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Smartwatch Algorithm for Automated Detection of Atrial Fibrillation
Joseph M Bumgarner1, Cameron T Lambert1, Ayman A Hussein1
1Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio.
Journal of the American College of Cardiology
|March 15, 2018
Summary
The Kardia Band (KB) accurately detects atrial fibrillation (AF) from sinus rhythm (SR) when supported by physician review. This wearable technology shows promise for screening patients before cardioversion, potentially avoiding unnecessary procedures.
Area of Science:
- Cardiology
- Medical Devices
- Digital Health
Background:
- The Kardia Band (KB) is a novel wearable device paired with an app for recording rhythm strips using an Apple Watch.
- It offers automated detection of atrial fibrillation (AF).
Purpose of the Study:
- To evaluate the accuracy of the KB in differentiating between sinus rhythm (SR) and AF.
- Comparison was made against physician-interpreted 12-lead electrocardiograms (ECGs) and KB recordings.
Main Methods:
- Consecutive patients with AF undergoing cardioversion (CV) were enrolled.
- Simultaneous ECG and KB recordings were obtained pre- and post-CV.
- KB interpretations were compared to physician-reviewed ECGs and blinded electrophysiologist reviews.
Main Results:
- The KB algorithm demonstrated 93% sensitivity and 84% specificity for AF detection compared to ECG.
- Physician interpretation of KB recordings showed 99% sensitivity and 83% specificity.
- Excellent agreement (K coefficient = 0.88) was observed between KB and physician readings for interpretable recordings.
Conclusions:
- The KB, with physician support, accurately distinguishes AF from SR.
- This technology can aid in pre-cardioversion screening, potentially preventing unneeded procedures.
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