort of 454 patients with DME matched with 1640 patients with DM, the economic burden of DME was significantly higher than that of DM, with total costs over 3 years being 2.09 (95% CI 1.78-2.47) times higher. Reimbursement costs were 1.89 (95% CI 1.57-2.28) times higher in the group with DME than with the group with DM, while nonreimbursement costs were 2.54 (95% CI 2.12-3.06) times higher. Out-of-pocket costs and costs covered by insurance were also higher by a factor of 2.11 (95% CI 1.58-2.59) and a factor of 2.01 (95% CI 1.85-2.42), respectively. Patients with DME had a significantly higher number of outpatient (1.87-fold) and inpatient (1.99-fold) visits compared with those with DM (P<.001 in all cases). Conclusions: Patients with DME experience a heightened economic burden compared with diabetic patients without DME. The substantial and enduring economic impact observed in real-world settings underscores the need to alleviate patients? burden through preventive measures, effective management, appropriate reimbursement policies, and the development of innovative treatments. Strategies to mitigate the economic impact of DME should include proactive approaches such as expanding anti-VEGF reimbursement criteria, approving and reimbursing cost-effective drugs such as bevacizumab, advocating for proactive eye examinations, and embracing early diagnosis by ophthalmologists facilitated by cutting-edge methodologies such as artificial intelligence for patients with DM. UR - https://publichealth.jmir.org/2024/1/e56741 UR - http://dx.doi.org/10.2196/56741 UR - http://www.ncbi.nlm.nih.gov/pubmed/39378098 ID - info:doi/10.2196/56741 ER - TY - JOUR AU - Liao, Yi-Fang AU - Lee, Yu-Chen AU - Lin, Hui-Ju AU - Shao, Yi-Ching PY - 2024/10/8 TI - Acupuncture as Adjuvant Therapy for Glaucoma: Protocol for a Randomized Controlled Trial JO - JMIR Res Protoc SP - e57888 VL - 13 KW - acupuncture KW - open-angle glaucoma KW - optical coherence tomography KW - intraocular pressure KW - glaucoma KW - adjuvant therapy KW - optic neuropathy KW - disease progression KW - ophthalmic disorders KW - optic KW - conventional treatment KW - efficacy KW - adjunctive therapy N2 - Background: Glaucoma is a chronic progressive optic neuropathy that necessitates lifelong treatment to reduce the decline of the optic nerve. Due to the extended and continuous treatments required for patients, complementary therapies are often considered alongside conventional treatments to enhance the effectiveness of the treatment. Acupuncture has demonstrated the potential to lower intraocular pressure in previous clinical trials, making it a promising glaucoma intervention. Objective: The primary objective of this study is to conduct a single-center randomized control trial involving patients with glaucoma. Acupuncture will be evaluated as an adjunctive therapy. The trial aims to explore its effectiveness for glaucoma. Methods: In this single-center randomized controlled trial, participants (N=50) with primary open-angle glaucoma will be randomly assigned to the treatment group, receiving ophthalmic acupuncture with ?De Qi? sensation, or the control group, receiving minimum acupuncture stimulation on nonophthalmic acupoints. The intervention will consist of weekly acupuncture treatments for a total of 6 sessions. Participants will be assessed at 8 time points, which are baseline, during the intervention (6 times), and at a 3-month follow-up. The primary outcome measure is a change in the intraocular pressure before and after each acupuncture treatment. Secondary outcomes will include measurements of heart rate and blood pressure before and after acupuncture, best-corrected visual acuity, visual field, optical coherence tomography, optical coherence tomography angiography, the Glaucoma Symptom Scale, and the Glaucoma Quality of Life-15 questionnaire. Results: Recruitment of participants for the trial commenced on June 28, 2023. A total of 10 participants have been enrolled to test the feasibility of the experiment. We anticipate that the preliminary data from this trial will be completed by December 2025. Conclusions: This trial uses rigorous methodology and comprehensive outcome measurements to assess the clinical efficacy of acupuncture as an adjunctive therapy for glaucoma, providing valuable insights for future clinical treatment guidelines. Trial Registration: ClinicalTrials.gov NCT05753137; https://clinicaltrials.gov/study/NCT05753137 International Registered Report Identifier (IRRID): DERR1-10.2196/57888 UR - https://www.researchprotocols.org/2024/1/e57888 UR - http://dx.doi.org/10.2196/57888 UR - http://www.ncbi.nlm.nih.gov/pubmed/39378079 ID - info:doi/10.2196/57888 ER - TY - JOUR AU - Sood, Ishaana AU - Sabherwal, Shalinder AU - Mathur, Umang AU - Jain, Elesh AU - Bhadauria, Madhu AU - Agrawal, Deepshikha AU - Khurana, Ashi AU - Mittal, Vikas AU - Mahindrakar, Avinash AU - Govindahari, Vishal AU - Kulkarni, Sucheta AU - Nischal, K. Ken PY - 2024/9/30 TI - Harnessing Generalizable Real-World Ophthalmic Big Data: Descriptive Analysis of the Bodhya Eye Consortium Model for Collaborative Research JO - Online J Public Health Inform SP - e53370 VL - 16 KW - anthropological and genomic heterogeneity KW - big data KW - consortium KW - collaborative research KW - generalizability KW - global health impact KW - North India N2 - Background: Eye care organizations and professionals worldwide are increasingly focusing on bridging the gap between population health and medical practice. Recent advances in genomics and anthropology have revealed that most Indian groups trace their ancestry to a blend of 2 genetically distinct populations: Ancestral North Indians, who share genetic affinities with Central Asians, Middle Easterners, Caucasians, and Europeans; and Ancestral South Indians, genetically distinct from groups outside the Indian subcontinent. Studies conducted among North Indian populations can therefore offer insights that are potentially applicable to these diverse global populations, underscoring significant implications for global health. Objective: The Bodhya Eye Consortium is a collaboration among 8 high-volume nonprofit eyecare organizations from across North India. The consortium aims to harness real-world data consistently and with assured quality for collaborative research. This paper outlines the formation of the consortium as a proposed model for controlled collaborative research among the leading eyecare organizations of North India. Methods: We detail the creation and effective implementation of a consortium following a structured road map that included planning and assessment, establishing an exploratory task force, defining specialty areas, setting objectives and priorities, and conducting a SWOT (strengths, weaknesses, opportunities, and threats) analysis. Central to this process was a comprehensive data audit aimed at standardizing data collection across all participating organizations. Results: The consortium currently comprises 9 organizations, each represented in the governance structure by the Governing Council. Scientific standards for published research are established and overseen by the Scientific Committee, while the Conflict Resolution Committee manages any unresolved disputes. The consortium?s working groups, organized by various eyecare specialties, collaborate on research projects through virtual interactions. A foundational step in this process was the organizationwide data audit, which revealed that most organizations complied with accurate and standardized data collection practices. Organizations with deficiencies in data completeness developed action plans to address them. Subsequently, the consortium adopted data collection proformas, contributing to the publication of high-quality manuscripts characterized by low dropout rates. Conclusions: The collaborative research conducted by the Bodhya Eye Consortium?a group of high-volume eyecare organizations primarily from North India?offers a unique opportunity to contribute to scientific knowledge across various domains of eyecare. By leveraging the established heterogeneity of anthropological and genomic origins within the population, the findings can be generalizable, to some extent, to European, Middle Eastern, and European American populations. This access to potentially invaluable, generalizable data has significant global health implications and opens possibilities for broader collaboration. The model outlined in this descriptive paper can serve as a blueprint for other health care organizations looking to develop similar collaborations for research and knowledge sharing. UR - https://ojphi.jmir.org/2024/1/e53370 UR - http://dx.doi.org/10.2196/53370 UR - http://www.ncbi.nlm.nih.gov/pubmed/39348171 ID - info:doi/10.2196/53370 ER - TY - JOUR AU - Wang, Xiaoling AU - Rao, Rui AU - Li, Hua AU - Lei, Xiaoping AU - Dong, Wenbin PY - 2024/9/18 TI - Red Blood Cell Transfusion for Incidence of Retinopathy of Prematurity: Prospective Multicenter Cohort Study JO - JMIR Pediatr Parent SP - e60330 VL - 7 KW - red blood cell transfusion KW - retinopathy of prematurity KW - VPI KW - very preterm infants KW - ROP KW - visual impairment KW - blindness KW - RBC KW - red blood cell N2 - Background: Retinopathy of prematurity (ROP) is a leading cause of visual impairment and blindness in preterm infants. Objective: This study sought to investigate the association between red blood cell (RBC) transfusion and ROP in very preterm infants (VPIs) to inform clinical strategies for ROP prevention and treatment. Methods: We designed a prospective multicenter cohort study that included VPIs and follow-up data from January 2017 to December 2022 at 3 neonatal clinical medicine centers. They were categorized into a transfusion group (infants who received an RBC transfusion within 4 wk) and a nontransfusion group. The relationship between RBC transfusion and ROP incidence was assessed using binary logistic regression, with subgroup analyses based on gestational age, birth weight, sex, and sepsis status. Inverse probability of treatment weighting and propensity score matching were applied to account for all potential confounding factors that could affect ROP development, followed by sensitivity analysis. Results: The study included 832 VPIs, including 327 in the nontransfusion group and 505 in the transfusion group. The transfusion group had a lower average birth weight and gestational age and a greater incidence of ROP, ?stage 2 ROP, and severe ROP. Logistic regression analysis revealed that the transfusion group had a significantly greater risk of ROP (adjusted odds ratio [aOR] 1.70, 95% CI 1.14?2.53, P=.009) and ?stage 2 ROP (aOR 1.68, 95% CI 1.02?2.78, P=.04) but not severe ROP (aOR 1.75, 95% CI 0.61?5.02, P=.30). The trend analysis also revealed an increased risk of ROP with an increasing number of transfusions and a larger volume of blood transfused (P for trend<.001). Subgroup analyses confirmed a consistent trend, with the transfusion group at a higher risk for ROP across all subgroups. Inverse probability of treatment weighting and propensity score matching analyses supported the initial findings. Conclusions: For VPIs, RBC transfusion significantly increases the risk of ROP, and the risk increases with an increasing number of transfusions and volume of blood transfused. UR - https://pediatrics.jmir.org/2024/1/e60330 UR - http://dx.doi.org/10.2196/60330 ID - info:doi/10.2196/60330 ER - TY - JOUR AU - Kammrath Betancor, Paola AU - Böhringer, Daniel AU - Maier, Philip AU - Lapp, Thabo AU - Reinhard, Thomas PY - 2024/9/10 TI - Splenectomy as a Risk Factor for Graft Rejection Following Endothelial Transplantation: Retrospective Study JO - Interact J Med Res SP - e50106 VL - 13 KW - anterior chamber?associated immune deviation KW - ACAID KW - Descemet membrane endothelial keratoplasty KW - DMEK KW - splenectomy N2 - Background: Anterior chamber?associated immune deviation (ACAID) is an active immunotolerance mechanism, which is induced by placing antigen into the anterior eye chamber as long as a major surgical trauma is avoided. For this reason, ACAID may be a major contributor to the favorable immunologic outcomes in Descemet membrane endothelial keratoplasty (DMEK). Rodent models have demonstrated the importance of a functional spleen for the development of an ACAID. Objective: This study aimed to investigate whether splenectomy leads to increased rejection rates after DMEK in humans. Methods: A retrospective evaluation was conducted on the course following DMEK at the Eye Center, Medical Center, University of Freiburg, for patients with a self-reported history of splenectomy compared to patients without this condition. Potential study patients were contacted by mail. A questionnaire to self-report splenectomy and the time thereof was sent out. The medical records of all consenting patients at the Eye Center were reviewed for graft survival and immune reactions. Results: We asked 1818 patients after DMEK to report their history of splenectomy. A total of 1340 patients responded and were included in the study. Of these 1340 patients, 16 (1.2%) reported a history of splenectomy (ie, 26 DMEKs, with 10 patients being transplanted in both eyes and 6 patients being transplanted in 1 eye; median age at surgery 73.7, range 66.7-76.1 y). The remaining patients (1324 patients, ie, 1941 eyes) served as controls, with 1941 DMEKs (median age at surgery 71.5, range 64.1-77.2 y). Five (19%) out of the 26 eyes from the splenectomy group required a second transplant due to dislocation (n=2.8%), failure (n=2.8%), and rejection (n=1.4%). Kaplan-Meier analysis revealed no relevant difference compared with controls. Conclusions: Our results suggest that splenectomy has no major effect on the outcome following DMEK. Subsequent, ACAID may not be the main reason for the favorable immunological outcomes in DMEK, or the camero-splenic axis may be subordinate in humans. However, we only included 16 patients who underwent splenectomy, so it might be possible that we missed a minor effect. UR - https://www.i-jmr.org/2024/1/e50106 UR - http://dx.doi.org/10.2196/50106 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/50106 ER - TY - JOUR AU - Lin, Senlin AU - Ma, Yingyan AU - Jiang, Yanwei AU - Li, Wenwen AU - Peng, Yajun AU - Yu, Tao AU - Xu, Yi AU - Zhu, Jianfeng AU - Lu, Lina AU - Zou, Haidong PY - 2024/4/17 TI - Service Quality and Residents? Preferences for Facilitated Self-Service Fundus Disease Screening: Cross-Sectional Study JO - J Med Internet Res SP - e45545 VL - 26 KW - digital technology KW - screening KW - self-service KW - eye disease KW - health economics evaluation KW - health technology assessment KW - disease screening KW - artificial intelligence KW - AI KW - eye KW - community KW - effectiveness KW - screening efficiency KW - safety N2 - Background: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents? preference for this new pattern are unclear. Objective: This study aimed to compare the service quality and residents? preferences between facilitated self-service eye screening and traditional manual screening and to explore the relationships between the screening service?s quality and residents? preferences. Methods: We conducted a cross-sectional study in Shanghai, China. Residents who underwent facilitated self-service fundus disease screening at one of the screening sites were assigned to the exposure group; those who were screened with a traditional fundus camera operated by an optometrist at an adjacent site comprised the control group. The primary outcome was the screening service quality, including effectiveness (image quality and screening efficiency), physiological discomfort, safety, convenience, and trustworthiness. The secondary outcome was the participants? preferences. Differences in service quality and the participants? preferences between the 2 groups were compared using chi-square tests separately. Subgroup analyses for exploring the relationships between the screening service?s quality and