Journal article
The WATCH AF Trial: SmartWATCHes for Detection of Atrial Fibrillation.
- Dörr M 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.
- Nohturfft V Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany.
- Brasier N Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Bosshard E Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Djurdjevic A Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Gross S Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany.
- Raichle CJ Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Rhinisperger M Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Stöckli R Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland.
- Eckstein J Chief Medical Information Officer (CMIO) Office, University Hospital Basel, Basel, Switzerland; Department of Internal Medicine, University Hospital Basel, Basel, Switzerland.
- 2019-02-21
Published in:
- JACC. Clinical electrophysiology. - 2019
atrial fibrillation
iECG screening
mobile ECG
photoplethysmography
screening
smartwatch
Aged
Aged, 80 and over
Algorithms
Atrial Fibrillation
Case-Control Studies
Electrocardiography
Female
Humans
Male
Photoplethysmography
Prospective Studies
Pulse Wave Analysis
Reproducibility of Results
Sensitivity and Specificity
Wearable Electronic Devices
English
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).
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).
- Language
-
- English
- Open access status
- bronze
- Identifiers
-
- DOI 10.1016/j.jacep.2018.10.006
- PMID 30784691
- Persistent URL
- https://folia.unifr.ch/global/documents/150159
Statistics
Document views: 36
File downloads: