Evidence map›Paper›PMID 41879156›Full record

ReviewEuropean heart journal2026

Wearable devices and cardiovascular health: revolutionizing remote monitoring and disease prevention.

Andrew M Hughes, Daniel J Taylor, Paul D Morris, Evan L Brittain

Abstract readReview
In one paragraph

Review in European heart journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Observational
  4. Article
  5. Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026
    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

4 authors.

Andrew M HughesDivision of Cardiovascular Medicine, University of Minnesota, Minneapolis, MN, USA.
Daniel J TaylorDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Paul D MorrisDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Evan L BrittainDivision of Cardiovascular Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Office 680, Nashville, TN 37203, USA.ORCID 0000-0001-5843-3392

Funding

NIH HHS
6 · The paper itself

Abstract

Wearable devices are transforming cardiovascular medicine by enabling continuous monitoring of physiologic and behavioural measures outside of traditional clinical settings. Smartwatches and activity trackers, the most widely used wearables, employ motion and biometric sensors to measure physical activity, sleep quality, heart rate, and rhythm. By converting health goals into objective, quantifiable measures, wearable devices empower patients to assume a more active role in their health while providing clinicians with novel opportunities for longitudinal, real-world assessment. Clinical applications span the cardiovascular continuum from lifestyle interventions targeting physical activity and sleep to the remote management of chronic conditions such as heart failure. Widespread clinical adoption of wearables remains limited by challenges, such as variability in device methodology, data outputs, validation, and intended use; incompatibility with existing electronic health records; and the lack of standardized, evidence-based workflows for clinicians to efficiently interpret and act upon wearable data. This review summarizes the current landscape of wearable technologies in cardiovascular medicine by highlighting key clinical applications, evidence gaps in the existing literature, the role of artificial intelligence, and barriers to implementation. We discuss strategies to enhance clinical integration and strengthen the current evidence base while also providing practical guidance to help clinicians navigate commonly encountered clinical scenarios.

Indexed as

Cardiovascular DiseasesWearable Electronic DevicesArtificial IntelligenceDigital HealthExerciseHumansMonitoring, PhysiologicRemote Patient MonitoringTelemedicineArtificial intelligenceBehavioural monitoringCardiovascular diseaseCardiovascular riskWearable devices

Identifiers

PMID41879156
PMCPMC13178683

What OpenQuestion holds

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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.