residents? preference were conducted using generalized logit models. Results: A total of 358 residents enrolled; among them, 176 (49.16%) were included in the exposure group and the remaining 182 (50.84%) in the control group. Residents? basic characteristics were balanced between the 2 groups. There was no significant difference in service quality between the 2 groups (image quality pass rate: P=.79; average screening time: P=.57; no physiological discomfort rate: P=.92; safety rate: P=.78; convenience rate: P=.95; trustworthiness rate: P=.20). However, the proportion of participants who were willing to use the same technology for their next screening was significantly lower in the exposure group than in the control group (P<.001). Subgroup analyses suggest that distrust in the facilitated self-service eye screening might increase the probability of refusal to undergo screening (P=.02). Conclusions: This study confirms that the facilitated self-service fundus disease screening pattern could achieve good service quality. However, it was difficult to reverse residents? preferences for manual screening in a short period, especially when the original manual service was already excellent. Therefore, the digital transformation of health care must be cautious. We suggest that attention be paid to the residents? individual needs. More efficient man-machine collaboration and personalized health management solutions based on large language models are both needed. UR - https://www.jmir.org/2024/1/e45545 UR - http://dx.doi.org/10.2196/45545 UR - http://www.ncbi.nlm.nih.gov/pubmed/38630535 ID - info:doi/10.2196/45545 ER - TY - JOUR AU - Wang, Zheng AU - Kempen, John AU - Luo, Gang PY - 2024/4/4 TI - Using Smartphones to Enhance Vision Screening in Rural Areas: Pilot Study JO - JMIR Form Res SP - e55270 VL - 8 KW - vision screening KW - refractive error KW - strabismus KW - smartphone KW - visual acuity KW - vision KW - visual KW - eye KW - eyes KW - screening KW - mHealth KW - mobile health KW - app KW - apps KW - application KW - applications KW - feasibility KW - optometry KW - ophthalmology N2 - Background: While it is treatable, uncorrected refractive error is the number one cause of visual impairment worldwide. This eye condition alone, or together with ocular misalignment, can also cause amblyopia, which is also treatable if detected early but still occurs in about 4% of the population. Mass vision screening is the first and most critical step to address these issues, but due to limited resources, vision screening in many rural areas remains a major challenge. Objective: We aimed to pilot-test the feasibility of using smartphone apps to enhance vision screening in areas where access to eye care is limited. Methods: A vision screening program was piggybacked on a charity summer camp program in a rural county in Sichuan, China. A total of 73 fourth and fifth graders were tested for visual acuity using a standard eye chart and were then tested for refractive error and heterophoria using 2 smartphone apps (a refraction app and a strabismus app, respectively) by nonprofessional personnel. Results: A total of 5 of 73 (6.8%, 95% CI 2.3%-15.3%) students were found to have visual acuity worse than 20/20 (logarithm of minimal angle of resolution [logMAR] 0) in at least one eye. Among the 5 students, 3 primarily had refractive error according to the refraction app. The other 2 students had manifest strabismus (one with 72?prism diopter [PD] esotropia and one with 33-PD exotropia) according to the strabismus app. Students without manifest strabismus were also measured for phoria using the strabismus app in cover/uncover mode. The median phoria was 0.0-PD (IQR 2.9-PD esophoria to 2.2-PD exophoria). Conclusions: The results from this vision screening study are consistent with findings from other population-based vision screening studies in which conventional tools were used by ophthalmic professionals. The smartphone apps are promising and have the potential to be used in mass vision screenings for identifying risk factors for amblyopia and for myopia control. The smartphone apps may have significant implications for the future of low-cost vision care, particularly in resource-constrained and geographically remote areas. UR - https://formative.jmir.org/2024/1/e55270 UR - http://dx.doi.org/10.2196/55270 UR - http://www.ncbi.nlm.nih.gov/pubmed/38573757 ID - info:doi/10.2196/55270 ER - TY - JOUR AU - Gerbutavicius, Rokas AU - Merle, A. David AU - Wolf, Armin AU - Dimopoulos, Spyridon AU - Kortuem, Ulrich Karsten AU - Kortuem, Charlotte Friederike PY - 2024/3/29 TI - User Friendliness and Perioperative Guidance Benefits of a Cataract Surgery Education App: Randomized Controlled Trial JO - JMIR Form Res SP - e55742 VL - 8 KW - mHealth KW - mobile health KW - workflow optimization KW - patient satisfaction KW - health education KW - educational background KW - phacoemulsification N2 - Background: Cataract surgeries are among the most performed surgeries worldwide. A thorough patient education is essential to inform patients about the perioperative process and postoperative target results concerning the intraocular lens and objectives for visual outcomes. However, addressing all relevant aspects and questions is time-consuming. Mobile apps can facilitate this process for both patients and physicians and thus be beneficial. However, the success of such an app depends on its user friendliness and acceptance by patients. Objective: This study aimed to evaluate the user friendliness and acceptance of a cataract surgery education app on mobile devices among patients undergoing cataract surgery, the characteristics of patients who benefit the most from app use, and the influence of the app on patient satisfaction with treatment. Methods: All patients who underwent cataract surgery at an ophthalmological practice from August 2020 to July 2021 were invited to participate in this randomized controlled trial. Out of 493 invited patients, 297 (60.2%) were enrolled in this study. Patients were randomized into 3 different groups. Half of the patients were offered to participate in Group 1 with use of the ?Patient Journey? app. However, if they decided not to use the app, they were included in Group 2 (app denial). The other half of the patients were included in Group 3 (control) with no use of the app and with information provided conventionally. The app provided general information on the ophthalmological center, surgeons, cataract, and treatment options. Different questionnaires were used in all 3 groups to evaluate satisfaction with the perioperative process. Group 1 evaluated the app. Demographic characteristics, such as age, gender, and educational degree, were assessed. Results: Group 1 included 77 patients (median age 69 years). Group 2 included 61 patients, and their median age was higher (median age 79 years). Group 3 included 159 patients (median age 74 years). There was no difference in satisfaction with the perioperative process and clinic between the 3 groups. Almost all app users appreciated the digital details provided for the organization and the information on the surgery. Age did not play a major role in appreciation of the app. Female patients tended to appreciate the information provided more than male patients. Patients who did not have a higher university degree experienced more benefits from the informational content of the app and were the most satisfied with the information. However, male patients and academics were in general more aware of technology and handled the app more easily. Conclusions: The app showed high user friendliness and acceptance, and could particularly benefit specific patient groups. App users demonstrated a noninferior high satisfaction with the treatment in the ophthalmological center in comparison with patients who were informed about the surgery only conventionally. UR - https://formative.jmir.org/2024/1/e55742 UR - http://dx.doi.org/10.2196/55742 UR - http://www.ncbi.nlm.nih.gov/pubmed/38551619 ID - info:doi/10.2196/55742 ER - TY - JOUR AU - Pallerla, R. Srinivasa AU - Pallerla, R. Madhurima AU - Krishnaiah, Sannapaneni PY - 2024/1/9 TI - Trends in the Ophthalmic Workforce and Eye Care Infrastructure in South India: Cross-Sectional Questionnaire Study JO - Online J Public Health Inform SP - e50921 VL - 16 KW - trends KW - human resources KW - infrastructure KW - eye care KW - South India N2 - Background: This study is part of broad-based research to determine the impact of blindness control activities in general and with special reference to the Andhra Pradesh Right to Sight Society (APRTSS) activities in the southern Indian states of Andhra Pradesh and Telangana. As part of the global ?VISION 2020: The Right to Sight? initiative, the APRTSS was established in the undivided state of Andhra Pradesh in 2002. Since then, the APRTSS has been actively implementing the strategies of VISION 2020 to reduce visual impairment and blindness in the state. Objective: The availability and distribution of the eye care workforce are essential to reach the goals of VISION 2020: The Right to Sight, the global initiative to eliminate avoidable blindness. This study assessed the trends in the availability and distribution of eye health professionals and eye care infrastructure in 2 southern Indian states: Andhra Pradesh and Telangana. Methods: This cross-sectional study used a pretested questionnaire to gather data for the year from 2012 to 2013. Data for 2002 to 2003 were collected from available historical records. The questionnaires were pretested in a pilot study conducted before the main survey. Pretested questionnaires were administered to all eye care professionals?ophthalmologists (n=1712) and midlevel ophthalmic personnel (MLOP; n=1250)?eye care facilities with ?10 inpatient beds or performing ?100 cataract surgeries per annum (n=640), local nongovernmental eye care organizations (n=182), and international eye care organizations (n=10). Data were collected for 2 different time periods: the baseline year of 2002 to 2003 and the target year of 2012 to 2013. Data analysis was conducted using SPSS version 19.0. Results: The response rates were 81.1% (519/640) for eye care facilities, 96.1% (1645/1712) for ophthalmologists, and 67.6% (845/1250) for MLOP. From 2002-2003 to 2012-2013, there has been an increase in eye care facilities, from 234 to 519 (121.8%); ophthalmologists, from 935 to 1712 (83.1%); and MLOP, from 767 to 1250 (63%). The ophthalmologist:population ratio improved from 1:88,260 in 2002-2003 to 1:51,468 in 2012-2013. The MLOP:population ratio improved from 1:168,283 in 2002-2003 to 1:138,117 in 2012-2013 but still falls short of the ideal number. Conclusions: Both southern Indian states are able to meet the requirements for ophthalmologists and eyecare infrastructure as per the goals of VISION 2020. However, the number of MLOP falls short of the ideal ratio for the population. This study has some limitations. For example, most of the data collected through questionnaires were based on self-report, which might introduce bias due to memory recall or over or under-reporting of certain information. However, this was addressed by cross-checking the collected data with information from supplementary sources. UR - https://ojphi.jmir.org/2024/1/e50921 UR - http://dx.doi.org/10.2196/50921 UR - http://www.ncbi.nlm.nih.gov/pubmed/38261522 ID - info:doi/10.2196/50921 ER - TY - JOUR AU - Wong, Kang-An AU - Ang, Hou Bryan Chin AU - Gunasekeran, Visva Dinesh AU - Husain, Rahat AU - Boon, Joewee AU - Vikneson, Krishna AU - Tan, Qi Zyna Pei AU - Tan, Wei Gavin Siew AU - Wong, Yin Tien AU - Agrawal, Rupesh PY - 2023/10/19 TI - Remote Perimetry in a Virtual Reality Metaverse Environment for Out-of-Hospital Functional Eye Screening Compared Against the Gold Standard Humphrey Visual Fields Perimeter: Proof-of-Concept Pilot Study JO - J Med Internet Res SP - e45044 VL - 25 KW - eye KW - screening KW - glaucoma KW - virtual reality KW - metaverse KW - digital health KW - visual impairment KW - visually impaired KW - functional testing KW - ophthalmologic KW - ophthalmology KW - remote care KW - visual field KW - HVF KW - perimetry test N2 - Background: The growing global burden of visual impairment necessitates better population eye screening for early detection of eye diseases. However, accessibility to testing is often limited and centralized at in-hospital settings. Furthermore, many eye screening programs were disrupted by the COVID-19 pandemic, presenting an urgent need for out-of-hospital solutions. Objective: This study investigates the performance of a novel remote perimetry application designed in a virtual reality metaverse environment to enable functional testing in community-based and primary care settings. Methods: This was a prospective observational study investigating the performance of a novel remote perimetry solution in comparison with the gold standard Humphrey visual field (HVF) perimeter. Subjects received a comprehensive ophthalmologic assessment, HVF perimetry, and remote perimetry testing. The primary outcome measure was the agreement in the classification of overall perimetry result normality by the HVF (Swedish interactive threshold algorithm?fast) and testing with the novel algorithm. Secondary outcome measures included concordance of individual testing points and perimetry topographic maps. Results: We recruited 10 subjects with an average age of 59.6 (range 28-81) years. Of these, 7 (70%) were male and 3 (30%) were female. The agreement in the classification of overall perimetry results was high (9/10, 90%). The pointwise concordance in the automated classification of individual test points was 83.3% (8.2%; range 75%-100%). In addition, there was good perimetry topographic concordance with the HVF in all subjects. Conclusions: Remote perimetry in a metaverse environment had good concordance with gold standard perimetry using the HVF and could potentially avail functional eye screening in out-of-hospital settings. UR - https://www.jmir.org/2023/1/e45044 UR - http://dx.doi.org/10.2196/45044 UR - http://www.ncbi.nlm.nih.gov/pubmed/37856179 ID - info:doi/10.2196/45044 ER - TY - JOUR AU - Nagino, Ken AU - Okumura, Yuichi AU - Akasaki, Yasutsugu AU - Fujio, Kenta AU - Huang, Tianxiang AU - Sung, Jaemyoung AU - Midorikawa-Inomata, Akie AU - Fujimoto, Keiichi AU - Eguchi, Atsuko AU - Hurramhon, Shokirova AU - Yee, Alan AU - Miura, Maria AU - Ohno, Mizu AU - Hirosawa, Kunihiko AU - Morooka, Yuki AU - Murakami, Akira AU - Kobayashi, Hiroyuki AU - Inomata, Takenori PY - 2023/8/3 TI - Smartphone App?Based and Paper-Based Patient-Reported Outcomes Using a Disease-Specific Questionnaire for Dry Eye Disease: Randomized Crossover Equivalence Study JO - J Med Internet Res SP - e42638 VL - 25 KW - dry eye syndrome KW - mobile app KW - equivalence trial KW - Ocular Surface Disease Index KW - patient-reported outcome measures KW - mobile health KW - reliability KW - validity KW - telemedicine KW - precision medicine N2 - Background: Using traditional patient-reported outcomes (PROs), such as paper-based questionnaires, is cumbersome in the era of web-based medical consultation and telemedicine. Electronic PROs may reduce the burden on patients if implemented widely. Considering promising reports of DryEyeRhythm, our in-house mHealth smartphone app for investigating dry eye disease (DED) and the electronic and paper-based Ocular Surface Disease Index (OSDI) should be evaluated and compared to determine their equivalency. Objective: The purpose of this study is to assess the equivalence between smartphone app?based and paper-based questionnaires for DED. Methods: This prospective, nonblinded, randomized crossover study enrolled 34 participants between April 2022 and June 2022 at a university hospital in Japan. The participants were allocated randomly into 2 groups in a 1:1 ratio. The paper-app group initially responded to the paper-based Japanese version of the OSDI (J-OSDI), followed by the app-based J-OSDI. The app-paper group responded to similar questionnaires but in reverse order. We performed an equivalence test based on minimal clinically important differences to assess the equivalence of the J-OSDI total scores between the 2 platforms (paper-based vs app-based). A 95% CI of the mean difference between the J-OSDI total scores within the ±7.0 range between the 2 platforms indicated equivalence. The internal consistency and agreement of the app-based J-OSDI were assessed with Cronbach ? coefficients and intraclass correlation coefficient values. Results: A total of 33 participants were included in this study. The total scores for the app- and paper-based J-OSDI indicated satisfactory equivalence per our study definition (mean difference 1.8, 95% CI ?1.4 to 5.0). Moreover, the app-based J-OSDI total score demonstrated good internal consistency and agreement (Cronbach ?