Using a smartwatch electrocardiogram to detect abnormalities associated with sudden cardiac arrest in young adults. Issue 3 (1st September 2021)

• Record Type: Journal Article
• Authors: Nasarre, Mathieu; Strik, Marc; Daniel Ramirez, , Francisco; Buliard, Samuel; Marchand, Hugo; Abu-Alrub, Saer; Ploux, Sylvain; Haïssaguerre, Michel; Bordachar, Pierre
• Is Part Of: Europace. Volume 24:Issue 3(2022)
• Page Start: 406
• Page End: 412
• Publication Date: 2021-09-01
• Subjects: Electrocardiography -- Brugada -- Long QT -- Smartwatch -- Sudden cardiac arrest -- Sudden cardiac death -- Pre-excitation -- Arrhythmogenic right ventricular cardiomyopathy -- Hypertrophic cardiomyopathy -- Young adults; Arrhythmia -- Treatment -- Periodicals; Cardiac pacing -- Periodicals; Catheter ablation -- Periodicals; Heart -- Physiology -- Periodicals; Electrophysiology -- Periodicals; 617.4120645
• DOI: 10.1093/europace/euab192
• Languages: English
• ISSNs: 1099-5129

Abstract

Abstract: Aims : Smartwatch electrocardiograms (ECGs) could facilitate the detection of sudden cardiac arrest (SCA)-associated abnormalities. We evaluated the feasibility of using smartwatch-derived ECGs for detecting SCA-associated abnormalities in young adults and its agreement with 12-lead ECGs. Methods and results : Twelve-lead and Apple Watch ECGs were registered in 155 healthy volunteers and 67 patients aged 18–45 years with diagnosis and ECG signs of long-QT syndrome ( n = 10), Brugada syndrome ( n = 12), ventricular pre-excitation ( n = 19), hypertrophic cardiomyopathy (HCM, n = 13), and arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC/D, n = 13). Cardiologists separately analysed 12-lead ECGs and the smartwatch ECGs taken from the left wrist (AW-I) and then from chest positions V1, V3, and V6 (AW-4). Compared with AW-I, AW-4 improved the classification of ECGs as 'abnormal', increasing the sensitivity from 64% to 89% ( P < 0.01). Pre-excitation was detected in most cases using AW-I (sensitivity 89%) and in all cases using AW-4 (sensitivity 100%, P = 0.48 compared with AW-I, specificity 100% for both). Brugada was missed using AW-I but was detected in 11/12 patients using AW-4 (sensitivity 92%, specificity 100%, P = 0.003). Long QT was detected in 8/10 cases using AW-I (sensitivity 80%, specificity 100%) and in 9 patients using AW-4 (sensitivity 90%, specificity 100%, P > 0.99). Hypertrophic cardiomyopathy was correctly suspected using AW-I and AW-4 (sensitivity 92% and 85%, specificity 85%, and 100%, P > 0.99). AW-I was mostly (62%) considered normal in ARVC/D whereas AW-4 was useful in suspecting ARVC/D (100% sensitivity, 99% specificity, P = 0.004). Conclusions : Detection of SCA-associated ECG abnormalities (pre-excitation, Brugada patterns, long QT, and signs suggestive of HCM and ARVC/D) is possible with an ECG smartwatch.