Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study

• Published in: Journal of personalized medicine Vol. 12; no. 6; p. 942
• Main Authors: Frodi, Diana My, Manea, Vlad, Diederichsen, Søren Zöga, Svendsen, Jesper Hastrup, Wac, Katarzyna, Andersen, Tariq Osman
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.06.2022; MDPI
• Subjects: Algorithms; Arrhythmia; Behavior; Cardiac arrhythmia; Cardiology; Cardiovascular diseases; consumer-wearable activity tracker; Data analysis; Defibrillators; Heart failure; Heart rate; implantable cardioverter-defibrillator; Medical prognosis; Mortality; Observational studies; Patients; Physical activity; Precision medicine; R&D; Research & development; Sleep; Variables; Ventricle; ventricular arrhythmia; wearable; Denmark; United States > US; San Francisco California; sleep; ventricular arrhythmia; risk assessment; heart rate; wearable; consumer-wearable activity tracker; early detection; implantable cardioverter-defibrillator; co-calibration; physical activity
• ISSN: 2075-4426; 2075-4426
• DOI: 10.3390/jpm12060942

Ventricular arrhythmia (VA) is a leading cause of sudden death and health deterioration. Recent advances in predictive analytics and wearable technology for behavior assessment show promise but require further investigation. Yet, previous studies have only assessed other health outcomes and monitored patients for short durations (7−14 days). This study explores how behaviors reported by a consumer wearable can assist VA risk prediction. An exploratory observational study was conducted with participants who had an implantable cardioverter-defibrillator (ICD) and wore a Fitbit Alta HR consumer wearable. Fitbit reported behavioral markers for physical activity (light, fair, vigorous), sleep, and heart rate. A case-crossover analysis using conditional logistic regression assessed the effects of time-adjusted behaviors over 1−8 weeks on VA incidence. Twenty-seven patients (25 males, median age 59 years) were included. Among the participants, ICDs recorded 262 VA events during 8093 days monitored by Fitbit (median follow-up period 960 days). Longer light to fair activity durations and a higher heart rate increased the odds of a VA event (p < 0.001). In contrast, lengthier fair to vigorous activity and sleep durations decreased the odds of a VA event (p < 0.001). Future studies using consumer wearables in a larger population should prioritize these outcomes to further assess VA risk.