=.958; intraclass correlation=0.919; 95% CI 0.842 to 0.959) and was significantly correlated with its paper-based counterpart (Pearson correlation=0.932, P<.001). Conclusions: This study demonstrated the equivalence of PROs between the app- and paper-based J-OSDI. Implementing the app-based J-OSDI in various scenarios, including telehealth, may have implications for the early diagnosis of DED and longitudinal monitoring of PROs. UR - https://www.jmir.org/2023/1/e42638 UR - http://dx.doi.org/10.2196/42638 UR - http://www.ncbi.nlm.nih.gov/pubmed/37535409 ID - info:doi/10.2196/42638 ER - TY - JOUR AU - Gupta, C. Juhi AU - Arora, M. Vineet AU - Vollbrecht, Hanna AU - Kappel, Nicole AU - Meltzer, O. David AU - Press, G. Valerie PY - 2023/5/24 TI - The Relationship Between Insufficient Vision and Technology Access and Use Among Hospitalized Adults at an Urban Academic Hospital: Observational Study JO - JMIR Form Res SP - e40103 VL - 7 KW - vision KW - health technology KW - chronic disease KW - ownership KW - internet KW - eHealth KW - digital health KW - eye KW - optometry KW - myopia KW - ophthalmology KW - myopic KW - digital device KW - observational study KW - use KW - visual impairment KW - visually impaired N2 - Background: The role of sufficient vision in self-management is salient with respect to the growing prevalence of eHealth-based interventions for chronic diseases. However, the relationship between insufficient vision and self-management has been understudied. Objective: We aimed to assess differences in access to and use of technology among adults with and without insufficient vision at an academic urban hospital. Methods: This is an observational study of hospitalized adult general medicine patients that is part of a larger quality improvement study called the hospitalist study. The hospitalist study provided demographic and health literacy data (Brief Health Literacy Screen). Our substudy included several measures. Validated surveys assessed technology access and use, and included benchmarked questions from the National Pew Survey to determine access to, willingness to use, and self-described ability to use technology at home, particularly for self-management, and eHealth-specific questions assessing future willingness to access eHealth post discharge. The eHealth Literacy Scale (eHEALS) was used to assess eHealth literacy. Visual acuity was assessed using the Snellen pocket eye chart with low vision defined as visual acuity ?20/50 in at least one eye. Descriptive statistics, bivariate chi-square analyses, and multivariate logistic regressions (adjusted for age, race, gender, education level, and eHealth literacy) were performed using Stata. Results: A total of 59 participants completed our substudy. The mean age was 54 (SD 16.4) years. Demographic data from the hospitalist study was missing for several participants. Among those who responded, most identified as Black (n=34, 79%) and female (n=26, 57%), and most reported at least some college education (n=30, 67%). Most participants owned technology devices (n=57, 97%) and had previously used the internet (n=52, 86%), with no significant differences between those with insufficient and sufficient vision (n=34 vs n=25). Though there was a 2x effect size for laptop ownership, with those with sufficient vision more likely to own a laptop, those with insufficient vision versus sufficient vision were less likely to report an ability to perform online tasks without assistance, including using a search engine (n=22, 65% vs n=23, 92%; P=.02), opening an attachment (n=17, 50% vs n=22, 88%; P=.002), and using an online video (n=20, 59% vs n=22, 88%; P=.01). In multivariate analysis, the ability to independently open an online attachment did not remain statistically significant (P=.01). Conclusions: Technology device ownership and internet use rates are high in this population, yet participants with insufficient vision (vs sufficient vision) reported a reduced ability to independently perform online tasks. To ensure the effective use of eHealth technologies by at-risk populations, the relationship between vision and technology use needs to be further studied. UR - https://formative.jmir.org/2023/1/e40103 UR - http://dx.doi.org/10.2196/40103 UR - http://www.ncbi.nlm.nih.gov/pubmed/37223969 ID - info:doi/10.2196/40103 ER - TY - JOUR AU - Mbwogge, Mathew AU - Astbury, Nicholas AU - Nkumbe, Ebong Henry AU - Bunce, Catey AU - Bascaran, Covadonga PY - 2022/8/9 TI - Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention JO - JMIRx Med SP - e34263 VL - 3 IS - 3 KW - waiting time KW - waiting list KW - patient satisfaction KW - quality improvement KW - clinical audit KW - ophthalmology KW - patient-centered care N2 - Background: Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles. Objective: The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction. Methods: This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time. Results: In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; ?23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92). Conclusions: Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff. UR - https://med.jmirx.org/2022/3/e34263 UR - http://dx.doi.org/10.2196/34263 UR - http://www.ncbi.nlm.nih.gov/pubmed/37725529 ID - info:doi/10.2196/34263 ER - TY - JOUR AU - Zhao, Junqiang AU - Lu, Yi AU - Qian, Yong AU - Luo, Yuxin AU - Yang, Weihua PY - 2022/6/14 TI - Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study JO - J Med Internet Res SP - e37532 VL - 24 IS - 6 KW - artificial intelligence KW - retinal disease KW - data visualization KW - bibliometric KW - citespace, VOSviewer KW - retinal KW - eye KW - visual impairment N2 - Background: Patients with retinal diseases may exhibit serious complications that cause severe visual impairment owing to a lack of awareness of retinal diseases and limited medical resources. Understanding how artificial intelligence (AI) is used to make predictions and perform relevant analyses is a very active area of research on retinal diseases. In this study, the relevant Science Citation Index (SCI) literature on the AI of retinal diseases published from 2012 to 2021 was integrated and analyzed. Objective: The aim of this study was to gain insights into the overall application of AI technology to the research of retinal diseases from set time and space dimensions. Methods: Citation data downloaded from the Web of Science Core Collection database for AI in retinal disease publications from January 1, 2012, to December 31, 2021, were considered for this analysis. Information retrieval was analyzed using the online analysis platforms of literature metrology: Bibliometrc, CiteSpace V, and VOSviewer. Results: A total of 197 institutions from 86 countries contributed to relevant publications; China had the largest number and researchers from University College London had the highest H-index. The reference clusters of SCI papers were clustered into 12 categories. ?Deep learning? was the cluster with the widest range of cocited references. The burst keywords represented the research frontiers in 2018-2021, which were ?eye disease? and ?enhancement.? Conclusions: This study provides a systematic analysis method on the literature regarding AI in retinal diseases. Bibliometric analysis enabled obtaining results that were objective and comprehensive. In the future, high-quality retinal image?forming AI technology with strong stability and clinical applicability will continue to be encouraged. UR - https://www.jmir.org/2022/6/e37532 UR - http://dx.doi.org/10.2196/37532 UR - http://www.ncbi.nlm.nih.gov/pubmed/35700021 ID - info:doi/10.2196/37532 ER - TY - JOUR AU - Ramchandran, S. Rajeev AU - Yousefi-Nooraie, Reza AU - Dadgostar, Porooshat AU - Yilmaz, Sule AU - Basant, Jesica AU - Dozier, M. Ann PY - 2022/3/30 TI - Implementation of Teleophthalmology to Improve Diabetic Retinopathy Surveillance: Qualitative Interview Study of Clinical Staff Informed by Implementation Science Frameworks JO - JMIR Diabetes SP - e32162 VL - 7 IS - 1 KW - Consolidated Framework for Implementation Research KW - teleophthalmology KW - diabetic retinopathy KW - implementation KW - qualitative study KW - Practical, Robust Implementation and Sustainability Model N2 - Background: The store-and-forward camera-based evaluation of the eye, or teleophthalmology, is an effective way to identify diabetic retinopathy, the leading cause of blindness in the United States, but uptake has been slow. Understanding the barriers to and facilitators of implementing teleophthalmology programs from those actively adopting, running, and sustaining such programs is important for widespread adoption. Objective: This study aims to understand the factors that are important in introducing teleophthalmology to improve access to diagnostic eye care for patients with diabetes in primary care clinics by using implementation science. Methods: This qualitative study in 3 urban, low-income, largely racial and ethnic minority?serving safety-net primary care clinics in Rochester, New York, interviewed nurses and physicians on implementing a teleophthalmology program by using questions informed by the Practical, Robust Implementation and Sustainability Model and the Consolidated Framework for Implementation Research. Results: Primary care nurses operationalizing the program in their clinics saw increased work burden and a lack of self-efficacy as barriers. Continuous training on the teleophthalmology process for nurses, physicians, and administrative staff through in-service and peer training by champions and superusers were identified by interviewees as needs. Facilitators included the perceived convenience for the patient and a perceived educational advantage to the program, as it gave an opportunity for providers to discuss the importance of eye care with patients. Concerns in making and tracking referrals to ophthalmology because of challenges related to care coordination were highlighted. The financial aspects of the program (eg, patient coverage and care provider reimbursement) were unclear to many staff members, influencing adoption and sustainability. Conclusions: Streamlining processes and workflows, training and assigning adequate staff, effectively coordinating care between primary care and eye care to improve follow-ups, and ensuring financial viability can all help streamline the adoption of teleophthalmology. UR - https://diabetes.jmir.org/2022/1/e32162 UR - http://dx.doi.org/10.2196/32162 UR - http://www.ncbi.nlm.nih.gov/pubmed/35353038 ID - info:doi/10.2196/32162 ER - TY - JOUR AU - Gilbert, M. Rose AU - Sumodhee, Dayyanah AU - Pontikos, Nikolas AU - Hollyhead, Catherine AU - Patrick, Angus AU - Scarles, Samuel AU - Van Der Smissen, Sabrina AU - Young, M. Rodrigo AU - Nettleton, Nick AU - Webster, R. Andrew AU - Cammack, Jocelyn PY - 2022/1/31 TI - Collaborative Research and Development of a Novel, Patient-Centered Digital Platform (MyEyeSite) for Rare Inherited Retinal Disease Data: Acceptability and Feasibility Study JO - JMIR Form Res SP - e21341 VL - 6 IS - 1 KW - MyEyeSite KW - inherited retinal diseases (IRD) KW - rare diseases KW - genetics KW - ophthalmology KW - digital health KW - eye data KW - GDPR KW - subject access request (SAR) KW - mobile phone N2 - Background: Inherited retinal diseases (IRDs) are a leading cause of blindness in children and working age adults in the United Kingdom and other countries, with an appreciable socioeconomic impact. However, by definition, IRD data are individually rare, and as a result, this patient group has been underserved by research. Researchers need larger amounts of these rare data to make progress in this field, for example, through the development of gene therapies. The challenge has been how to find and make these data available to researchers in the most productive way. MyEyeSite is a research collaboration aiming to design and develop a digital platform (the MyEyeSite platform) for people with rare IRDs that will enable patients, doctors, and researchers to aggregate and share specialist eye health data. A crucial component of this platform is the MyEyeSite patient application, which will provide the means for patients with IRD to interact with the system and, in particular, to collate, manage, and share their personal specialist IRD data both for research and their own health care. Objective: This study aims to test the acceptability and feasibility of the MyEyeSite platform in the target IRD population through a collaborative patient-centered study. Methods: Qualitative data were generated through focus groups and workshops, and quantitative data were obtained through a survey of patients with IRD. Participants were recruited through clinics at Moorfields Eye Hospital National Health Service (NHS) Foundation Trust and the National Institute for Health Research (NIHR) Moorfields Biomedical Research Centre through their patient and public involvement databases. Results: Our IRD focus group sample (n=50) highlighted the following themes: frustration with the current system regarding data sharing within the United Kingdom?s NHS; positive expectations of the potential benefits of the MyEyeSite patient application, resulting from increased access to this specialized data; and concerns regarding data security, including potentially unethical use of the data outside the NHS. Of the surveyed 80 participants, 68 (85%) were motivated to have a more active role in their eye care and share their data for research purposes using a secure technology, such as a web application or mobile app. Conclusions: This study demonstrates that patients with IRD are highly motivated to be actively involved in managing their own data for research and their own eye care. It demonstrates the feasibility of involving patients with IRD in the detailed design of the MyEyeSite platform exemplar, with input from the patient with IRD workshops playing a key role in determining both the functionality and accessibility of the designs and prototypes. The development of a user-centered technological solution to the problem of rare health data has the potential to benefit not only the patient with IRD community but also others with rare diseases. UR - https://formative.jmir.org/2022/1/e21341 UR - http://dx.doi.org/10.2196/21341 UR - http://www.ncbi.nlm.nih.gov/pubmed/35099396 ID - info:doi/10.2196/21341 ER - TY - JOUR AU - Maile, Howard AU - Li, Olivia Ji-Peng AU - Gore, Daniel AU - Leucci, Marcello AU - Mulholland, Padraig AU - Hau, Scott AU - Szabo, Anita AU - Moghul, Ismail AU - Balaskas, Konstantinos AU - Fujinami, Kaoru AU - Hysi, Pirro AU - Davidson, Alice AU - Liskova, Petra AU - Hardcastle, Alison AU - Tuft, Stephen AU - Pontikos, Nikolas PY - 2021/12/13 TI - Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review JO - JMIR Med Inform SP - e27363 VL - 9 IS - 12 KW - artificial intelligence KW - machine learning KW - cornea KW - keratoconus KW - corneal tomography KW - subclinical KW - corneal imaging KW - decision support systems KW - corneal disease KW - keratometry N2 - Background: Keratoconus is a disorder characterized by progressive thinning and distortion of the cornea. If detected at an