Smartwatch Algorithm for Automated Detection of Atrial Fibrillation

Joseph M Bumgarner, Cameron T Lambert, Ayman A Hussein, Daniel J Cantillon, Bryan Baranowski, Kathy Wolski, Bruce D Lindsay, Oussama M Wazni, Khaldoun G Tarakji

The Kardia Band (KB) is a novel technology that enables patients to record a rhythm strip using an Apple smartwatch. The band is paired with an app providing automated detection of atrial fibrillation (AF). To examine whether the KB could accurately differentiate sinus rhythm (SR) from AF compared to physician-interpreted 12-lead ECGs and KB recordings. Consecutive patients with AF presenting for cardioversion (CV) were enrolled. Patients underwent pre-CV ECG along with a KB recording. If CV performed, a post-CV ECG was obtained along with a KB recording. The KB interpretations were compared to physician-reviewed ECGs. The KB recordings were reviewed by blinded electrophysiologists and compared to ECG interpretations. Sensitivity, specificity and K coefficient were measured. One hundred patients were enrolled (Age 68 ± 11 years). Eight patients did not undergo CV. There were 169 simultaneous ECG and KB recordings. Fifty-seven were non-interpretable by the KB. Compared to ECG, the KB interpreted AF with 93% sensitivity, 84% specificity and K coefficient 0.77. Physician-interpretation of KB recordings demonstrated 99% sensitivity, 83% specificity and K coefficient 0.83. Of 57 non-interpretable KB recordings, interpreting electrophysiologists diagnosed AF with 100% sensitivity, 80% specificity and K coefficient 0.74. Among 113 cases where KB and physician readings of the same recording were interpretable, agreement was excellent (K coefficient 0.88). The KB algorithm for AF detection, supported by physician review can accurately differentiate AF from SR. This technology can help screen patients prior to elective CV and avoid unnecessary procedures.