Evidence map›Paper›PMID 34042996›Full record

ArticleJAMA network open2021

Association of Wearable Device Use With Pulse Rate and Health Care Use in Adults With Atrial Fibrillation.

Libo Wang, Kyron Nielsen, Joshua Goldberg, Jeremiah R Brown, John S Rumsfeld, Benjamin A Steinberg, Yue Zhang, Michael E Matheny, Rashmee U Shah

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
5.3field-weighted citation impact, top 3% of its field
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

30 citing papers in PubMed, 39 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Wearable health monitoring: wave of the future or waste of time?Global cardiology science & practice · 2024
    Review
  10. Article
  11. Review
  12. Article
  13. Observational
  14. Improved 1-year outcomes after active cooling during left atrial radiofrequency ablation.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2023
    Article
  15. Article
  16. Wearables in Cardiovascular Disease.Journal of cardiovascular translational research · 2023
    Review
  17. Mayo Clinic proceedings. Digital health · 2023
    Review
  18. Article
  19. Article
  20. Review
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

9 authors at 4 institutions in 1 country.

Libo WangDivision of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City.
Kyron NielsenDivision of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City.
Joshua GoldbergDepartment of Internal Medicine, University of Utah, Salt Lake City.
Jeremiah R BrownDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
John S RumsfeldUniversity of Colorado School of Medicine, Aurora.
Benjamin A SteinbergDivision of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City.
Yue ZhangDepartment of Internal Medicine, University of Utah, Salt Lake City.
Michael E MathenyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Rashmee U ShahDivision of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City.
University of Utah · USDartmouth College · USGeriatric Research Education and Clinical Center · USUniversity of Colorado Denver · US

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
Optimizing Outcomes for Patients with Heart Failure and Atrial FibrillationK23HL143156 · NHLBI · UNIVERSITY OF UTAH · PI STEINBERG, BENJAMIN ADAM · 2018 to 2022
$951k
Improving Cardiovascular Drug Safety With Automated Bleeding ClassificationK08HL136850 · NHLBI · UNIVERSITY OF UTAH · PI SHAH, RASHMEE U. · 2017 to 2020
$652k
Healthcare Impact of Consumer-Driven Atrial Fibrillation DetectionR03HL148372 · NHLBI · UNIVERSITY OF UTAH · PI SHAH, RASHMEE U. · 2019 to 2020
$153k
NCATS NIH HHS UL1 TR002538NHLBI NIH HHS K08 HL136850NHLBI NIH HHS K23 HL143156NHLBI NIH HHS R03 HL148372
6 · The paper itself

Abstract

Importance: Increasingly, individuals with atrial fibrillation (AF) use wearable devices (hereafter wearables) that measure pulse rate and detect arrhythmia. The associations of wearables with health outcomes and health care use are unknown. Objective: To characterize patients with AF who use wearables and compare pulse rate and health care use between individuals who use wearables and those who do not. Design, Setting, and Participants: This retrospective, propensity-matched cohort study included 90 days of follow-up of patients in a tertiary care, academic health system. Included patients were adults with at least 1 AF-specific International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code from 2017 through 2019. Electronic medical records were reviewed to identify 125 individuals who used wearables and had adequate pulse-rate follow-up who were then matched using propensity scores 4 to 1 with 500 individuals who did not use wearables. Data were analyzed from June 2020 through February 2021. Exposure: Using commercially available wearables with pulse rate or rhythm evaluation capabilities. Main Outcomes and Measures: Mean pulse rates from measures taken in the clinic or hospital and a composite health care use score were recorded. The composite outcome included evaluation and management, ablation, cardioversion, telephone encounters, and number of rate or rhythm control medication orders. Results: Among 16 320 patients with AF included in the analysis, 348 patients used wearables and 15 972 individuals did not use wearables. Prior to matching, patients using wearables were younger (mean [SD] age, 64.0 [13.0] years vs 70.0 [13.8] years; P < .001) and healthier (mean [SD] CHA2DS2-VASc [congestive heart failure, hypertension, age ≥ 65 years or 65-74 years, diabetes, prior stroke/transient ischemic attack, vascular disease, sex] score, 3.6 [2.0] vs 4.4 [2.0]; P < .001) compared with individuals not using wearables, with similar gender distribution (148 [42.5%] women vs 6722 women [42.1%]; P = .91). After matching, mean pulse rate was similar between 125 patients using wearables and 500 patients not using wearables (75.01 [95% CI, 72.74-77.27] vs 75.79 [95% CI, 74.68-76.90] beats per minute [bpm]; P = .54), whereas mean composite use score was higher among individuals using wearables (3.55 [95% CI, 3.31-3.80] vs 3.27 [95% CI, 3.14-3.40]; P = .04). Among measures in the composite outcome, there was a significant difference in use of ablation, occurring in 22 individuals who used wearables (17.6%) vs 37 individuals who did not use wearables (7.4%) (P = .001). In the regression analyses, mean composite use score was 0.28 points (95% CI, 0.01 to 0.56 points) higher among individuals using wearables compared with those not using wearables and mean pulse was similar, with a -0.79 bpm (95% CI -3.28 to 1.71 bpm) difference between the groups. Conclusions and Relevance: This study found that follow-up health care use among individuals with AF was increased among those who used wearables compared with those with similar pulse rates who did not use wearables. Given the increasing use of wearables by patients with AF, prospective, randomized, long-term evaluation of the associations of wearable technology with health outcomes and health care use is needed.

Indexed as

Facilities and Services UtilizationHeart RateMonitoring, PhysiologicWearable Electronic DevicesAdultAgedAtrial FibrillationFemaleFollow-Up StudiesHealth ServicesHumansMaleMiddle AgedPropensity ScoreRetrospective StudiesSelf-Management

Identifiers

PMID34042996
PMCPMC8160588
OpenAlexW3165531410

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.