Technology‐based Comprehensive Cardiac Rehabilitation Therapy (TaCT) for women with cardiovascular disease in a middle‐income setting: A randomized controlled trial protocol
Bibliographic record
Abstract
Women are underrepresented in cardiac rehabilitation (CR) despite the benefits, and this is exacerbated in lower-resource settings where CR is insufficiently available. In this randomized controlled trial, the effectiveness of the Technology-based Comprehensive Cardiac Rehabilitation Therapy (TaCT) electronic cardiac rehabilitation (eCR) intervention on functional capacity, risk factors, quality of life, heart-health behaviors, symptoms, and morbidity will be tested among women with CVD in a middle-income country. Following a pilot study, a single-center, single-blinded, 2 parallel-arm (1:1 SNOSE) superiority trial comparing an eCR intervention (TaCT) to usual care, with assessments pre-intervention and at 3 and 6 months will be undertaken. One hundred adult women will be recruited. Permuted block (size 10) randomization will be applied. The 6-month intervention comprises an app, website, SMS texts with generic heart-health management advice, and bi-weekly 1:1 telephone calls with a nurse trainee. Individualized exercise prescriptions will be developed based on an Incremental Shuttle Walk Test (primary outcome) and dietary plans based on 24 h dietary recall. A yoga/relaxation video will be provided via WhatsApp, along with tobacco cessation support and a moderated group chat. At 3 months, intervention engagement and acceptability will be assessed. Analyses will be conducted based on intent-to-treat. If results of this novel trial of women-focused eCR in a middle-income country demonstrate clinically-significant increases in functional capacity, this could represent an important development for the field considering this would be an important outcome for women and would translate to lower mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.021 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.065 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".