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Record W3094706597 · doi:10.1016/j.cjca.2020.10.015

A Randomized Controlled Trial of an Exercise Maintenance Intervention in Men and Women After Cardiac Rehabilitation (ECO-PCR Trial)

2020· article· en· W3094706597 on OpenAlexafffundvenue
Robert D. Reid, Evyanne Wooding, Chris M. Blanchard, Mahshid Moghei, Jennifer Harris, Guy-Anne Proulx, Stéphanie A. Prince, Kerri A. Mullen, Gabriela Melo Ghisi, Murray Krahn, Caroline Chessex, Andrew Pipe, Amy E. Mark, Sherry L. Grace

Bibliographic record

VenueCanadian Journal of Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity Health NetworkUniversity of TorontoYork UniversityDalhousie UniversityUniversity of Ottawa
FundersHeart and Stroke Foundation of Canada
KeywordsMedicineRandomized controlled trialPhysical therapyRehabilitationIntervention (counseling)Internal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Exercise maintenance interventions are needed for cardiac rehabilitation (CR) graduates to maintain moderate and vigorous-intensity physical activity (MVPA). We tested an exercise facilitator intervention (EFI) to promote exercise maintenance compared with usual care (UC) separately in men and women. METHODS: This was a 3-site, randomized (1:1), parallel-group, superiority trial (ECO-PCR). CR graduates were stratified by site and sex and randomly allocated (concealed). EFI participants received a face-to-face introductory session, 5 small-group counseling teleconferences, and 3 personal calls from a trained facilitator over 50 weeks. In-person assessments were undertaken at baseline and 26 and 52 weeks after randomization. The primary outcome was weekly minutes of MVPA, measured by accelerometer. Secondary outcomes were exercise capacity, risk factors, quality of life, and enrollment in community-based exercise programs. Effects were tested with the use of linear mixed models. RESULTS: A total of 449 CR graduates (135 women, 314 men) were randomised (n = 226 EFI, n = 223 UC). In the intention-to-treat analysis for men and for women, there were no significant effects for treatment or time on MVPA. In a planned secondary analysis that considered only those adherent to EFI (completed ≥ 66% of sessions; per-protocol), bouted MVPA (ie, in sustained bouts of ≥ 10 min) was higher in women in the EFI group (mean = 132.6 ± 135.2 min/wk at 52 weeks) compared with UC (111.8 ± 113.1; P = 0.013). Regarding secondary outcomes, in women, a treatment group main effect was observed for blood pressure (P = 0.011) and exercise capacity (P = 0.019; both per-protocol) favouring EFI; no other differences were observed. CONCLUSIONS: In this trial of CR completers, an EFI showed promise for women, but was ineffective in men.

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.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.010
GPT teacher head0.287
Teacher spread0.277 · 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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2020
Admission routes3
Has abstractyes

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