early stage, corneal collagen cross-linking can prevent disease progression and further visual loss. Although advanced forms are easily detected, reliable identification of subclinical disease can be problematic. Several different machine learning algorithms have been used to improve the detection of subclinical keratoconus based on the analysis of multiple types of clinical measures, such as corneal imaging, aberrometry, or biomechanical measurements. Objective: The aim of this study is to survey and critically evaluate the literature on the algorithmic detection of subclinical keratoconus and equivalent definitions. Methods: For this systematic review, we performed a structured search of the following databases: MEDLINE, Embase, and Web of Science and Cochrane Library from January 1, 2010, to October 31, 2020. We included all full-text studies that have used algorithms for the detection of subclinical keratoconus and excluded studies that did not perform validation. This systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. Results: We compared the measured parameters and the design of the machine learning algorithms reported in 26 papers that met the inclusion criteria. All salient information required for detailed comparison, including diagnostic criteria, demographic data, sample size, acquisition system, validation details, parameter inputs, machine learning algorithm, and key results are reported in this study. Conclusions: Machine learning has the potential to improve the detection of subclinical keratoconus or early keratoconus in routine ophthalmic practice. Currently, there is no consensus regarding the corneal parameters that should be included for assessment and the optimal design for the machine learning algorithm. We have identified avenues for further research to improve early detection and stratification of patients for early treatment to prevent disease progression. UR - https://medinform.jmir.org/2021/12/e27363 UR - http://dx.doi.org/10.2196/27363 UR - http://www.ncbi.nlm.nih.gov/pubmed/34898463 ID - info:doi/10.2196/27363 ER - TY - JOUR AU - Sabherwal, Shalinder AU - Chinnakaran, Anand AU - Sood, Ishaana AU - Garg, K. Gaurav AU - Singh, P. Birendra AU - Shukla, Rajan AU - Reddy, A. Priya AU - Gilbert, Suzanne AU - Bassett, Ken AU - Murthy, S. Gudlavalleti V. AU - PY - 2021/11/4 TI - Effect of Door-to-Door Screening and Awareness Generation Activities in the Catchment Areas of Vision Centers on Service Use: Protocol for a Randomized Experimental Study JO - JMIR Res Protoc SP - e31951 VL - 10 IS - 11 KW - study protocol KW - randomized intervention study KW - vision centers KW - door-to-door screening KW - cost-effectiveness KW - sustainability KW - screening KW - awareness KW - vision KW - eye KW - utilization KW - usage KW - India KW - rural KW - intervention KW - engagement KW - scalability N2 - Background: A vision center (VC) is a significant eye care service model to strengthen primary eye care services. VCs have been set up at the block level, covering a population of 150,000-250,000 in rural areas in North India. Inadequate use by rural communities is a major challenge to sustainability of these VCs. This not only reduces the community?s vision improvement potential but also impacts self-sustainability and limits expansion of services in rural areas. The current literature reports a lack of awareness regarding eye diseases and the need for care, social stigmas, low priority being given to eye problems, prevailing gender discrimination, cost, and dependence on caregivers as factors preventing the use of primary eye care. Objective: Our organization is planning an awareness-cum-engagement intervention?door-to-door basic eye checkup and visual acuity screening in VCs coverage areas?to connect with the community and improve the rational use of VCs. Methods: In this randomized, parallel-group experimental study, we will select 2 VCs each for the intervention arm and the control arm from among poor, low-performing VCs (ie, walk-in of ?10 patients/day) in our 2 operational regions (Vrindavan, Mathura District, and Mohammadi, Kheri District) of Uttar Pradesh. Intervention will include door-to-door screening and awareness generation in 8-12 villages surrounding the VCs, and control VCs will follow existing practices of awareness generation through community activities and health talks. Data will be collected from each VC for 4 months of intervention. Primary outcomes will be an increase in the number of walk-in patients, spectacle advise and uptake, referral and uptake for cataract and specialty surgery, and operational expenses. Secondary outcomes will be uptake of refraction correction and referrals for cataract and other eye conditions. Differences in the number of walk-in patients, referrals, uptake of services, and cost involved will be analyzed. Results: Background work involved planning of interventions and selection of VCs has been completed. Participant recruitment has begun and is currently in progress. Conclusions: Through this study, we will analyze whether our door-to-door intervention is effective in increasing the number of visits to a VC and, thus, overall sustainability. We will also study the cost-effectiveness of this intervention to recommend its scalability. Trial Registration: ClinicalTrials.gov NCT04800718; https://clinicaltrials.gov/ct2/show/NCT04800718 International Registered Report Identifier (IRRID): DERR1-10.2196/31951 UR - https://www.researchprotocols.org/2021/11/e31951 UR - http://dx.doi.org/10.2196/31951 UR - http://www.ncbi.nlm.nih.gov/pubmed/34734839 ID - info:doi/10.2196/31951 ER - TY - JOUR AU - Shrestha, Manisha AU - Bhandari, Gopal AU - Rathi, Kumar Suresh AU - Gudlavalleti, Gaurang Anirudh AU - Pandey, Binod AU - Ghimire, Ramesh AU - Ale, Daman AU - Kayastha, Sajani AU - Chaudhary, Shankar Daya AU - Byanju, Raghunandan AU - PY - 2021/10/8 TI - Improving the Follow-up Rate for Pediatric Patients (0-16 years) of an Eye Hospital in Nepal: Protocol for a Public Health Intervention Study JO - JMIR Res Protoc SP - e31578 VL - 10 IS - 10 KW - counseling KW - follow-up KW - intervention study KW - pediatric patients KW - ophthalmology KW - public health KW - Nepal N2 - Background: The follow-up of pediatric patients ensures regular ocular morbidity monitoring and better treatment outcome. Hiralal Santudevi Pradhan Institute of Ophthalmic Science (Bharatpur Eye Hospital [BEH]) noticed that the follow-up rate was only 22% among its pediatric patients. Several factors like lack of awareness and forgetfulness among patients may contribute to a lower number of follow-up visits. Therefore, BEH decided to find if counseling and reminders through SMS text messaging and phone calls would improve the follow-up rates. Objective: This study aims to evaluate the impact of interventions like counseling and reminder SMS text messaging and phone calls in improving the follow-up rate of pediatric patients. Methods: This is a public health intervention study being conducted using quantitative analysis. All children (0-16 years) with ocular conditions requiring at least 3 follow-up visits in the study period will be included. In all, 264 participants will be allocated to 3 groups: routine standard care, counseling, and reminders with SMS text messaging and phone calls. In counseling, patients will take part in 20-minute counseling sessions with trained counselors at each visit, and information leaflets will be provided to them. In the reminder SMS text messaging and phone call group, patients will receive an SMS text message 3 days prior and a phone call 1 day prior to their scheduled visits. Patients attending within 2 days of the scheduled date will be considered compliant to follow-up. The proportion of patients completing all the follow-up visits in each group will be assessed. Informed consent will be taken from parents and children. Univariate and multivariate analyses will be conducted. Results: The ethical approval for this study has been obtained from the Ethical Review Board (ERB) of Nepal Health Research Council (ERB protocol registration #761/2020 P). The data collection was initiated on January, 24, 2021, but due to the COVID-19 pandemic, as of September 2021, we have only been able to enroll 154 of the planned 264 participants (58.3% of the sample size). Conclusions: This study will reliably document not only the factors associated with follow-up rate through an intervention package (counseling and reminders through SMS text messaging and phone calls) but also the cost effectiveness of the intervention package, which can be applied in all the departments of the hospital. Trial Registration: ClinicalTrials.gov NCT04837534; https://clinicaltrials.gov/ct2/show/NCT04837534 International Registered Report Identifier (IRRID): DERR1-10.2196/31578 UR - https://www.researchprotocols.org/2021/10/e31578 UR - http://dx.doi.org/10.2196/31578 UR - http://www.ncbi.nlm.nih.gov/pubmed/34521615 ID - info:doi/10.2196/31578 ER - TY - JOUR AU - Cao, Jiamin AU - Wang, Nuo AU - Hou, Shiying AU - Qi, Xin AU - Chen, Yu AU - Xiong, Wei PY - 2021/9/28 TI - Overview of Graves Ophthalmopathy Literature From 1999 to 2019: Bibliometric Analysis JO - Interact J Med Res SP - e24831 VL - 10 IS - 3 KW - Graves ophthalmopathy KW - bibliometric analysis KW - CiteSpace KW - Web of Science N2 - Background: Research on Graves ophthalmopathy has increased remarkably over the last 2 decades; however, few statistical analyses of the data presented in these publications have been conducted. Objective: This study aims to detect and analyze emerging trends and collaboration networks in Graves ophthalmopathy research. Methods: Graves ophthalmopathy?related publications from 1999 to 2019 were collected from the Web of Science Core Collection Database. Collected publications were restricted by category (article or review) and language (English). Bibliometric analyses included changes in the annual numbers of publications, journals, authors, countries, institutions, keywords, and references. Results: In total, 3051 publications that met the criteria were collected. The number of annual publications has exhibited an increasing trend over the last 20 years. The journal Thyroid ranked first, publishing 183 Graves ophthalmopathy?related studies. There was no evidence of a relationship between impact factor (IF) and the number of publications (P=.69). The author Smith TJ had the largest number of publications on Graves ophthalmopathy (n=83). Of the countries that had published Graves ophthalmopathy?related articles, the United States had the largest number (n=784) and the highest centrality (0.18). Among institutions, the University of Pisa (Italy) contributed the most Graves ophthalmopathy?related articles (n=114). The most recent burst keywords (proliferation, rituximab, and selenium) and references may provide clues on emerging trends in research and clinical practice. Conclusions: This bibliometric analysis highlights countries, institutions, and authors who contributed to Graves ophthalmopathy?related publications. Emerging trends in Graves ophthalmopathy research, based on burst keywords and references, may provide clues relevant to clinical practice and future research. UR - https://www.i-jmr.org/2021/3/e24831 UR - http://dx.doi.org/10.2196/24831 UR - http://www.ncbi.nlm.nih.gov/pubmed/34581676 ID - info:doi/10.2196/24831 ER - TY - JOUR AU - Saeed, Q. Ali AU - Sheikh Abdullah, Huda Siti Norul AU - Che-Hamzah, Jemaima AU - Abdul Ghani, Tarmizi Ahmad PY - 2021/9/21 TI - Accuracy of Using Generative Adversarial Networks for Glaucoma Detection: Systematic Review and Bibliometric Analysis JO - J Med Internet Res SP - e27414 VL - 23 IS - 9 KW - glaucoma KW - generative adversarial network KW - deep learning KW - systematic literature review KW - retinal disease KW - blood vessels KW - optic disc N2 - Background: Glaucoma leads to irreversible blindness. Globally, it is the second most common retinal disease that leads to blindness, slightly less common than cataracts. Therefore, there is a great need to avoid the silent growth of this disease using recently developed generative adversarial networks (GANs). Objective: This paper aims to introduce a GAN technology for the diagnosis of eye disorders, particularly glaucoma. This paper illustrates deep adversarial learning as a potential diagnostic tool and the challenges involved in its implementation. This study describes and analyzes many of the pitfalls and problems that researchers will need to overcome to implement this kind of technology. Methods: To organize this review comprehensively, articles and reviews were collected using the following keywords: (?Glaucoma,? ?optic disc,? ?blood vessels?) and (?receptive field,? ?loss function,? ?GAN,? ?Generative Adversarial Network,? ?Deep learning,? ?CNN,? ?convolutional neural network? OR encoder). The records were identified from 5 highly reputed databases: IEEE Xplore, Web of Science, Scopus, ScienceDirect, and PubMed. These libraries broadly cover the technical and medical literature. Publications within the last 5 years, specifically 2015-2020, were included because the target GAN technique was invented only in 2014 and the publishing date of the collected papers was not earlier than 2016. Duplicate records were removed, and irrelevant titles and abstracts were excluded. In addition, we excluded papers that used optical coherence tomography and visual field images, except for those with 2D images. A large-scale systematic analysis was performed, and then a summarized taxonomy was generated. Furthermore, the results of the collected articles were summarized and a visual representation of the results was presented on a T-shaped matrix diagram. This study was conducted between March 2020 and November 2020. Results: We found 59 articles after conducting a comprehensive survey of the literature. Among the 59 articles, 30 present actual attempts to synthesize images and provide accurate segmentation/classification using single/multiple landmarks or share certain experiences. The other 29 articles discuss the recent advances in GANs, do practical experiments, and contain analytical studies of retinal disease. Conclusions: Recent deep learning techniques, namely GANs, have shown encouraging performance in retinal disease detection. Although this methodology involves an extensive computing budget and optimization process, it saturates the greedy nature of deep learning techniques by synthesizing images and solves major medical issues. This paper contributes to this research field by offering a thorough analysis of existing works, highlighting current limitations, and suggesting alternatives to support other researchers and participants in further improving and strengthening future work. Finally, new directions for this research have been identified. UR - https://www.jmir.org/2021/9/e27414 UR - http://dx.doi.org/10.2196/27414 UR - http://www.ncbi.nlm.nih.gov/pubmed/34236992 ID - info:doi/10.2196/27414 ER - TY - JOUR AU - Nida, Kedir Esmael AU - Bekele, Sisay AU - Geurts, Luc AU - Vanden Abeele, Vero PY - 2021/9/17 TI - Acceptance of a Smartphone-Based Visual Field Screening Platform for Glaucoma: Pre-Post Study JO - JMIR Form Res SP - e26602 VL - 5 IS - 9 KW - mHealth acceptance KW - UTAUT KW - glaucoma screening KW - mhealth for eye care KW - mhealth KW - glaucoma KW - visual KW - eye KW - ophthalmology KW - ophthalmic KW - mobile phone N2 - Background: Glaucoma, the silent thief of sight, is a major cause of blindness worldwide. It is a burden for people in low-income countries, specifically countries where glaucoma-induced blindness accounts for 15% of the total incidence of blindness. More than half the people living with glaucoma in low-income countries are unaware of the disease until it progresses to an advanced stage, resulting in permanent visual impairment. Objective: This study aims to evaluate the acceptability of the Glaucoma Easy Screener (GES), a low-cost and portable visual field screening platform comprising a smartphone, a stereoscopic virtual reality headset, and a gaming joystick. Methods: A mixed methods study that included 24 eye care professionals from 4 hospitals in Southwest Ethiopia was conducted to evaluate the acceptability of GES. A pre-post design was used to collect perspectives before and after using the GES by using questionnaires and semistructured interviews. A Wilcoxon signed-rank test was used to determine the significance of any change in the scores of the questionnaire items (two-tailed, 95% CI; ?