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Record W4408104736 · doi:10.1016/j.cjco.2025.02.017

Wearable Devices for Exercise Prescription and Physical Activity Monitoring in Patients with Various Cardiovascular Conditions

2025· review· en· W4408104736 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCJC Open · 2025
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of TorontoSt. Michael's HospitalAcadia UniversityUniversity of Ottawa
Fundersnot available
KeywordsWearable computerExercise prescriptionMedical prescriptionPhysical activityMedicinePhysical medicine and rehabilitationPhysical therapyActivity monitorComputer sciencePharmacologyEmbedded system

Abstract

fetched live from OpenAlex

As wearable technologies have become increasingly affordable, accessible, and practical, an increasing number of people with cardiovascular disease are beginning to use consumer-grade devices.Common health and wellness metrics reported by wearable devices include heart rate, heart rhythm, and step count, which may afford opportunities to assess cardiovascular conditions, prescribe more personalized exercise for enhanced engagement, and monitor physical activity adherence in patients with cardiovascular disease.This narrative review discusses the application of wearable devices in patients with coronary artery disease, heart failure, atrial fibrillation (AF), cardiac implantable electric devices, and peripheral artery disease in different cardiovascular rehabilitation settings (eg, supervised and home-based).Available literature suggests that, when combined with telemonitoring, wearable devices can increase physical activity participation, thereby improving peak oxygen consumption ( _ VO 2peak ) and quality of life (QoL) in patients with coronary artery disease, enhancing physical function and QoL in patients with heart failure, and increasing walking capacity and _ VO 2peak in patients with peripheral R ESUM ELes technologies portables etant devenues de plus en plus abordables, accessibles et pratiques, un nombre croissant de personnes atteintes de maladies cardiovasculaires (MCV) commencent utiliser des dispositifs grand public.Les m etriques de sant e et de bien-tre commun ement rapport ees par les dispositifs portatifs comprennent la fr equence cardiaque (FC), le rythme cardiaque et le nombre de pas, ce qui peut permettre d' evaluer les conditions cardiovasculaires, de prescrire des exercices plus personnalis es pour am eliorer l'engagement et de surveiller l'adh esion l'activit e physique chez les patients atteints de MCV.Cette revue narrative traite de l'application des dispositifs portables chez les patients atteints de maladie coronarienne (MC), d'insuffisance cardiaque (IC), de fibrillation auriculaire (FA), porteurs de dispositifs electroniques cardiaques implantables (DEI), ou atteints de maladie art erielle p eriph erique (MAP) dans diff erents contextes de r eadaptation cardiovasculaire (par exemple, supervis ee et domicile).La litt erature disponible suggre que, lorsqu'ils sont associ es la t el esurveillance, les dispositifs portables peuvent augmenter la participation l'activit e physique, am eliorant ainsi la consommation Cardiovascular disease (CVD) is the leading cause of death globally, responsible for an estimated 17.9 million deaths each year, 1 with 30% of ischemic heart disease cases worldwide being linked to physical inactivity. 2 A supervised cardiovascular rehabilitation (CR) program prevents secondary events and reduces the risk of mortality in patients with CVD. 3 However, centre-based supervised CR is grossly underutilized, due to several barriers, including lack of physician recommendation, limited accessibility, lack of resources (eg, a CJC Open 7 (2025) 695e706

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.329
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it