Cardiac Rehabilitation Outcomes by Ethnocultural Background
Bibliographic record
Abstract
BACKGROUND: Patients of diverse ethnocultural backgrounds are underrepresented among participants and, hence, little is known about their outcomes. The objectives of this study were to compare cardiac rehabilitation (CR) utilization, cardiovascular risk factor reduction (blood pressure, lipids, anthropometrics), and functional capacity between white and ethnocultural minority patients participating in CR across Canada. METHODS: The study was a retrospective, observational cohort study using the Canadian Cardiac Rehab Registry (CCRR). Participants from an ethnocultural minority (n ≥ 25) were propensity-matched to white participants based on sociodemographic and clinical characteristics. CR outcomes were compared. RESULTS: In the CCRR, 3848 (53.8%) participants had an ethnocultural background reported. Of those, whites (n = 3630) and South Asians (n = 26), Southeast Asians (n = 45), and Arab/West Asians (n = 37) minorities had sufficient representation in the registry to be analyzed. In the matched sample, 364 (97.1%) participants completed a discharge assessment. Southeast Asian participants adhered to (96.5%, P = .02) and completed (88.2%, P = .02) CR more often than white participants (90.2% and 55.6%, respectively). Southeast Asian participants had significantly lower diastolic blood pressure (P = .002) at CR discharge than matched white participants. No other differences in outcomes or functional capacity were observed. CONCLUSIONS: Ethnocultural minorities make up a small proportion of CR participants in Canada. However, when they do participate, they achieve similar CR outcomes compared with white participants. CR programs should seek to ensure ethnoculturally diverse patients are referred to their programs and ensure their programs are culturally sensitive to the needs of the preponderant ethnocultural groups in their catchment areas.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".