=.05). The questionnaire and interview questions were guided by the Unified Theory of Acceptance and Use of Technology. Results: Positive results were obtained both before and after use, suggesting the acceptance of mobile health solutions for conducting glaucoma screening by using a low-cost headset with a smartphone and a game controller. There was a significant increase (two-tailed, 95% CI; ?=.05) in the average scores of 86% (19/22) of postuse questionnaire items compared with those of preuse questionnaire items. Ophthalmic professionals perceived GES as easy to use and as a tool that enabled the conduct of glaucoma screening tests, especially during outreach to rural areas. However, positive evaluations are contingent on the accuracy of the tool. Moreover, ophthalmologists voiced the need to limit the tool to screening only (ie, not for making diagnoses). Conclusions: This study supports the feasibility of using a mobile device in combination with a low-cost virtual reality headset and classic controller for glaucoma screening in rural areas. GES has the potential to reduce the burden of irreversible blindness caused by glaucoma. However, further assessment of its sensitivity and specificity is required. UR - https://formative.jmir.org/2021/9/e26602 UR - http://dx.doi.org/10.2196/26602 UR - http://www.ncbi.nlm.nih.gov/pubmed/34533462 ID - info:doi/10.2196/26602 ER - TY - JOUR AU - Han, Yong AU - Li, Weiming AU - Liu, Mengmeng AU - Wu, Zhiyuan AU - Zhang, Feng AU - Liu, Xiangtong AU - Tao, Lixin AU - Li, Xia AU - Guo, Xiuhua PY - 2021/7/13 TI - Application of an Anomaly Detection Model to Screen for Ocular Diseases Using Color Retinal Fundus Images: Design and Evaluation Study JO - J Med Internet Res SP - e27822 VL - 23 IS - 7 KW - anomaly detection KW - artificial intelligence KW - cataract KW - diabetic retinopathy KW - disease screening KW - eye KW - fundus image KW - glaucoma KW - macular degeneration KW - ocular disease KW - ophthalmology N2 - Background: The supervised deep learning approach provides state-of-the-art performance in a variety of fundus image classification tasks, but it is not applicable for screening tasks with numerous or unknown disease types. The unsupervised anomaly detection (AD) approach, which needs only normal samples to develop a model, may be a workable and cost-saving method of screening for ocular diseases. Objective: This study aimed to develop and evaluate an AD model for detecting ocular diseases on the basis of color fundus images. Methods: A generative adversarial network?based AD method for detecting possible ocular diseases was developed and evaluated using 90,499 retinal fundus images derived from 4 large-scale real-world data sets. Four other independent external test sets were used for external testing and further analysis of the model?s performance in detecting 6 common ocular diseases (diabetic retinopathy [DR], glaucoma, cataract, age-related macular degeneration, hypertensive retinopathy [HR], and myopia), DR of different severity levels, and 36 categories of abnormal fundus images. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the model?s performance were calculated and presented. Results: Our model achieved an AUC of 0.896 with 82.69% sensitivity and 82.63% specificity in detecting abnormal fundus images in the internal test set, and it achieved an AUC of 0.900 with 83.25% sensitivity and 85.19% specificity in 1 external proprietary data set. In the detection of 6 common ocular diseases, the AUCs for DR, glaucoma, cataract, AMD, HR, and myopia were 0.891, 0.916, 0.912, 0.867, 0.895, and 0.961, respectively. Moreover, the AD model had an AUC of 0.868 for detecting any DR, 0.908 for detecting referable DR, and 0.926 for detecting vision-threatening DR. Conclusions: The AD approach achieved high sensitivity and specificity in detecting ocular diseases on the basis of fundus images, which implies that this model might be an efficient and economical tool for optimizing current clinical pathways for ophthalmologists. Future studies are required to evaluate the practical applicability of the AD approach in ocular disease screening. UR - https://www.jmir.org/2021/7/e27822 UR - http://dx.doi.org/10.2196/27822 UR - http://www.ncbi.nlm.nih.gov/pubmed/34255681 ID - info:doi/10.2196/27822 ER - TY - JOUR AU - Kang, Yu-Chuan Eugene AU - Yeung, Ling AU - Lee, Yi-Lun AU - Wu, Cheng-Hsiu AU - Peng, Shu-Yen AU - Chen, Yueh-Peng AU - Gao, Quan-Ze AU - Lin, Chihung AU - Kuo, Chang-Fu AU - Lai, Chi-Chun PY - 2021/5/31 TI - A Multimodal Imaging?Based Deep Learning Model for Detecting Treatment-Requiring Retinal Vascular Diseases: Model Development and Validation Study JO - JMIR Med Inform SP - e28868 VL - 9 IS - 5 KW - deep learning KW - retinal vascular diseases KW - multimodal imaging KW - treatment requirement KW - machine learning KW - eye KW - retinal KW - imaging KW - treatment KW - model KW - detection KW - vascular N2 - Background: Retinal vascular diseases, including diabetic macular edema (DME), neovascular age-related macular degeneration (nAMD), myopic choroidal neovascularization (mCNV), and branch and central retinal vein occlusion (BRVO/CRVO), are considered vision-threatening eye diseases. However, accurate diagnosis depends on multimodal imaging and the expertise of retinal ophthalmologists. Objective: The aim of this study was to develop a deep learning model to detect treatment-requiring retinal vascular diseases using multimodal imaging. Methods: This retrospective study enrolled participants with multimodal ophthalmic imaging data from 3 hospitals in Taiwan from 2013 to 2019. Eye-related images were used, including those obtained through retinal fundus photography, optical coherence tomography (OCT), and fluorescein angiography with or without indocyanine green angiography (FA/ICGA). A deep learning model was constructed for detecting DME, nAMD, mCNV, BRVO, and CRVO and identifying treatment-requiring diseases. Model performance was evaluated and is presented as the area under the curve (AUC) for each receiver operating characteristic curve. Results: A total of 2992 eyes of 2185 patients were studied, with 239, 1209, 1008, 211, 189, and 136 eyes in the control, DME, nAMD, mCNV, BRVO, and CRVO groups, respectively. Among them, 1898 eyes required treatment. The eyes were divided into training, validation, and testing groups in a 5:1:1 ratio. In total, 5117 retinal fundus photos, 9316 OCT images, and 20,922 FA/ICGA images were used. The AUCs for detecting mCNV, DME, nAMD, BRVO, and CRVO were 0.996, 0.995, 0.990, 0.959, and 0.988, respectively. The AUC for detecting treatment-requiring diseases was 0.969. From the heat maps, we observed that the model could identify retinal vascular diseases. Conclusions: Our study developed a deep learning model to detect retinal diseases using multimodal ophthalmic imaging. Furthermore, the model demonstrated good performance in detecting treatment-requiring retinal diseases. UR - https://medinform.jmir.org/2021/5/e28868 UR - http://dx.doi.org/10.2196/28868 UR - http://www.ncbi.nlm.nih.gov/pubmed/34057419 ID - info:doi/10.2196/28868 ER - TY - JOUR AU - Nguyen, Xuan-Lan Anne AU - Trinh, Xuan-Vi AU - Wang, Y. Sophia AU - Wu, Y. Albert PY - 2021/5/17 TI - Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions JO - J Med Internet Res SP - e20803 VL - 23 IS - 5 KW - sentiment analysis KW - emotions analysis KW - natural language processing KW - online forums KW - social media KW - patient attitudes KW - medicine KW - infodemiology KW - infoveillance KW - digital health N2 - Background: Clinical data in social media are an underused source of information with great potential to allow for a deeper understanding of patient values, attitudes, and preferences. Objective: This tutorial aims to describe a novel, robust, and modular method for the sentiment analysis and emotion detection of free text from web-based forums and the factors to consider during its application. Methods: We mined the discussion and user information of all posts containing search terms related to a medical subspecialty (oculoplastics) from MedHelp, the largest web-based platform for patient health forums. We used data cleaning and processing tools to define the relevant subset of results and prepare them for sentiment analysis. We executed sentiment and emotion analyses by using IBM Watson Natural Language Understanding to generate sentiment and emotion scores for the posts and their associated keywords. The keywords were aggregated using natural language processing tools. Results: Overall, 39 oculoplastic-related search terms resulted in 46,381 eligible posts within 14,329 threads. Posts were written by 18,319 users (117 doctors; 18,202 patients) and included 201,611 associated keywords. Keywords that occurred ?500 times in the corpus were used to identify the most prominent topics, including specific symptoms, medication, and complications. The sentiment and emotion scores of these keywords and eligible posts were analyzed to provide concrete examples of the potential of this methodology to allow for a better understanding of patients? attitudes. The overall sentiment score reflects a positive, neutral, or negative sentiment, whereas the emotion scores (anger, disgust, fear, joy, and sadness) represent the likelihood of the presence of the emotion. In keyword grouping analyses, medical signs, symptoms, and diseases had the lowest overall sentiment scores (?0.598). Complications were highly associated with sadness (0.485). Forum posts mentioning body parts were related to sadness (0.416) and fear (0.321). Administration was the category with the highest anger score (0.146). The top 6 forum subgroups had an overall negative sentiment score; the most negative one was the Neurology forum, with a score of ?0.438. The Undiagnosed Symptoms forum had the highest sadness score (0.448). The least likely fearful posts were those from the Eye Care forum, with a score of 0.260. The overall sentiment score was much more negative before the doctor replied. The anger, disgust, fear, and sadness emotion scores decreased in likelihood, whereas joy was slightly more likely to be expressed after doctors replied. Conclusions: This report allows physicians and researchers to efficiently mine and perform sentiment analysis on social media to better understand patients? perspectives and promote patient-centric care. Important factors to be considered during its application include evaluating the scope of the search; selecting search terms and understanding their linguistic usages; and establishing selection, filtering, and processing criteria for posts and keywords tailored to the desired results. UR - https://www.jmir.org/2021/5/e20803 UR - http://dx.doi.org/10.2196/20803 UR - http://www.ncbi.nlm.nih.gov/pubmed/33999001 ID - info:doi/10.2196/20803 ER - TY - JOUR AU - Hwang, Youjin AU - Shin, Donghoon AU - Eun, Jinsu AU - Suh, Bongwon AU - Lee, Joonhwan PY - 2021/3/29 TI - Design Guidelines of a Computer-Based Intervention for Computer Vision Syndrome: Focus Group Study and Real-World Deployment JO - J Med Internet Res SP - e22099 VL - 23 IS - 3 KW - computer-based intervention KW - computer vision syndrome KW - system interface KW - deployment study N2 - Background: Prolonged time of computer use increases the prevalence of ocular problems, including eye strain, tired eyes, irritation, redness, blurred vision, and double vision, which are collectively referred to as computer vision syndrome (CVS). Approximately 70% of computer users have vision-related problems. For these reasons, properly designed interventions for users with CVS are required. To design an effective screen intervention for preventing or improving CVS, we must understand the effective interfaces of computer-based interventions. Objective: In this study, we aimed to explore the interface elements of computer-based interventions for CVS to set design guidelines based on the pros and cons of each interface element. Methods: We conducted an iterative user study to achieve our research objective. First, we conducted a workshop to evaluate the overall interface elements that were included in previous systems for CVS (n=7). Through the workshop, participants evaluated existing interface elements. Based on the evaluation results, we eliminated the elements that negatively affect intervention outcomes. Second, we designed our prototype system LiquidEye that includes multiple interface options (n=11). Interface options included interface elements that were positively evaluated in the workshop study. Lastly, we deployed LiquidEye in the real world to see how the included elements affected the intervention outcomes. Participants used LiquidEye for 14 days, and during this period, we collected participants? daily logs (n=680). Additionally, we conducted prestudy and poststudy surveys, and poststudy interviews to explore how each interface element affects participation in the system. Results: User data logs collected from the 14 days of deployment were analyzed with multiple regression analysis to explore the interface elements affecting user participation in the intervention (LiquidEye). Statistically significant elements were the instruction page of the eye resting strategy (P=.01), goal setting of the resting period (P=.009), compliment feedback after completing resting (P<.001), a mid-size popup window (P=.02), and CVS symptom-like effects (P=.004). Conclusions: Based on the study results, we suggested design implications to consider when designing computer-based interventions for CVS. The sophisticated design of the customization interface can make it possible for users to use the system more interactively, which can result in higher engagement in managing eye conditions. There are important technical challenges that still need to be addressed, but given the fact that this study was able to clarify the various factors related to computer-based interventions, the findings are expected to contribute greatly to the research of various computer-based intervention designs in the future. UR - https://www.jmir.org/2021/3/e22099 UR - http://dx.doi.org/10.2196/22099 UR - http://www.ncbi.nlm.nih.gov/pubmed/33779568 ID - info:doi/10.2196/22099 ER - TY - JOUR AU - Begum, Tahmina AU - Rahman, Aminur AU - Nomani, Dilruba AU - Mamun, Abdullah AU - Adams, Alayne AU - Islam, Shafiqul AU - Khair, Zara AU - Khair, Zareen AU - Anwar, Iqbal PY - 2021/3/9 TI - Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study JO - JMIR Public Health Surveill SP - e23538 VL - 7 IS - 3 KW - diabetic retinopathy KW - diagnostic accuracy KW - digital fundus photograph KW - Bangladesh KW - diabetes KW - retinopathy KW - retina KW - opthalmology N2 - Background: Diabetic retinopathy can cause blindness even in the absence of symptoms. Although routine eye screening remains the mainstay of diabetic retinopathy treatment and it can prevent 95% of blindness, this screening is not available in many low- and middle-income countries even though these countries contribute to 75% of the global diabetic retinopathy burden. Objective: The aim of this study was to assess the diagnostic accuracy of diabetic retinopathy screening done by non-ophthalmologists using 2 different digital fundus cameras and to assess the risk factors for the occurrence of diabetic retinopathy. Methods: This validation study was conducted in 6 peripheral health facilities in Bangladesh from July 2017 to June 2018. A double-blinded diagnostic approach was used to test the accuracy of the diabetic retinopathy screening done by non-ophthalmologists against the gold standard diagnosis by ophthalmology-trained eye consultants. Retinal images were taken by using either a desk-based camera or a hand-held camera following pupil dilatation. Test accuracy was assessed using measures of sensitivity, specificity, and positive and negative predictive values. Overall agreement with the gold standard test was reported using the Cohen kappa statistic (?) and area under the receiver operating curve (AUROC). Risk factors for diabetic retinopathy occurrence were assessed using binary logistic regression. Results: In 1455 patients with diabetes, the overall sensitivity to detect any form of diabetic retinopathy by non-ophthalmologists was 86.6% (483/558, 95% CI 83.5%-89.3%) and the specificity was 78.6% (705/897, 95% CI 75.8%-81.2%). The accuracy of the correct classification was excellent with a desk-based camera (AUROC 0.901, 95% CI 0.88-0.92) and fair with a hand-held camera (AUROC 0.710, 95% CI 0.67-0.74). Out of the 3 non-ophthalmologist categories, registered nurses and paramedics had strong agreement with kappa values of 0.70 and 0.85 in the diabetic retinopathy assessment, respectively, whereas the nonclinical trained staff had weak agreement (?