Differences in Clinical Measures and Outcomes in South Asians vs Caucasians Attending Cardiac Rehabilitation
Bibliographic record
Abstract
Background South Asians have a greater predisposition to cardiac events, compared to Caucasians. Although cardiac rehabilitation programs (CRPs) are known to improve outcomes, data are sparse regarding benefits acquired by South Asians vs Caucasians. The objective of the current study was to determine the outcomes of South Asian patients undergoing CRPs, compared to Caucasian patients. Methods This study compared baseline characteristics and outcomes in all patients attending a CRP in Edmonton, Canada with a proportionately large South Asian population. Results From 1998 to 2016, a total of 811 South Asians and 5406 Caucasians attended CRPs. Baseline characteristics revealed that there were more nonsmokers (73.4% vs 29.4%, P < 0.001), with a lower body mass index (26.8 ± 0.1 vs 29.6 ± 0.1, P < 0.001), but higher prevalence of diabetes (37.7% vs 20.5%, P < 0.001) in the South Asian population. Outcome measures revealed that South Asians spent less time in the CRP (6.9 weeks ± 0.1 vs 7.3 weeks ± 0.1, P < 0.001), attended the nutrition class less (36.2% vs 53.4%, P < 0.001), and had a lower 6-minute walk improvement (66.9 m vs 73.6 m, P < 0.001). Frequency of use of β-blockers (86.9% vs 86.1%, P > 0.05), antiplatelet agents (96.3% vs 97.1%, P > 0.05), angiotensin-converting enzyme inhibitors (79.9% vs 80.0%, P > 0.05), and cholesterol-lowering agents (91.4% vs 93.8%, P > 0.05) was not significantly different. Conclusions Although South Asians seem to be prescribed and use proven pharmacologic treatments to the same extent as Caucasians, they appeared to benefit less from CRPs. Given higher event rates in South Asians, consideration should be given to altering the delivery of CRPs to South Asians to improve their efficacy.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".