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JACC Clin Electrophysiol. 2019 Feb;5(2):199-208. doi: 10.1016/j.jacep.2018.10.006. Epub 2018 Nov 28.

The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation.

Author information

1
Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany. Electronic address: mdoerr@uni-greifswald.de.
2
Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany.
3
Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
4
Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany.
5
Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland; Department of Internal Medicine, University Hospital Basel, Basel, Switzerland.

Abstract

OBJECTIVES:

The WATCH AF (SmartWATCHes for Detection of Atrial Fibrillation) trial compared the diagnostic accuracy to detect atrial fibrillation (AF) by a smartwatch-based algorithm using photoplethysmographic (PPG) signals with cardiologists' diagnosis by electrocardiography (ECG).

BACKGROUND:

Timely detection of AF is crucial for stroke prevention.

METHODS:

In this prospective, 2-center, case-control trial, a PPG pulse wave recording using a commercially available smartwatch was obtained along with Internet-enabled mobile ECG in 672 hospitalized subjects. PPG recordings were analyzed by a novel automated algorithm. Cardiologists' diagnoses were available for 650 subjects, although 142 (21.8%) datasets were not suitable for PPG analysis, among them 101 (15.1%) that were also not interpretable by the automated Internet-enabled mobile ECG algorithm, resulting in a sample size of 508 subjects (mean age 76.4 years, 225 women, 237 with AF) for the main analyses.

RESULTS:

For the PPG algorithm, we found a sensitivity of 93.7% (95% confidence interval [CI]: 89.8% to 96.4%), a specificity of 98.2% (95% CI: 95.8% to 99.4%), and 96.1% accuracy (95% CI: 94.0% to 97.5%) to detect AF.

CONCLUSIONS:

The results of the WATCH AF trial suggest that detection of AF using a commercially available smartwatch is in principle feasible, with very high diagnostic accuracy. Applicability of the tested algorithm is currently limited by a high dropout rate as a result of insufficient signal quality. Thus, achieving sufficient signal quality remains challenging, but real-time signal quality checks are expected to improve signal quality. Whether smartwatches may be useful complementary tools for convenient long-term AF screening in selected at-risk patients must be evaluated in larger population-based samples. (SmartWATCHes for Detection of Atrial Fibrillation [WATCH AF]:; NCT02956343).

KEYWORDS:

atrial fibrillation; iECG screening; mobile ECG; photoplethysmography; screening; smartwatch

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