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

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt


  • Fulltext

    Forlagets udgivne version, 5,17 MB, PDF-dokument

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. Twentyseven patients (25 males, median age 59 years) were included. Among the participants, ICDs recorded 262 VA events during 8,093 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.

TidsskriftJournal of Personalized Medicine
Udgave nummer6
Sider (fra-til)1-34
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
Funding: This study was part of the SCAUT research and development project co‐funded by the Innovation Fund Denmark #72‐2014‐1. It was also supported by the H2020 Societal Challenges: 769765 (Wellbeing and Health Virtual Coach, WellCo) and by the Active and Assisted Living pro‐ gram: AAL‐2019‐6‐120‐CP (Social Robot Companion to Support Homecare Nurses, Guardian).

Funding Information:
Conflicts of Interest: S.Z.D. serves as an advisor for Vital Beats and for Bristol‐Myers Squibb / Pfizer without relation to this work. J.H.S. is a member of a Medtronic advisory board and has received research grants from Medtronic (outside this study) and received speaker fees from Medtronic. T.O.A. is a co‐founder of Vital Beats and holds shares in the company. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. The authors declare no other conflict of interest.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

ID: 314299263