Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study.

Background: QTc interval monitoring, for the prevention of drug-induced arrhythmias is necessary, especially in the context of coronavirus disease 2019 (COVID-19). For the provision of widespread use, surrogates for 12‑lead ECG QTc assessment may be useful. This prospective observational study compared QTc duration assessed by artificial intelligence (AI-QTc) (Cardiologs®, Paris, France) on smartwatch single‑lead electrocardiograms (SW-ECGs) with those measured on 12‑lead ECGs, in patients with early stage COVID-19 treated with a hydroxychloroquine-azithromycin regimen.
Methods: Consecutive patients with COVID-19 who needed hydroxychloroquine-azithromycin therapy, received a smartwatch (Withings Move ECG®, Withings, France). At baseline, day-6 and day-10, a 12‑lead ECG was recorded, and a SW-ECG was transmitted thereafter. Throughout the drug regimen, a SW-ECG was transmitted every morning at rest. Agreement between manual QTc measurement on a 12‑lead ECG and AI-QTc on the corresponding SW-ECG was assessed by the Bland-Altman method.
Results: 85 patients (30 men, mean age 38.3 ± 12.2 years) were included in the study. Fair agreement between manual and AI-QTc values was observed, particularly at day-10, where the delay between the 12‑lead ECG and the SW-ECG was the shortest (-2.6 ± 64.7 min): 407 ± 26 ms on the 12‑lead ECG vs 407 ± 22 ms on SW-ECG, bias -1 ms, limits of agreement -46 ms to +45 ms; the difference between the two measures was <50 ms in 98.2% of patients.
Conclusion: In real-world epidemic conditions, AI-QTc duration measured by SW-ECG is in fair agreement with manual measurements on 12‑lead ECGs. Following further validation, AI-assisted SW-ECGs may be suitable for QTc interval monitoring.
Registration: ClinicalTrial.govNCT04371744.
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