Interactive Journal of Medical Research

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ChatGPT’s Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study

The individual step accuracy per simulation attempt for the cardiac arrest and bradycardia algorithms are reported in Tables 1 and 2, respectively. Chat GPT’s median accuracy for each step was 85% (IQR 40%-100%) for cardiac arrest and 30% (IQR 13%-81%) for bradycardia. The accuracy scores per simulation attempt for each algorithm are described in Table 3. Chat GPT’s median accuracy for over 20 simulation attempts for cardiac arrest was 69% (IQR 67%-74%) and for bradycardia was 42% (IQR 33%-50%).

Cecilia Pham, Romi Govender, Salik Tehami, Summer Chavez, Omolola E Adepoju, Winston Liaw

J Med Internet Res 2024;26:e55037

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A Strategy to Reduce Critical Cardiorespiratory Alarms due to Intermittent Enteral Feeding of Preterm Neonates in Intensive Care

We used a data-driven approach to explore the relationship between feeding and cardiorespiratory alarms and to investigate which of the two methods of enteral feeding, push or gravity, is better tolerated by infants as measured by the prevalence of critical desaturation (Sp O2 ≤80%) and bradycardia (heart rate ≤80 bpm) alarms measured during and immediately after feeding.

Rohan Joshi, Carola van Pul, Anouk Sanders, Hans Weda, Jan Willem Bikker, Loe Feijs, Peter Andriessen

Interact J Med Res 2017;6(2):e20

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