=0.35). The odds of having retinopathy increased with the duration of diabetes measured in 5-year intervals (P<.001); the odds of having retinopathy in patients with diabetes for 5-10 years (odds ratio [OR] 1.81, 95% CI 1.37-2.41) and more than 10 years (OR 3.88, 95% CI 2.91-5.15) were greater than that in patients with diabetes for less than 5 years. Obesity was found to have a negative association (P=.04) with diabetic retinopathy. Conclusions: Digital fundus photography is an effective screening tool with acceptable diagnostic accuracy. Our findings suggest that diabetic retinopathy screening can be accurately performed by health care personnel other than eye consultants. People with more than 5 years of diabetes should receive priority in any community-level retinopathy screening program. In a country like Bangladesh where no diabetic retinopathy screening services exist, the use of hand-held cameras can be considered as a cost-effective option for potential system-wide implementation. UR - https://publichealth.jmir.org/2021/3/e23538 UR - http://dx.doi.org/10.2196/23538 UR - http://www.ncbi.nlm.nih.gov/pubmed/33411671 ID - info:doi/10.2196/23538 ER - TY - JOUR AU - Wang, Jian AU - Li, Mei AU - Zhu, Daqiao AU - Cao, Yang PY - 2020/12/8 TI - Smartphone Overuse and Visual Impairment in Children and Young Adults: Systematic Review and Meta-Analysis JO - J Med Internet Res SP - e21923 VL - 22 IS - 12 KW - visual impairment KW - smartphone KW - mobile phone KW - overuse KW - child KW - young adult KW - systematic review KW - meta-analysis N2 - Background: Smartphone overuse has been cited as a potentially modifiable risk factor that can result in visual impairment. However, reported associations between smartphone overuse and visual impairment have been inconsistent. Objective: The aim of this systematic review was to determine the association between smartphone overuse and visual impairment, including myopia, blurred vision, and poor vision, in children and young adults. Methods: We conducted a systematic search in the Cochrane Library, PubMed, EMBASE, Web of Science Core Collection, and ScienceDirect databases since the beginning of the databases up to June 2020. Fourteen eligible studies (10 cross-sectional studies and 4 controlled trials) were identified, which included a total of 27,110 subjects with a mean age ranging from 9.5 to 26.0 years. We used a random-effects model for meta-analysis of the 10 cross-sectional studies (26,962 subjects) and a fixed-effects model for meta-analysis of the 4 controlled trials (148 subjects) to combine odds ratios (ORs) and effect sizes (ES). The I2 statistic was used to assess heterogeneity. Results: A pooled OR of 1.05 (95% CI 0.98-1.13, P=.16) was obtained from the cross-sectional studies, suggesting that smartphone overuse is not significantly associated with myopia, poor vision, or blurred vision; however, these visual impairments together were more apparent in children (OR 1.06, 95% CI 0.99-1.14, P=.09) than in young adults (OR 0.91, 95% CI 0.57-1.46,P=.71). For the 4 controlled trials, the smartphone overuse groups showed worse visual function scores compared with the reduced-use groups. The pooled ES was 0.76 (95% CI 0.53-0.99), which was statistically significant (P<.001). Conclusions: Longer smartphone use may increase the likelihood of ocular symptoms, including myopia, asthenopia, and ocular surface disease, especially in children. Thus, regulating use time and restricting the prolonged use of smartphones may prevent ocular and visual symptoms. Further research on the patterns of use, with longer follow up on the longitudinal associations, will help to inform detailed guidelines and recommendations for smartphone use in children and young adults. UR - https://www.jmir.org/2020/12/e21923 UR - http://dx.doi.org/10.2196/21923 UR - http://www.ncbi.nlm.nih.gov/pubmed/33289673 ID - info:doi/10.2196/21923 ER - TY - JOUR AU - Dunne, Stephen AU - Close, Helen AU - Richards, Nicola AU - Ellison, Amanda AU - Lane, R. Alison PY - 2020/10/23 TI - Maximizing Telerehabilitation for Patients With Visual Loss After Stroke: Interview and Focus Group Study With Stroke Survivors, Carers, and Occupational Therapists JO - J Med Internet Res SP - e19604 VL - 22 IS - 10 KW - telerehabilitation KW - vision KW - barriers KW - facilitators KW - technology N2 - Background: Visual field defects are a common consequence of stroke, and compensatory eye movement strategies have been identified as the most promising rehabilitation option. There has been a move toward compensatory telerehabilitation options, such as the Durham Reading and Exploration (DREX) training app, which significantly improves visual exploration, reading, and self-reported quality of life. Objective: This study details an iterative process of liaising with stroke survivors, carers, and health care professionals to identify barriers and facilitators to using rehabilitation tools, as well as elements of good practice in telerehabilitation, with a focus on how the DREX package can be maximized. Methods: Survey data from 75 stroke survivors informed 12 semistructured engagement activities (7 focus groups and 5 interviews) with 32 stroke survivors, 10 carers, and 24 occupational therapists. Results: Thematic analysis identified key themes within the data. Themes identified problems associated with poststroke health care from both patients? and occupational therapists? perspectives that need to be addressed to improve uptake of this rehabilitation tool and telerehabilitation options generally. This included identifying additional materials or assistance that were required to boost the impact of training packages. The acute rehabilitation setting was an identified barrier, and perceptions of technology were considered a barrier by some but a facilitator by others. In addition, 4 key features of telerehabilitation were identified: additional materials, the importance of goal setting, repetition, and feedback. Conclusions: The data were used to try to overcome some barriers to the DREX training and are further discussed as considerations for telerehabilitation in general moving forward. UR - http://www.jmir.org/2020/10/e19604/ UR - http://dx.doi.org/10.2196/19604 UR - http://www.ncbi.nlm.nih.gov/pubmed/33095179 ID - info:doi/10.2196/19604 ER - TY - JOUR AU - Wolffsohn, S. James AU - Leteneux-Pantais, Claudia AU - Chiva-Razavi, Sima AU - Bentley, Sarah AU - Johnson, Chloe AU - Findley, Amy AU - Tolley, Chloe AU - Arbuckle, Rob AU - Kommineni, Jyothi AU - Tyagi, Nishith PY - 2020/9/21 TI - Social Media Listening to Understand the Lived Experience of Presbyopia: Systematic Search and Content Analysis Study JO - J Med Internet Res SP - e18306 VL - 22 IS - 9 KW - presbyopia KW - near vision KW - social media KW - social media listening KW - infodemiology N2 - Background: Presbyopia is defined as the age-related deterioration of near vision over time which is experienced in over 80% of people aged 40 years or older. Individuals with presbyopia have difficulty with tasks that rely on near vision. It is not currently possible to stop or reverse the aging process that causes presbyopia; generally, it is corrected with glasses, contact lenses, surgery, or the use of a magnifying glass. Objective: This study aimed to explore how individuals used social media to describe their experience of presbyopia with regard to the symptoms experienced and the impacts of presbyopia on their quality of life. Methods: Social media sources including Twitter, forums, blogs, and news outlets were searched using a predefined search string relating to symptoms and impacts of presbyopia. The data that were downloaded, based on the keywords, underwent manual review to identify relevant data points. Relevant posts were further manually analyzed through a process of data tagging, categorization, and clustering. Key themes relating to symptoms, impacts, treatment, and lived experiences were identified. Results: A total of 4456 social media posts related to presbyopia were identified between May 2017 and August 2017. Using a random sampling methodology, we selected 2229 (50.0%) posts for manual review, with 1470 (65.9%) of these 2229 posts identified as relevant to the study objectives. Twitter was the most commonly used channel for discussions on presbyopia compared to forums and blogs. The majority of relevant posts originated in Spain (559/1470, 38.0%) and the United States (426/1470, 29.0%). Of the relevant posts, 270/1470 (18.4%) were categorized as posts written by individuals who have presbyopia, of which 37 of the 270 posts (13.7%) discussed symptoms. On social media, individuals with presbyopia most frequently reported experiencing difficulty reading small print (24/37, 64.9%), difficulty focusing on near objects (15/37, 40.5%), eye strain (12/37, 32.4%), headaches (9/37, 24.3%), and blurred vision (8/37, 21.6%). 81 of the 270 posts (30.0%) discussed impacts of presbyopia?emotional burden (57/81, 70.4%), functional or daily living impacts (46/81, 56.8%), such as difficulty reading (46/81, 56.8%) and using electronic devices (21/81, 25.9%), and impacts on work (3/81, 3.7%). Conclusions: Findings from this social media listening study provided insight into how people with presbyopia discuss their condition online and highlight the impact of presbyopia on individuals? quality of life. The social media listening methodology can be used to generate insights into the lived experience of a condition, but it is recommended that this research be combined with prospective qualitative research for added rigor and for confirmation of the relevance of the findings. UR - http://www.jmir.org/2020/9/e18306/ UR - http://dx.doi.org/10.2196/18306 UR - http://www.ncbi.nlm.nih.gov/pubmed/32955443 ID - info:doi/10.2196/18306 ER - TY - JOUR AU - Baxter, L. Sally AU - Klie, R. Adam AU - Radha Saseendrakumar, Bharanidharan AU - Ye, Y. Gordon AU - Hogarth, Michael PY - 2020/8/14 TI - Text Processing for Detection of Fungal Ocular Involvement in Critical Care Patients: Cross-Sectional Study JO - J Med Internet Res SP - e18855 VL - 22 IS - 8 KW - fungemia KW - fungal endophthalmitis KW - fungal ocular involvement KW - electronic health records KW - diagnosis codes KW - regular expressions KW - natural language processing KW - unstructured data N2 - Background: Fungal ocular involvement can develop in patients with fungal bloodstream infections and can be vision-threatening. Ocular involvement has become less common in the current era of improved antifungal therapies. Retrospectively determining the prevalence of fungal ocular involvement is important for informing clinical guidelines, such as the need for routine ophthalmologic consultations. However, manual retrospective record review to detect cases is time-consuming. Objective: This study aimed to determine the prevalence of fungal ocular involvement in a critical care database using both structured and unstructured electronic health record (EHR) data. Methods: We queried microbiology data from 46,467 critical care patients over 12 years (2000-2012) from the Medical Information Mart for Intensive Care III (MIMIC-III) to identify 265 patients with culture-proven fungemia. For each fungemic patient, demographic data, fungal species present in blood culture, and risk factors for fungemia (eg, presence of indwelling catheters, recent major surgery, diabetes, immunosuppressed status) were ascertained. All structured diagnosis codes and free-text narrative notes associated with each patient?s hospitalization were also extracted. Screening for fungal endophthalmitis was performed using two approaches: (1) by querying a wide array of eye- and vision-related diagnosis codes, and (2) by utilizing a custom regular expression pipeline to identify and collate relevant text matches pertaining to fungal ocular involvement. Both approaches were validated using manual record review. The main outcome measure was the documentation of any fungal ocular involvement. Results: In total, 265 patients had culture-proven fungemia, with Candida albicans (n=114, 43%) and Candida glabrata (n=74, 28%) being the most common fungal species in blood culture. The in-hospital mortality rate was 121 (46%). In total, 7 patients were identified as having eye- or vision-related diagnosis codes, none of whom had fungal endophthalmitis based on record review. There were 26,830 free-text narrative notes associated with these 265 patients. A regular expression pipeline based on relevant terms yielded possible matches in 683 notes from 108 patients. Subsequent manual record review again demonstrated that no patients had fungal ocular involvement. Therefore, the prevalence of fungal ocular involvement in this cohort was 0%. Conclusions: MIMIC-III contained no cases of ocular involvement among fungemic patients, consistent with prior studies reporting low rates of ocular involvement in fungemia. This study demonstrates an application of natural language processing to expedite the review of narrative notes. This approach is highly relevant for ophthalmology, where diagnoses are often based on physical examination findings that are documented within clinical notes. UR - https://www.jmir.org/2020/8/e18855 UR - http://dx.doi.org/10.2196/18855 UR - http://www.ncbi.nlm.nih.gov/pubmed/32795984 ID - info:doi/10.2196/18855 ER - TY - JOUR AU - Piano, Marianne AU - Nilforooshan, Ramin AU - Evans, Simon PY - 2020/8/10 TI - Binocular Vision, Visual Function, and Pupil Dynamics in People Living With Dementia and Their Relation to the Rate of Cognitive Decline and Structural Changes Within the Brain: Protocol for an Observational Study JO - JMIR Res Protoc SP - e16089 VL - 9 IS - 8 KW - binocular vision KW - dementia KW - magnetic resonance imaging KW - stereopsis KW - pupil KW - sleep N2 - Background: Visual impairment is a common comorbidity in people living with dementia. Addressing sources of visual difficulties can have a significant impact on the quality of life for people living with dementia and their caregivers. Depth perception problems are purportedly common in dementia and also contribute to falls, visuomotor task difficulties, and poorer psychosocial well-being. However, depth perception and binocular vision are rarely assessed in dementia research. Sleep fragmentation is also common for people living with dementia, and binocular cooperation for depth perception can be affected by fatigue. Pupillary responses under cognitive load also have the potential to be a risk marker for cognitive decline in people living with dementia and can be combined with the above measures for a comprehensive evaluation of clinical visual changes in people living with dementia and their relation to changes in cognitive status, sleep quality, and cortical structure or