Evidence map›Paper›PMID 35743727›Full record

ArticleJournal of personalized medicine2022

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 Frodi, Vlad Manea, Søren Zöga Diederichsen, Jesper Hastrup Svendsen, Katarzyna Wac, Tariq Osman Andersen

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Diana My FrodiDepartment of Cardiology, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.ORCID 0000-0001-7074-5575
Vlad ManeaDepartment of Computer Science, Faculty of Science, University of Copenhagen, 2100 Copenhagen, Denmark.ORCID 0000-0002-1761-2850
Søren Zöga DiederichsenDepartment of Cardiology, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.ORCID 0000-0002-9687-0857
Jesper Hastrup SvendsenDepartment of Cardiology, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.ORCID 0000-0001-8466-8515
Katarzyna WacDepartment of Computer Science, Faculty of Science, University of Copenhagen, 2100 Copenhagen, Denmark.ORCID 0000-0002-8060-399X
Tariq Osman AndersenDepartment of Computer Science, Faculty of Science, University of Copenhagen, 2100 Copenhagen, Denmark.ORCID 0000-0002-9342-5520

Funding

Active and Assisted Living AAL-2019-6-120-CPH2020 Societal Challenges 769765Innovation Fund Denmark 72-2014-1
6 · The paper itself

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. 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.

Indexed as

co-calibrationconsumer-wearable activity trackerearly detectionheart rateimplantable cardioverter-defibrillatorphysical activityrisk assessmentsleepventricular arrhythmiawearable

Identifiers

PMID35743727
PMCPMC9225164

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.