Using a Smartwatch Electrocardiogram to Detect Abnormalities Associated With Sudden Cardiac Arrest in Young Adults

Mathieu Nasarre; Marc Strik; Francisco Daniel Ramirez; Samuel Buliard; Hugo Marchand; Saer Abu-Alrub; Sylvain Ploux; Michel Haïssaguerre; Pierre Bordachar

Disclosures

Europace. 2022;24(3):406-412. 

In This Article

Abstract and Introduction

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.

Introduction

Sudden cardiac arrest (SCA) and its most common consequence, sudden cardiac death (SCD), remain major public health problems, accounting for approximately 50% of all cardiovascular deaths.[1] Preventing SCD is challenging in part because in more than 25% of victims, it represents a first symptomatic cardiac event.[1] Compounding this is the estimated 10% survival rate for out-of-hospital cardiac arrest.[1] Whereas coronary artery disease is the predominant cause of SCD in elderly individuals, more varied diagnoses account for SCD in young adults, including cardiomyopathies, channelopathies, and accessory pathways.[2,3] The surface 12-lead ECG can readily enable the detection of prolonged QT intervals, Brugada patterns, and ventricular pre-excitation, and may trigger further investigations to assess for hypertrophic cardiomyopathy (HCM) and arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC/D).[4–10] However, in general, 12-lead ECGs are not widely performed in young asymptomatic adults. The widespread and growing use of contemporary smartwatches may provide alternative diagnostic opportunities by permitting consumers to self-register ECGs and to digitally send them to healthcare providers.[11] Rapid access to ECG recordings, without a physician's order, could facilitate screening efforts and could empower individuals to play a more active role in their health care. Indeed, this technology has shown considerable promise for atrial fibrillation screening.[12] However, a major technical limitation of smartwatch ECGs is that they are typically worn on the left wrist—a position in which only lead I is recorded. To better detect ECG abnormalities associated with SCA, additional recordings recreating precordial leads may be required.[13]

We sought to evaluate the agreement of smartwatch-derived single-lead ECG recordings with 12-lead ECGs for diagnosing various electrocardiographic abnormalities associated with SCA in young adults. In addition to examining recordings taken from the left wrist, smartwatch ECGs were recorded from different precordial sites to more comprehensively evaluate the diagnostic potential of this technology.

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