Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study.
Diana My FrodiVlad ManeaSøren Zoega DiederichsenJesper Hastrup SvendsenKatarzyna WacTariq Osman AndersenPublished in: Journal of personalized medicine (2022)
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.
Keyphrases
- heart rate
- physical activity
- heart rate variability
- blood pressure
- end stage renal disease
- health information
- ejection fraction
- heart failure
- chronic kidney disease
- newly diagnosed
- prognostic factors
- public health
- healthcare
- peritoneal dialysis
- left ventricular
- risk factors
- atrial fibrillation
- computed tomography
- clinical trial
- randomized controlled trial
- risk assessment
- skeletal muscle
- body mass index
- patient reported outcomes
- open label
- deep learning
- catheter ablation
- insulin resistance
- artificial intelligence
- gestational age