Pilot testing of the International Council of Cardiovascular Prevention and Rehabilitation Registry
Bibliographic record
Abstract
The International Council of Cardiovascular Prevention and Rehabilitation developed an International Cardiac Rehabilitation (CR) Registry (ICRR) to support CR programs in low-resource settings to optimize care provision and patient outcomes. This study assessed implementation of the ICRR, site data steward experience with on-boarding and data entry, and patient acceptability. Multimethod observational pilot involves (I) analysis of ICRR data from three centers (Iran, Pakistan, and Qatar) from inception to May 2022, (II) focus group with on-boarded site data stewards (also from Mexico and India), and (III) semistructured interviews with participating patients. Five hundred sixty-seven patients were entered. Based on volumes at each program, 85.6% of patients were entered in ICRR. 99.3% patients approached consented to participate. The average time to enter data at pre- and follow-up assessments by source was 6.8-12.6 min. Of 22 variables preprogram, completion was 89.5%. Among patients with any follow-up data, of four program-reported variables, completion was 99.0% in program completers and 51.5% in none; of 10 patient-reported variables, completion was 97.0% in program completers and 84.8% in none. The proportion of patients with any follow-up data was 84.8% in program completers, with 43.6% of noncompleters having any data entered other than completion status. Twelve data stewards participated in the focus group. Main themes were valuable on-boarding process, data entry, process of engaging patients, and benefits of participation. Thirteen patients were interviewed. Themes were good understanding of the registry, positive experience providing data, and value of lay summary and eagerness for annual assessment. Feasibility and data quality of ICRR were demonstrated.
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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 | 0.142 | 0.119 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".