Use of handheld electrocardiograph (SnapECG) for the remote monitoring of arrhythmias

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Abstract

Objective: To investigate the value of a SnapECG monitoring in diagnosing arrhythmias compared with the conventional management. Methods: In the first phase, the SnapECG and 12-lead electrocardiogram (ECG) were simultaneously adopted to detect arrhythmias in 439 hospitalized patients. The accuracies of the SnapECG in detecting different arrhythmias were assessed. In the second phase, 62 patients with palpitations were randomized to receive the SnapECG monitoring or conventional management for 3 months. The diagnosis rate, time of diagnosis, episodes before diagnosis, associated expenses, and scores of the modified European Heart Rhythm Association (EHRA), Self-rating Anxiety Scale (SAS), and the 36-item short-form health survey questionnaire (SF-36) were compared between groups. Results: In the first phase, the SnapECG monitoring showed a sensitivity of 83.55% and specificity of 96.79% in identifying tachyarrhythmias, and a sensitivity of 95.29% and specificity of 97.54% in identifying bradyarrhythmias. In the second phase, 1642 ECGs were recorded by the SnapECG, among which 290 abnormal ECGs were identified. Compared with the conventional management, the SnapECG monitoring increased the diagnosis rate of symptomatic arrhythmias (70.97% vs. 19.35%, P < 0.05), shortened the time of diagnosis (48.26 ± 36.78 days vs. 71.45 ± 30.01 days, P < 0.05) and consequently reduced the episodes of symptomatic arrhythmias prior to establishing diagnosis. The scores of modified EHRA, SAS, SF-36 significantly improved at 3-month compared with their baseline levels in the SnapECG group. Conclusions: Remote monitoring with the SnapECG can achieve early diagnosis of symptomatic arrhythmias. However, its sensitivity in identifying P-wave-related arrhythmias warrants further improvement.

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APA

Gu, Q., Chen, Z., Ma, J., Zhou, Y., Li, J., Ying, L., … Li, C. (2022). Use of handheld electrocardiograph (SnapECG) for the remote monitoring of arrhythmias. Digital Health, 8. https://doi.org/10.1177/20552076221113393

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