Comparison of 2 Smart Watch Algorithms for Detection of Atrial Fibrillation and the Benefit of Clinician Interpretation

BACKGROUND Smart watches and wearable technology capable of heart rhythm assessment have increased in use in the general population. The Apple Watch Series 4 (AW4) and KardiaBand (KB) are devices capable of obtaining single -lead electrocardiographic recordings, presenting a novel opportunity for the detection of paroxysmal arrhythmias.OBJECTIVES The aim of this study was to assess the diagnostic utility of the AW4 and KB in an elderly outpatient population. METHODS Consecutive recordings were taken from patients attending cardiology outpatient clinic from the AW4 and KB concurrently with 12-lead electrocardiography. Automated diagnoses and blinded single-lead electrocardiographic tracing interpretations by 2 cardiologists were analyzed. Analysis was also conducted to assess the effect of combined device and clinician interpretation.RESULTS One hundred twenty-five patients were prospectively recruited (mean age 76 +/- 7 years, 62% men). The accuracy of the automated rhythm assessment was higher with the KB than the AW4 (74% vs 65%). For the detection of atrial fibrillation, the sensitivity and negative predictive value of the KB were 89% and 97%, respectively, and of the AW4 were 19% and 82%, respectively. Using hybrid automated and clinician interpretation, the overall accuracy of the KB and AW4 was 91% and 87%, respectively. CONCLUSIONS The KB automated algorithm outperformed the AW4 in its accuracy and sensitivity for detecting atrial fibrillation in the outpatient setting. Clinician assessment of the single-lead electrocardiogram improved accuracy. These findings suggest that although these devices' tracings are of sufficient quality, automated diagnosis alone is not sufficient for making clinical decisions about atrial fibrillation diagnosis and management. (J Am Coll Cardiol EP 2022;8:782-791) (c) 2022 by the American College of Cardiology Foundation.