function. Objective: This study aims to characterize the nature of clinical visual changes and altered task-evoked pupillary responses that may occur in people living with dementia and evaluate whether these responses relate to changes in cognitive status (standardized Mini Mental State Examination [MMSE] score), Pittsburgh sleep quality index, and cortical structure or function. Methods: This proposed exploratory observational study will enroll ?210 people with recently diagnosed dementia (within the last 24 months). The following parameters will be assessed on 3 occasions, 4 months apart (plus or minus 2 weeks): visual function (visual acuity and contrast sensitivity), binocular function (motor fusion and stereopsis), task-evoked pupillary responses (minimum and maximum pupil size, time to maximum dilation, and dilation velocity), cognitive status (MMSE score), and sleep quality (Pittsburgh Sleep Quality Index). A subset of patients (n=30) with Alzheimer disease will undergo structural and functional magnetic resonance imaging at first and third visits, completing a 10-day consensus sleep diary to monitor sleep quality, verified by sleep actimetry. Results: This research was funded in February 2018 and received National Health Service Research Ethics Committee approval in September 2018. The data collection period was from October 1, 2018, to November 30, 2019. A total of 24 participants were recruited for the study. The data analysis is complete, with results expected to be published before the end of 2020. Conclusions: Findings will demonstrate how often people with dementia experience binocular vision problems. If frequent, diagnosing and treating them could improve quality of life by reducing the risk of falls and fine visuomotor task impairment and by relieving psychosocial anxiety. This research will also demonstrate whether changes in depth perception, pupillary responses, and quality of vision relate to changes in memory or sleep quality and brain structure or function. If related, these quick and noninvasive eye tests help monitor dementia. This would help justify whether binocular vision and pupillary response testing should be included in dementia-friendly eye-testing guidelines. International Registered Report Identifier (IRRID): RR1-10.2196/16089 UR - https://www.researchprotocols.org/2020/8/e16089 UR - http://dx.doi.org/10.2196/16089 UR - http://www.ncbi.nlm.nih.gov/pubmed/32773379 ID - info:doi/10.2196/16089 ER - TY - JOUR AU - Wintergerst, M. Maximilian W. AU - Jansen, G. Linus AU - Holz, G. Frank AU - Finger, P. Robert PY - 2020/7/29 TI - A Novel Device for Smartphone-Based Fundus Imaging and Documentation in Clinical Practice: Comparative Image Analysis Study JO - JMIR Mhealth Uhealth SP - e17480 VL - 8 IS - 7 KW - smartphone-based fundus imaging KW - smartphone-based funduscopy KW - smartphone KW - retinal imaging KW - mHealth KW - mobile phone KW - smartphone imaging KW - smartphone funduscopy KW - smartphone ophthalmoscope N2 - Background: Smartphone-based fundus imaging allows for mobile and inexpensive fundus examination with the potential to revolutionize eye care, particularly in lower-resource settings. However, most smartphone-based fundus imaging adapters convey image quality not comparable to conventional fundus imaging. Objective: The purpose of this study was to evaluate a novel smartphone-based fundus imaging device for documentation of a variety of retinal/vitreous pathologies in a patient sample with wide refraction and age ranges. Methods: Participants? eyes were dilated and imaged with the iC2 funduscope (HEINE Optotechnik) using an Apple iPhone 6 in single-image acquisition (image resolution of 2448 × 3264 pixels) or video mode (1248 × 1664 pixels) and a subgroup of participants was also examined by conventional fundus imaging (Zeiss VISUCAM 500). Smartphone-based image quality was compared to conventional fundus imaging in terms of sharpness (focus), reflex artifacts, contrast, and illumination on semiquantitative scales. Results: A total of 47 eyes from 32 participants (age: mean 62.3, SD 19.8 years; range 7-93; spherical equivalent: mean ?0.78, SD 3.21 D; range: ?7.88 to +7.0 D) were included in the study. Mean (SD) visual acuity (logMAR) was 0.48 (0.66; range 0-2.3); 30% (14/47) of the eyes were pseudophakic. Image quality was sufficient in all eyes irrespective of refraction. Images acquired with conventional fundus imaging were sharper and had less reflex artifacts, and there was no significant difference in contrast and illumination (P<.001, P=.03, and P=.10, respectively). When comparing image quality at the posterior pole, the mid periphery, and the far periphery, glare increased as images were acquired from a more peripheral part of the retina. Reflex artifacts were more frequent in pseudophakic eyes. Image acquisition was also possible in children. Documentation of deep optic nerve cups in video mode conveyed a mock 3D impression. Conclusions: Image quality of conventional fundus imaging was superior to that of smartphone-based fundus imaging, although this novel smartphone-based fundus imaging device achieved image quality high enough to document various fundus pathologies including only subtle findings. High-quality smartphone-based fundus imaging might represent a mobile alternative for fundus documentation in clinical practice. UR - https://mhealth.jmir.org/2020/7/e17480 UR - http://dx.doi.org/10.2196/17480 UR - http://www.ncbi.nlm.nih.gov/pubmed/32723717 ID - info:doi/10.2196/17480 ER - TY - JOUR AU - Ma, Shuoxin AU - Guan, Yongqing AU - Yuan, Yazhen AU - Tai, Yuan AU - Wang, Tan PY - 2020/7/13 TI - A One-Step, Streamlined Children?s Vision Screening Solution Based on Smartphone Imaging for Resource-Limited Areas: Design and Preliminary Field Evaluation JO - JMIR Mhealth Uhealth SP - e18226 VL - 8 IS - 7 KW - vision screening KW - resource-limited application KW - photorefraction KW - strabismus KW - myopia KW - anisometropia KW - mHealth KW - screening N2 - Background: Young children?s vision screening, as part of a preventative health care service, produces great value for developing regions. Besides yielding a high return on investment from forestalling surgeries using a low-cost intervention at a young age, it improves school performance and thus boosts future labor force quality. Leveraging low-skilled health care workers with smartphones and automated diagnosis to offer such programs can be a scalable model in resource-limited areas. Objective: This study aimed to develop and evaluate an effective, efficient, and comprehensive vision screening solution for school children in resource-limited areas. First, such an exam would need to cover the major risk factors of amblyopia and myopia, 2 major sources of vision impairment effectively preventable at a young age. Second, the solution must be integrated with digital patient record-keeping for long-term monitoring and popular statistical analysis. Last, it should utilize low-skilled technicians and only low-cost tools that are available in a typical school in developing regions, without compromising quality or efficiency. Methods: A workflow for the screening program was designed and a smartphone app was developed to implement it. In the standardized screening procedure, a young child went through the smartphone-based photoscreening in a dark room. The child held a smartphone in front of their forehead, displaying pre-entered personal information as a quick response code that duplexed as a reference of scale. In one 10-second procedure, the child?s personal information and interpupillary distance, relative visual axis alignment, and refractive error ranges were measured and analyzed automatically using image processing and artificial intelligence algorithms. The child?s risk for strabismus, myopia, and anisometropia was then derived and consultation given. Results: A preliminary evaluation of the solution was conducted alongside yearly physical exams in Luoyang, Henan, People?s Republic of China. It covered 20 students with suspected strabismus and 80 randomly selected students, aged evenly between 8 and 10. Each examinee took about 1 minute, and a streamlined workflow allowed 3 exams to run in parallel. The 1-shot and 2-shot measurement success rates were 87% and 100%, respectively. The sensitivity and specificity of strabismus detection were 0.80 and 0.98, respectively. The sensitivity and specificity of myopia detection were 0.83 and 1.00, respectively. The sensitivity and specificity of anisometropia detection were 0.80 and 1.00, respectively. Conclusions: The proposed vision screening program is effective, efficient, and scalable. Compared with previously published studies on utilizing a smartphone for an automated Hirschberg test and photorefraction screening, this comprehensive solution is optimized for practicality and robustness, and is thus better ready-to-deploy. Our evaluation validated the achievement of the program?s design specifications. UR - http://mhealth.jmir.org/2020/7/e18226/ UR - http://dx.doi.org/10.2196/18226 UR - http://www.ncbi.nlm.nih.gov/pubmed/32673243 ID - info:doi/10.2196/18226 ER - TY - JOUR AU - Inomata, Takenori AU - Nakamura, Masahiro AU - Iwagami, Masao AU - Midorikawa-Inomata, Akie AU - Sung, Jaemyoung AU - Fujimoto, Keiichi AU - Okumura, Yuichi AU - Eguchi, Atsuko AU - Iwata, Nanami AU - Miura, Maria AU - Fujio, Kenta AU - Nagino, Ken AU - Hori, Satoshi AU - Tsubota, Kazuo AU - Dana, Reza AU - Murakami, Akira PY - 2020/6/26 TI - Stratification of Individual Symptoms of Contact Lens?Associated Dry Eye Using the iPhone App DryEyeRhythm: Crowdsourced Cross-Sectional Study JO - J Med Internet Res SP - e18996 VL - 22 IS - 6 KW - contact lens-associated dry eye KW - mobile health KW - ResearchKit KW - smartphone app KW - DryEyeRhythm KW - subjective symptoms KW - risk factors KW - dry eye KW - stratification KW - mobile phone N2 - Background: Discontinuation of contact lens use is mainly caused by contact lens?associated dry eye. It is crucial to delineate contact lens?associated dry eye's multifaceted nature to tailor treatment to each patient?s individual needs for future personalized medicine. Objective: This paper aims to quantify and stratify individual subjective symptoms of contact lens?associated dry eye and clarify its risk factors for future personalized medicine using the smartphone app DryEyeRhythm (Juntendo University). Methods: This cross-sectional study included iPhone (Apple Inc) users in Japan who downloaded DryEyeRhythm. DryEyeRhythm was used to collect medical big data related to contact lens?associated dry eye between November 2016 and January 2018. The main outcome measure was the incidence of contact lens?associated dry eye. Univariate and multivariate adjusted odds ratios of risk factors for contact lens?associated dry eye were determined by logistic regression analyses. The t-distributed Stochastic Neighbor Embedding algorithm was used to depict the stratification of subjective symptoms of contact lens?associated dry eye. Results: The records of 4454 individuals (median age 27.9 years, SD 12.6), including 2972 female participants (66.73%), who completed all surveys were included in this study. Among the included participants, 1844 (41.40%) were using contact lenses, and among those who used contact lenses, 1447 (78.47%) had contact lens?associated dry eye. Multivariate adjusted odds ratios of risk factors for contact lens?associated dry eye were as follows: younger age, 0.98 (95% CI 0.96-0.99); female sex, 1.53 (95% CI 1.05-2.24); hay fever, 1.38 (95% CI 1.10-1.74); mental illness other than depression or schizophrenia, 2.51 (95% CI 1.13-5.57); past diagnosis of dry eye, 2.21 (95% CI 1.63-2.99); extended screen exposure time >8 hours, 1.61 (95% CI 1.13-2.28); and smoking, 2.07 (95% CI 1.49-2.88). The t-distributed Stochastic Neighbor Embedding analysis visualized and stratified 14 groups based on the subjective symptoms of contact lens?associated dry eye. Conclusions: This study identified and stratified individuals with contact lens?associated dry eye and its risk factors. Data on subjective symptoms of contact lens?associated dry eye could be used for prospective prevention of contact lens?associated dry eye progression. UR - http://www.jmir.org/2020/6/e18996/ UR - http://dx.doi.org/10.2196/18996 UR - http://www.ncbi.nlm.nih.gov/pubmed/32589162 ID - info:doi/10.2196/18996 ER - TY - JOUR AU - Rono, Hillary AU - Bastawrous, Andrew AU - Macleod, David AU - Bunywera, Cosmas AU - Mamboleo, Ronald AU - Wanjala, Emmanuel AU - Burton, Matthew PY - 2020/6/19 TI - Smartphone-Guided Algorithms for Use by Community Volunteers to Screen and Refer People With Eye Problems in Trans Nzoia County, Kenya: Development and Validation Study JO - JMIR Mhealth Uhealth SP - e16345 VL - 8 IS - 6 KW - visual impairment KW - algorithms KW - mobile phone KW - screening KW - mHealth KW - sensitivity KW - specificity N2 - Background: The provision of eye care services is currently insufficient to meet the requirements of eye care. Many people remain unnecessarily visually impaired or at risk of becoming so because of treatable or preventable eye conditions. A lack of access and awareness of services is, in large part, a key barrier to handle this unmet need. Objective: This study aimed to assess whether utilizing novel smartphone-based clinical algorithms can task-shift eye screening to community volunteers (CVs) to accurately identify and refer patients to primary eye care services. In particular, we developed the Peek Community Screening app and assessed its validity in making referral decisions for patients with eye problems. Methods: We developed a smartphone-based clinical algorithm (the Peek Community Screening app) using age, distance vision, near vision, and pain as referral criteria. We then compared CVs? referral decisions using this app with those made by an experienced ophthalmic clinical officer (OCO), which was the reference standard. The same participants were assessed by a trained CV using the app and by an OCO using standard outreach equipment. The outcome was the proportion of all decisions that were correct when compared with that of the OCO. Results: The required sensitivity and specificity for the Peek Community Screening app were achieved after seven iterations. In the seventh iteration, the OCO identified referable eye problems in 65.9% (378/574) of the participants. CVs correctly identified 344 of 378 (sensitivity 91.0%; 95% CI 87.7%-93.7%) of the cases and correctly identified 153 of 196 (specificity 78.1%; 95% CI 71.6%-83.6%) cases as not having a referable eye problem. The positive predictive value was 88.9% (95% CI 85.3%-91.8%), and the negative predictive value was 81.8% (95% CI 75.5%-87.1%). Conclusions: Development of such an algorithm is feasible; however, it requires considerable effort and resources. CVs can accurately use the Peek Community Screening app to identify and refer people with eye problems. An iterative design process is necessary to ensure validity in the local context. UR - https://mhealth.jmir.org/2020/6/e16345 UR - http://dx.doi.org/10.2196/16345 UR - http://www.ncbi.nlm.nih.gov/pubmed/32558656 ID - info:doi/10.2196/16345 ER - TY - JOUR AU - Choi, G. Namkee AU - DiNitto, M. Diana AU - Lee, EunKyoung Othelia AU - Choi, Y. Bryan PY - 2020/6/3 TI - Internet and Health Information Technology Use and Psychological Distress Among Older Adults With Self-Reported Vision Impairment: Case-Control Study JO - J Med Internet Res SP - e17294 VL - 22 IS - 6 KW - older adults KW - vision impairment KW - HIT KW - psychological distress KW - digital divide KW - mobile phone N2 - Background: The number of older adults with vision impairment (VI) is growing. As health care services increasingly call for patients to use technology, it is important to examine internet/health information technology (HIT) use among older adults with VI. Objective: This study aimed to examine (1) the rates of internet/HIT use among older adults with VI compared with a matched