J Emerg Med
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The COVID-19 pandemic presents a significant challenge to the global health care system. Implementing timely, accurate, and cost-effective screening approaches is crucial in preventing infections and saving lives by guiding disease management. ⋯ This study developed and validated three machine learning prediction models for COVID-19 mortality based on accessible clinical features. The RF model showed the best performance among the three models. The nine variables identified in the models may warrant further investigation as potential prognostic indicators of severe COVID-19.
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Randomized Controlled Trial
Pediatric Chest Compression Improvement Via Augmented Reality Cardiopulmonary Resuscitation Feedback in Community General Emergency Departments: A Mixed-Methods Simulation-Based Pilot Study.
Yearly, more than 20,000 children experience a cardiac arrest. High-quality pediatric cardiopulmonary resuscitation (CPR) is generally challenging for community hospital teams, where pediatric cardiac arrest is infrequent. Current feedback systems are insufficient. Therefore, we developed an augmented reality (AR) CPR feedback system for use in many settings. ⋯ The novel CPR feedback system, AR-CPR, significantly changed the CC performance in community hospital non-pediatric-specialized general EDs from 18-21% to 87-90% of CC epochs at goal. This study offers preliminary evidence suggesting AR-CPR improves CC quality in community hospital settings.