Automated Detection of Low Ejection Fraction from a One-lead Electrocardiogram: Application of an AI algorithm to an ECG-enabled Digital Stethoscope

ECG-enabled stethoscopes (ECG-Scope) acquire single lead ECGs during cardiac auscultation, and may facilitate real-time screening for pathologies not routinely identified by cardiac auscultation alone. Since we previously demonstrated an artificial intelligence (AI) algorithm can identify left ventricular dysfunction(LVSD) (defined as ejection fraction (EF) ≤ 40%) with an AUC of 0.91 using a 12 lead ECG, we conducted a prospective study to determine the efficacy of applying AI to an ECG-enabled Digital Stethoscope. We found that an AI algorithm applied to an ECG-enabled Digital Dtethoscope reliably detected the presence of a low EF in patients (AUC 0.91 when using the model to select recording automatically). The ability to screen patients with a possible low EF during routine physical examinations may facilitate rapid detection of LVSD.