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 tidsskriftTidsskriftartikelfagfællebedømt

Standard

Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator : An Exploratory Observational Study. / Frodi, Diana My; Manea, Vlad; Diederichsen, Søren Zöga; Svendsen, Jesper Hastrup; Wac, Katarzyna; Andersen, Tariq Osman.

I: Journal of Personalized Medicine, Bind 12, Nr. 6, 942, 2022, s. 1-34.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Frodi, DM, Manea, V, Diederichsen, SZ, Svendsen, JH, Wac, K & Andersen, TO 2022, 'Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator: An Exploratory Observational Study', Journal of Personalized Medicine, bind 12, nr. 6, 942, s. 1-34. https://doi.org/10.3390/jpm12060942

APA

Frodi, D. M., Manea, V., Diederichsen, S. Z., Svendsen, J. H., Wac, K., & Andersen, T. O. (2022). Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator: An Exploratory Observational Study. Journal of Personalized Medicine, 12(6), 1-34. [942]. https://doi.org/10.3390/jpm12060942

Vancouver

Frodi DM, Manea V, Diederichsen SZ, Svendsen JH, Wac K, Andersen TO. Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator: An Exploratory Observational Study. Journal of Personalized Medicine. 2022;12(6):1-34. 942. https://doi.org/10.3390/jpm12060942

Author

Frodi, Diana My ; Manea, Vlad ; Diederichsen, Søren Zöga ; Svendsen, Jesper Hastrup ; Wac, Katarzyna ; Andersen, Tariq Osman. / Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator : An Exploratory Observational Study. I: Journal of Personalized Medicine. 2022 ; Bind 12, Nr. 6. s. 1-34.

Bibtex

@article{5802d5df388a4eb99a1e4db1af910b22,
title = "Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator: An Exploratory Observational Study",
abstract = "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.",
keywords = "consumer‐wearable activity tracker, co‐calibration, early detection, heart rate, implantable cardioverter‐defibrillator, physical activity, risk assessment, sleep, ventricular arrhythmia, wearable",
author = "Frodi, {Diana My} and Vlad Manea and Diederichsen, {S{\o}ren Z{\"o}ga} and Svendsen, {Jesper Hastrup} and Katarzyna Wac and Andersen, {Tariq Osman}",
note = "Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2022",
doi = "10.3390/jpm12060942",
language = "English",
volume = "12",
pages = "1--34",
journal = "Journal of Personalized Medicine",
issn = "2075-4426",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "6",

}

RIS

TY - JOUR

T1 - Using Consumer‐Wearable Activity Trackers for Risk Prediction of Life‐Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter‐Defibrillator

T2 - An Exploratory Observational Study

AU - Frodi, Diana My

AU - Manea, Vlad

AU - Diederichsen, Søren Zöga

AU - Svendsen, Jesper Hastrup

AU - Wac, Katarzyna

AU - Andersen, Tariq Osman

N1 - Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - consumer‐wearable activity tracker

KW - co‐calibration

KW - early detection

KW - heart rate

KW - implantable cardioverter‐defibrillator

KW - physical activity

KW - risk assessment

KW - sleep

KW - ventricular arrhythmia

KW - wearable

UR - http://www.scopus.com/inward/record.url?scp=85132142103&partnerID=8YFLogxK

U2 - 10.3390/jpm12060942

DO - 10.3390/jpm12060942

M3 - Journal article

C2 - 35743727

AN - SCOPUS:85132142103

VL - 12

SP - 1

EP - 34

JO - Journal of Personalized Medicine

JF - Journal of Personalized Medicine

SN - 2075-4426

IS - 6

M1 - 942

ER -

ID: 314299263