High-Throughput Detection of Risk Factors to Sudden Cardiac Arrest in Youth Athletes: A Smartwatch-Based Screening Platform

Xiang, Evan, Wang, Thomas, Poddar, Vivan

arXiv.org Artificial Intelligence 

The National Institute of Health defines Sudden Cardiac Arrest (SCA) as a moment when the heart is not beating sufficiently to maintain perfusion due to the heart's electrical or mechanical failure [1]. SCA is the leading cause of death among youth athletes -- a focus group that has a heightened risk of SCA -- with 1 in 16,000 young athletes and 1 in 5200 athletes at the elite level afflicted yearly [1, 2]. For youth athletes, the primary cause of SCA is hypertrophic cardiomyopathy (HCM) in the U.S. and arrhythmogenic right ventricular cardiomyopathy (ARVC) in Europe. SCA may also result from coronary artery disease, Long QT Syndrome, Myocarditis, Wolff-Parkinson-White syndrome, and dilated cardiomyopathy [1-4]. Figure 1 provides a comprehensive list of significant predictors of SCA [5]. While these disorders do not always lead to instances of SCA, they present a substantial increase in the chance of SCA events, which is further amplified by the innate risk of sports participation [6-9]. Concerningly, the current 14-point questionnaire pre-participation evaluation (PPE) recommended by the American Heart Association (AHA) is ineffective at detecting risk factors with poor sensitivity and specificity of 18.8% and 68.0%

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