Outcomes following percutaneous coronary intervention and coronary artery bypass grafting surgery in Chinese, South Asian and white patients with acute myocardial infarction: administrative data analysis
Bibliographic record
Abstract
BACKGROUND: Little is known on whether there are ethnic differences in outcomes following percutaneous coronary intervention (PCI) and coronary artery bypass grafting surgery (CABG) after acute myocardial infarction (AMI). We compared 30-day and long-term mortality, recurrent AMI, and congestive heart failure in South Asian, Chinese and White patients with AMI who underwent PCI and CABG. METHODS: Hospital administrative data in British Columbia (BC), Canada were linked to the BC Cardiac Registry to identify all patients with AMI who underwent PCI (n = 4729) or CABG (n = 1687) (1999-2003). Ethnicity was determined from validated surname algorithms. Logistic regression for 30-day mortality and Cox proportional-hazards models were adjusted for age, sex, socio-economic status, severity of coronary disease, comorbid conditions, time from AMI to a revascularization procedure and distance to the nearest hospital. RESULTS: Following PCI, Chinese had higher short-term mortality (Odds Ratio (OR): 2.36, 95% CI: 1.12-5.00; p = 0.02), and South Asians had a higher risk for recurrent AMI (OR: 1.34, 95% CI: 1.08-1.67, p = 0.007) and heart failure (OR 1.81, 95% CI: 1.00-3.29, p = 0.05) compared to White patients. Risk of heart failure was higher in South Asian patients who underwent CABG compared to White patients (OR (95% CI) = 2.06 (0.92-4.61), p = 0.08). There were no significant differences in mortality following CABG between groups. CONCLUSIONS: Chinese and South Asian patients with AMI and PCI or CABG had worse outcomes compared to their White counterparts. Further studies are needed to confirm these findings and investigate potential underlying causes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".