sample of their peers without VI, (2) associations of VI with internet/HIT use, and (3) association of HIT use with psychological distress, assessed with the Kessler-6 screen. Methods: Data were obtained from the 2013 to 2018 US National Health Interview Survey. Older adults (aged ?65 years) with self-reported VI were matched with older adults without VI, in a 1:1 ratio, based on age, sex, number of chronic medical conditions, and functional limitations (N=2866). Descriptive statistics and multivariable logistic regression models, with sociodemographic factors, health conditions, health insurance type, and health care service use as covariates, were used to examine the research questions. Results: In total, 3.28% of older adults (compared with 0.84% of those aged 18-64 years) reported VI, and 25.7% of them were aged ?85 years. Those with VI were significantly more socioeconomically disadvantaged than those without VI and less likely to use the internet (adjusted odds ratio [aOR] 0.64, 95% CI0.49-0.83) and HIT (aOR 0.74, 95% CI 0.56-0.97). However, among internet users, VI was not associated with HIT use. HIT use was associated with lower odds of mild/moderate or serious psychological distress (aOR 0.62, 95% CI 0.43-0.90), whereas VI was associated with greater odds of mild/moderate or serious distress (aOR 1.84, 95% CI 1.36-2.49). Health care provider contacts were also associated with higher odds of internet or HIT use. Conclusions: Compared with their matched age peers without VI, older adults with VI are less likely to use HIT because they are less likely to use the internet. Socioeconomically disadvantaged older adults experiencing a digital divide need help to access information and communication technologies through a fee waiver or subsidy to cover internet equipment and subscription and ensure continuous connectivity. Older adults with VI who do not know how to use the internet/HIT but want to learn should be provided instruction, with special attention to accessibility features and adaptive devices. Older adults with a low income also need better access to preventive eye care and treatment of VI as well as other health care services. UR - https://www.jmir.org/2020/6/e17294 UR - http://dx.doi.org/10.2196/17294 UR - http://www.ncbi.nlm.nih.gov/pubmed/32490851 ID - info:doi/10.2196/17294 ER - TY - JOUR AU - Tan, Han Choon AU - Kyaw, Myint Bhone AU - Smith, Helen AU - Tan, S. Colin AU - Tudor Car, Lorainne PY - 2020/5/15 TI - Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies JO - J Med Internet Res SP - e16658 VL - 22 IS - 5 KW - diabetic retinopathy KW - smartphone KW - mobile phone KW - ophthalmoscopy KW - artificial intelligence KW - telemedicine N2 - Background: Diabetic retinopathy (DR), a common complication of diabetes mellitus, is the leading cause of impaired vision in adults worldwide. Smartphone ophthalmoscopy involves using a smartphone camera for digital retinal imaging. Utilizing smartphones to detect DR is potentially more affordable, accessible, and easier to use than conventional methods. Objective: This study aimed to determine the diagnostic accuracy of various smartphone ophthalmoscopy approaches for detecting DR in diabetic patients. Methods: We performed an electronic search on the Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, and Cochrane Library for literature published from January 2000 to November 2018. We included studies involving diabetic patients, which compared the diagnostic accuracy of smartphone ophthalmoscopy for detecting DR to an accurate or commonly employed reference standard, such as indirect ophthalmoscopy, slit-lamp biomicroscopy, and tabletop fundus photography. Two reviewers independently screened studies against the inclusion criteria, extracted data, and assessed the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies?2 tool, with disagreements resolved via consensus. Sensitivity and specificity were pooled using the random effects model. A summary receiver operating characteristic (SROC) curve was constructed. This review is reported in line with the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies guidelines. Results: In all, nine studies involving 1430 participants were included. Most studies were of high quality, except one study with limited applicability because of its reference standard. The pooled sensitivity and specificity for detecting any DR was 87% (95% CI 74%-94%) and 94% (95% CI 81%-98%); mild nonproliferative DR (NPDR) was 39% (95% CI 10%-79%) and 95% (95% CI 91%-98%); moderate NPDR was 71% (95% CI 57%-81%) and 95% (95% CI 88%-98%); severe NPDR was 80% (95% CI 49%-94%) and 97% (95% CI 88%-99%); proliferative DR (PDR) was 92% (95% CI 79%-97%) and 99% (95% CI 96%-99%); diabetic macular edema was 79% (95% CI 63%-89%) and 93% (95% CI 82%-97%); and referral-warranted DR was 91% (95% CI 86%-94%) and 89% (95% CI 56%-98%). The area under SROC curve ranged from 0.879 to 0.979. The diagnostic odds ratio ranged from 11.3 to 1225. Conclusions: We found heterogeneous evidence showing that smartphone ophthalmoscopy performs well in detecting DR. The diagnostic accuracy for PDR was highest. Future studies should standardize reference criteria and classification criteria and evaluate other available forms of smartphone ophthalmoscopy in primary care settings. UR - http://www.jmir.org/2020/5/e16658/ UR - http://dx.doi.org/10.2196/16658 UR - http://www.ncbi.nlm.nih.gov/pubmed/32347810 ID - info:doi/10.2196/16658 ER - TY - JOUR AU - Chun, Jaehyeong AU - Kim, Youngjun AU - Shin, Yoon Kyoung AU - Han, Hyup Sun AU - Oh, Yeul Sei AU - Chung, Tae-Young AU - Park, Kyung-Ah AU - Lim, Hui Dong PY - 2020/5/5 TI - Deep Learning?Based Prediction of Refractive Error Using Photorefraction Images Captured by a Smartphone: Model Development and Validation Study JO - JMIR Med Inform SP - e16225 VL - 8 IS - 5 KW - amblyopia KW - cycloplegic refraction KW - deep learning KW - deep convolutional neural network KW - mobile phone KW - photorefraction KW - refractive error KW - screening N2 - Background: Accurately predicting refractive error in children is crucial for detecting amblyopia, which can lead to permanent visual impairment, but is potentially curable if detected early. Various tools have been adopted to more easily screen a large number of patients for amblyopia risk. Objective: For efficient screening, easy access to screening tools and an accurate prediction algorithm are the most important factors. In this study, we developed an automated deep learning?based system to predict the range of refractive error in children (mean age 4.32 years, SD 1.87 years) using 305 eccentric photorefraction images captured with a smartphone. Methods: Photorefraction images were divided into seven classes according to their spherical values as measured by cycloplegic refraction. Results: The trained deep learning model had an overall accuracy of 81.6%, with the following accuracies for each refractive error class: 80.0% for ??5.0 diopters (D), 77.8% for >?5.0 D and ??3.0 D, 82.0% for >?3.0 D and ??0.5 D, 83.3% for >?0.5 D and <+0.5 D, 82.8% for ?+0.5 D and <+3.0 D, 79.3% for ?+3.0 D and <+5.0 D, and 75.0% for ?+5.0 D. These results indicate that our deep learning?based system performed sufficiently accurately. Conclusions: This study demonstrated the potential of precise smartphone-based prediction systems for refractive error using deep learning and further yielded a robust collection of pediatric photorefraction images. UR - https://medinform.jmir.org/2020/5/e16225 UR - http://dx.doi.org/10.2196/16225 UR - http://www.ncbi.nlm.nih.gov/pubmed/32369035 ID - info:doi/10.2196/16225 ER - TY - JOUR AU - Boucher, Carole Marie AU - Nguyen, Duc Michael Trong AU - Qian, Jenny PY - 2020/4/7 TI - Assessment of Training Outcomes of Nurse Readers for Diabetic Retinopathy Telescreening: Validation Study JO - JMIR Diabetes SP - e17309 VL - 5 IS - 2 KW - training KW - teleophthalmology KW - telemedicine KW - diabetic retinopathy KW - screening KW - referral KW - nurse N2 - Background: With the high prevalence of diabetic retinopathy and its significant visual consequences if untreated, timely identification and management of diabetic retinopathy is essential. Teleophthalmology programs have assisted in screening a large number of individuals at risk for vision loss from diabetic retinopathy. Training nonophthalmological readers to assess remote fundus images for diabetic retinopathy may further improve the efficiency of such programs. Objective: This study aimed to evaluate the performance, safety implications, and progress of 2 ophthalmology nurses trained to read and assess diabetic retinopathy fundus images within a hospital diabetic retinopathy telescreening program. Methods: In this retrospective interobserver study, 2 ophthalmology nurses followed a specific training program within a hospital diabetic retinopathy telescreening program and were trained to assess diabetic retinopathy images at 2 levels of intervention: detection of diabetic retinopathy (level 1) and identification of referable disease (level 2). The reliability of the assessment by level 1?trained readers in 266 patients and of the identification of patients at risk of vision loss from diabetic retinopathy by level 2?trained readers in 559 more patients were measured. The learning curve, sensitivity, and specificity of the readings were evaluated using a group consensus gold standard. Results: An almost perfect agreement was measured in identifying the presence of diabetic retinopathy in both level 1 readers (?=0.86 and 0.80) and in identifying referable diabetic retinopathy by level 2 readers (?=0.80 and 0.83). At least substantial agreement was measured in the level 2 readers for macular edema (?=0.79 and 0.88) for all eyes. Good screening threshold sensitivities and specificities were obtained for all level readers, with sensitivities of 90.6% and 96.9% and specificities of 95.1% and 85.1% for level 1 readers (readers A and B) and with sensitivities of 86.8% and 91.2% and specificities of 91.7% and 97.0% for level 2 readers (readers A and B). This performance was achieved immediately after training and remained stable throughout the study. Conclusions: Notwithstanding the small number of trained readers, this study validates the screening performance of level 1 and level 2 diabetic retinopathy readers within this training program, emphasizing practical experience, and allows the establishment of an ongoing assessment clinic. This highlights the importance of supervised, hands-on experience and may help set parameters to further calibrate the training of diabetic retinopathy readers for safe screening programs. UR - https://diabetes.jmir.org/2020/2/e17309 UR - http://dx.doi.org/10.2196/17309 UR - http://www.ncbi.nlm.nih.gov/pubmed/32255431 ID - info:doi/10.2196/17309 ER - TY - JOUR AU - Nam, Min Sang AU - Peterson, A. Thomas AU - Butte, J. Atul AU - Seo, Yul Kyoung AU - Han, Wook Hyun PY - 2020/2/20 TI - Explanatory Model of Dry Eye Disease Using Health and Nutrition Examinations: Machine Learning and Network-Based Factor Analysis From a National Survey JO - JMIR Med Inform SP - e16153 VL - 8 IS - 2 KW - dry eye disease KW - epidemiology KW - machine learning KW - systems analysis KW - patient-specific modeling N2 - Background: Dry eye disease (DED) is a complex disease of the ocular surface, and its associated factors are important for understanding and effectively treating DED. Objective: This study aimed to provide an integrative and personalized model of DED by making an explanatory model of DED using as many factors as possible from the Korea National Health and Nutrition Examination Survey (KNHANES) data. Methods: Using KNHANES data for 2012 (4391 sample cases), a point-based scoring system was created for ranking factors associated with DED and assessing patient-specific DED risk. First, decision trees and lasso were used to classify continuous factors and to select important factors, respectively. Next, a survey-weighted multiple logistic regression was trained using these factors, and points were assigned using the regression coefficients. Finally, network graphs of partial correlations between factors were utilized to study the interrelatedness of DED-associated factors. Results: The point-based model achieved an area under the curve of 0.70 (95% CI 0.61-0.78), and 13 of 78 factors considered were chosen. Important factors included sex (+9 points for women), corneal refractive surgery (+9 points), current depression (+7 points), cataract surgery (+7 points), stress (+6 points), age (54-66 years; +4 points), rhinitis (+4 points), lipid-lowering medication (+4 points), and intake of omega-3 (0.43%-0.65% kcal/day; ?4 points). Among these, the age group 54 to 66 years had high centrality in the network, whereas omega-3 had low centrality. Conclusions: Integrative understanding of DED was possible using the machine learning?based model and network-based factor analysis. This method for finding important risk factors and identifying patient-specific risk could be applied to other multifactorial diseases. UR - http://medinform.jmir.org/2020/2/e16153/ UR - http://dx.doi.org/10.2196/16153 UR - http://www.ncbi.nlm.nih.gov/pubmed/32130150 ID - info:doi/10.2196/16153 ER - TY - JOUR AU - Mleeh, Talal Nouf AU - Alzahrani, Abdulwahed Nujood AU - Hariri, Osama Jehad AU - Mortada, Hisham Hatan AU - Algethami, Ridha Mohammed PY - 2019/12/19 TI - Dermatologists? Adherence to the Latest Recommendations for Screening of Hydroxychloroquine Retinopathy in Saudi Arabia: Cross-Sectional Study JO - Interact J Med Res SP - e15218 VL - 8 IS - 4 KW - Saudi Arabia KW - dermatologist KW - adherence KW - hydroxychloroquine KW - retinopathy N2 - Background: Hydroxychloroquine (HCQ) has been used to manage many inflammatory skin conditions. Nevertheless, retinopathy continues to be its most significant adverse effect. The American Academy of Ophthalmology (AAO) recommends baseline ophthalmologic screening in the first year of HCQ treatment. However, a recent study found an inadequate awareness of the recommendations. Furthermore, limited data are available regarding the implementation of the recommendations among dermatologists. Objective: The aim of this study was to assess dermatologists? adherence to recommendations pertaining to their current practice regarding HCQ toxicity detection. Methods: A self-administrated questionnaire was distributed between February 2 and May 4, 2018, among members of the Saudi Society of Dermatology. The questionnaire comprised demographic-related questions and questions pertaining to each physician?s routine practice about the follow-up of HCQ-treated patients. Results: A total of 76 dermatologists completed the questionnaire. We achieved a response rate of 62.54%. More than half (43/76, 56%) of the dermatologists were male. Furthermore, more than half (41/76, 53%) of them reported treating 1 to 3 patients with HCQ during the last year. Furthermore, two-thirds (47/76, 61%) of them reported screening patients before initiating HCQ treatment. Regarding follow-up recommendations, 59% (45/76) of dermatologists reported yearly after starting treatment for no-risk patients, whereas 94% (72/76) reported ?yearly within 5 years of treatment? for at-risk patients. Data were considered significant at P<.05. All analyses were performed using SPSS, version 20 (IBM). Conclusions: Dermatologists in Saudi Arabia are not well informed about some aspects of the latest recommendations regarding screening for HCQ toxicity in terms of tests, follow-up timing, cessation of the drug, and causative agents. Therefore, we recommend conducting more studies in Saudi Arabia to determine the adherence of more physicians to the AAO recommendations. Furthermore, patient education regarding HCQ toxicity and increased patient awareness are recommended for effective and safe HCQ use. UR - http://www.i-jmr.org/2019/4/e15218/ UR - http://dx.doi.org/10.2196/15218 UR - http://www.ncbi.nlm.nih.gov/pubmed/31855186 ID - info:doi/10.2196/15218 ER -