Clinical Validation of 5 Direct-to-Consumer Wearable Smart Devices to Detect Atrial Fibrillation: BASEL Wearable Study
- PMID: 36858690
- DOI: 10.1016/j.jacep.2022.09.011
Clinical Validation of 5 Direct-to-Consumer Wearable Smart Devices to Detect Atrial Fibrillation: BASEL Wearable Study
Abstract
Background: Multiple smart devices capable to detect atrial fibrillation (AF) are presently available. Sensitivity and specificity for the detection of AF may differ between available smart devices, and this has not yet been adequately investigated.
Objectives: The aim was to assess the accuracy of 5 smart devices in identifying AF compared with a physician-interpreted 12-lead electrocardiogram as the reference standard in a real-world cohort of patients.
Methods: We consecutively enrolled patients presenting to a cardiology service at a tertiary referral center in a prospective, diagnostic study.
Results: We prospectively analyzed 201 patients (31% women, median age 66.7 years). AF was present in 62 (31%) patients. Sensitivity and specificity for the detection of AF were comparable between devices: 85% and 75% for the Apple Watch 6, 85% and 75% for the Samsung Galaxy Watch 3, 58% and 75% for the Withings Scanwatch, 66% and 79% for the Fitbit Sense, and 79% and 69% for the AliveCor KardiaMobile, respectively. The rate of inconclusive tracings (the algorithm was unable to determine the heart rhythm) was 18%, 17%, 24%, 21%, and 26% for the Apple Watch 6, Samsung Galaxy Watch 3, Withings Scan Watch, Fitbit Sense, and AliveCor KardiaMobile (P < 0.01 for pairwise comparison), respectively. By manual review of inconclusive tracings, the rhythm could be determined in 955 (99%) of 969 single-lead electrocardiograms. Regarding patient acceptance, the Apple Watch was ranked first (39% of participants).
Conclusions: In this clinical validation of 5 direct-to-consumer smart devices, we found differences in the amount of inconclusive tracings diminishing sensitivity and specificity of the smart devices. In a clinical setting, manual review of tracings is required in about one-fourth of cases.
Keywords: atrial fibrillation; digital health; intelligent ECG; smartwatch.
Copyright © 2023. Published by Elsevier Inc.
Conflict of interest statement
Funding Support and Author Disclosures Dr Knecht has received funding from the Stiftung für kardiovaskuläre Forschung. Dr Schaer has served on the Speakers Bureau for Medtronic. Dr Mueller has received research support from the Swiss National Science Foundation, the Swiss Heart Foundation, the KTI, the University Hospital Basel, the University of Basel, Abbott, Beckman Coulter, Brahms, Idorsia, Novartis, Ortho Diagnostics, Quidel, Roche, Siemens, Singulex, and Sphingotec, outside the submitted work; and speaker/consulting honoraria from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, BMS, Novartis, Osler, Roche, and Sanofi, all paid to the institution. Dr Kühne has received personal fees from Bayer, Boehringer Ingelheim, Pfizer BMS, Daiichi Sankyo, Medtronic, Biotronik, Boston Scientific, Johnson & Johnson, Roche; and grants from Bayer, Pfizer, Boston Scientific, BMS, Biotronik, and Daiichi Sankyo, all outside the submitted work. Dr Sticherling has served on the advisory board for Medtronic Europe and Boston Scientitic Europe; received educational grants from Biosense Webster and Biotronik; received a research grant from the European Union’s FP7 program and Biosense Webster; and received lecture and consulting fees from Abbott, Medtronic, Biosense Webster, Boston Scientific, MicroPort, and Biotronik, all outside the submitted work. Dr Badertscher has received research funding from the University of Basel, the Stiftung für Herzschrittmacher und Elektrophysiologie, the Freiwillige Akademische Gesellschaft Basel, and Johnson & Johnson, all outside the submitted work; and received personal fees from Abbott. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Comment in
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Smart Devices in Detecting AF: Excellent Signal Quality, But AI Can Still Learn From Clinicians.JACC Clin Electrophysiol. 2023 Feb;9(2):243-245. doi: 10.1016/j.jacep.2022.10.036. JACC Clin Electrophysiol. 2023. PMID: 36858691 No abstract available.
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