P2511Differences in clinical measures and outcomes in South Asians (SA) vs Caucasians (CA) attending a cardiac rehabilitation program (CRP)
Bibliographic record
Abstract
SA have a greater predisposition to cardiac events compared to CA. Although CRP is known to improve outcomes, little data is available regarding benefits acquired by SA considering language barriers, possible lower socioeconomic status and cultural norms. The study examined this issue on a population of pts attending a CRP in Edmonton with a proportionately large SA population. All data was collected & entered into a database formulated within the SPSS data management system. All participated in 4–12 week program including aerobic & isometric exercise, dietary evaluation and other risk factor modifications. From Jan 1998–April 2016, 5406 CA (Age 61.5±0.2; Males = 76.4%) and 811 SA (Age 60.5±0.4; Males = 77.1%) attended CRP. Baseline characteristics revealed more nonsmokers (70.6% vs 26.6%, p<0.05), lower BMI (26.8±0.1 vs 29.4±0.1, p<0.05) but higher diabetes (27.7% vs 21.5%, p<0.05) in the SA population. Higher Beck Depression Inventory scores (8.0±0.3 vs 7.2±0.1, p<0.05) and HBA1C (6.5±0.2 vs 5.7±0.1, p<0.05) was found. There were also more unemployed (4.5% vs 2.5%, p<0.05) and homemakers (12.6% vs 4.0%, p<0.05) amongst the SA. Outcome measures revealed that SA spent less time on the program (6.9 wks ±0.1 vs 7.3wks ±0.1, p<0.05), attended the nutrition class less (36.2% vs 53.4%, p<0.05) and had lower pre CRP 6 min walk results (414.0m ±4.0 vs 446.5m ±1.6, p<0.05). SA achieved lower 6 min walk improvement from pre - post CRP (63.4m ±2.4 vs 70.0m ±1.0, p<0.05) as well. However the frequency of beta blocker (86.9% vs 86.1%, p>0.05), anti platelet agent (96.3% vs 97.1%, p>0.05), ACEI/ARBS (79.9% vs 80.0%, p>0.05) and cholesterol lowering agent (93.8% vs 91.4%, p>0.05) use was not significantly different.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".