Clinical validation of automated QTc measurements from single lead ECG using a novel smartwatch

• Published in: Europace (London, England) Vol. 24; no. Supplement_1
• Main Authors: Mannhart, D, Hennings, EH, Lischer, ML, Vernier, CV, Du Fay De Lavallaz, JDF, Knecht, SK, Schaer, BS, Osswald, SO, Kuehne, MK, Sticherling, CS, Badertscher, PB
• Format: Journal Article
• Language: English
• Published: Oxford University Press 19.05.2022
• ISSN: 1099-5129; 1532-2092
• DOI: 10.1093/europace/euac053.573

Abstract Funding Acknowledgements Type of funding sources: None. Introduction A possible side-effect of various medical drugs is prolongation of the electric repolarization of the heart, measured as the corrected QT-interval (QTc). Patients treated with these drugs should be monitored frequently via an ECG to screen for early changes indicating possible life-threating arrythmias. Especially during the Covid-19 pandemic, remote patient monitoring gained importance. The Withings Scanwatch offers automated analysis of the QTc remotely, thereby obviating the need for in-person visits. We aimed to compare automated QTc-measurements using a single lead ECG (SL-ECG) of a novel smartwatch (Withings Scanwatch, SW-ECG) with manual-measured QTc from a nearly simultaneously recorded standard 12-lead ECG. Methods We enrolled consecutive patients referred to a tertiary hospital for cardiac workup in a prospective, observational study. To obtain a SW-ECG, patients were instructed to keep their index finger on the stainless steel ring on the top case of the smartwatch continuously for 30 seconds The QT-interval was manually interpreted by two blinded, independent cardiologists through the tangent-method, using lead II or V5/V6. Bazett’s formula was used to calculate QTc. Results We prospectively enrolled 317 patients (48% female, mean age 63.3 ± 17.2 years). The smartwatch was able to automatically measure QTc-intervals in 177 patients (56%). The diagnostic accuracy of SW-ECG for detection of a QTc-interval ≥ 460ms as quantified by the area under the curve (AUC) was 0.91 (95%CI 86.4-95.9). The Bland-Altman analysis resulted in a bias of 6.6ms (95% limit of agreement (LoA) –58.6ms to 71.9ms) comparing automated QTc measurements via SW-ECG with manual QTc-measurement via 12-lead ECG (Figure 1). In 12 patients (6.9%) the difference between the two measurements was greater than the LoA. Premature ventricular complexes, noise or differences in heart rate were responsible in 8.3%, 83.0% and 8.3%, respectively, for observed outliers. Conclusion In this clinical validation of a direct-to-consumer smartwatch we found fair to good agreement between automated-SW-ECG QTc-measurements and manual 12-lead-QTc measurements. The SW-ECG, however, was only able to automatically calculate QTc-intervals in one half of all assessed patients. Our work shows, that the automated algorithm of the SW-ECG needs to be improved to be useful in a clinical setting.