Abstract 13692: Incidence, Recurrence, and Ethnicity Specific Risk Factors for Premature Coronary Artery Disease in South Asians and Europeans
Bibliographic record
Abstract
Introduction: Premature coronary artery disease (CAD) incidence is increasing globally. South Asians (SA) have a disproportionately high burden of atherosclerotic cardiovascular disease (ASCVD). However, the effect of SA ethnicity on the risk of recurrent events in patients with premature CAD has not been prospectively evaluated. Methods: Patients in the SAVEBC and UK biobank (UKB) registries were enrolled and stratified by ethnicity and presence of premature CAD. The co-primary outcomes were to compare proportion of premature CAD and the incidence of recurrent ASVCD events. Secondary exploratory outcomes included describing demographic, physical, biochemical variables between cohorts. Results: 11,136 patients were included, 1,129 (143 SA; 21%) were from SAVEBC and 10,007 (400 SA; 4.0%) from UKB. There was a higher proportion of premature CAD in SA compared to Caucasians in UKB (5.2% vs. 2.0%, p < 0.001). Similarly, SA were overrepresented in SAVEBC (21% of cohort vs. 7.9% of British Columbia population). SA compared to Caucasians with premature CAD had increased prevalence of diabetes (SAVEBC: 20.1% vs 13.8%, p=0.08; UKB: 37.5% vs 18.0%, p<0.001), and lower mean HDL cholesterol (SAVEBC: 1.4±0.4 vs 1.5±0.4, p=0.21; UKB: 1.1±0.3 vs 1.2±0.3, p<0.001). SA had more diffuse disease reflected by more coronary segments affected (4.9±3.0 vs. 4.1±2.6, p=0.05), and a trend towards more affected coronary vessels compared to Caucasians (1.31±1.4 vs. 0.61±0.91, p=0.14). SA had greater incidence of recurrent ASCVD vs. Caucasians (4.19 vs. 3.08 events per 100 P-Y; incidence rate ratio p-value < 0.001). SA had higher risk of recurrent ASCVD events (HR 1.35, 95% CI 1.13,1.61, p<0.001). SA ethnicity remained a predictor of recurrent events on adjusted COX regression (HR 1.24, 95% CI 1.03,1.48, p=0.02). Conclusion: Using two prospective registries, SA had a higher proportion of premature CAD and recurrent cardiovascular events with shorter time to recurrent events. Some risk may be explained by adverse cardiometabolic profiles, however significant risk mechanisms are yet to be elucidated. Understanding the unique mechanisms of cardiovascular risk in SA is critical to appropriately identify high-risk individuals and initiate contemporary preventative therapies.
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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 | 0.000 | 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) | 0.003 | 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".