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Mobile Phone Detection of Atrial Fibrillation
Study Questions:
Can mobile phones accurately detect atrial fibrillation (AF) episodes?
Methods:
This was a case-control study of consecutive patients with AF matched by age and sex to patients with sinus rhythm (SR) who were enrolled from the cardiology and internal medicine wards of Turku University Hospital, Finland, between April and September 2017. A 3-minute mechanocardiography (MCG) recording was acquired from each subject with a Sony Xperia smartphone placed on their sternum, while a simultaneously obtained five-lead telemetry electrocardiography (ECG) recording was used as the comparison method to assess rhythm and the number of supraventricular and ventricular extra-systole. ECG rhythm classifications were confirmed by two independent cardiologists, and a third cardiologist made the final decision if interpretations diverged. The MCG recordings were analyzed utilizing an algorithm developed beforehand by investigators blinded to the underlying rhythm.
Results:
A total of 150 consecutive patients in AF were matched by age and sex to 150 patients in SR. The mean age of the subjects was 74.8 years, and 132 (44.0%) were female. The MCG algorithm correctly classified AF in 143/150 cases and SR in 144/150 controls. Four of the six cases in SR misclassified as AF had marked sinus arrhythmia. The resulting sensitivity was 95.3% (95% confidence interval [CI], 90.6-98.1) and specificity was 96.0% (95% CI, 91.5-98.5). The respective positive and negative predictive values were 96.0% (95% CI, 91.6-98.1) and 95.4% (95% CI, 90.9-97.7), while the positive and the negative likelihood ratios were 23.8 (95% CI, 10.9-55.8) and 0.05 (95% CI, 0.02-0.10), respectively. Reducing the duration of analyzed section of recording to 60 seconds did not affect sensitivity or specificity. Body mass index, respiratory rate, heart rate, or supraventricular extrasystole count were not associated with false-positive rhythm classification. Compared to subjects with a true negative result, those with a false-positive result had a higher median ventricular extrasystole count, a history of heart failure, and were more likely to have pulmonary edema by chest X-ray.
Conclusions:
The authors concluded that smartphone MCG reliably detects AF without any additional hardware and provides a new easy-to-use and accessible concept for AF screening.
Perspective:
Use of smartphones for rhythm analysis will allow us to improve our understanding of AF burden and related management decisions. These data suggest that smartphone-derived recording can be performed accurately.
Keywords: ACC18, ACC Annual Scientific Session, Arrhythmias, Cardiac, Arrhythmia, Sinus, Atrial Fibrillation, Body Mass Index, Cell Phone, Electrocardiography, Geriatrics, Heart Failure, Heart Rate, Pulmonary Edema, Respiratory Rate, Secondary Prevention, Systole, Telemetry
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