Abstract 13306: Substantial Variation in the Rate of Coronary Artery Disease Among Ontario Immigrants
Bibliographic record
Abstract
Immigrants constitute a substantial proportion of the population in Western Europe and North America. Although prior studies have suggested that a "healthy immigrant effect" exists, little is known about the extent and variation of stable obstructive coronary artery disease (CAD) among immigrants. We evaluated the association of country of origin and the rates of stable CAD among immigrants. We assembled a cohort of immigrants and non-immigrants who received elective cardiac catheterization in Ontario, Canada, between April 1, 2012 and March 31, 2021. Immigrants were categorized by their country of origin into 7 regions: Africa, Caribbean, Latin America, Western Countries, East Asia, South Asia, and Middle East. Our main outcome was the rate of obstructive CAD (left main stenosis ≥50% or major epicardial vessel stenosis ≥70%). Multivariable logistic regression analyses adjusting for age, cardiac risk factors, and socioeconomic status was used to study the association of country of birth with presence of CAD. The study included 208,363 non-immigrants and 36,139 immigrants: 13,503 from South Asia, 6,839 from Western Countries, 5,036 from East Asia, 4,374 from the Middle East, 2,481 from Latin America, 2,320 from Caribbean, and 1,586 from Africa. Obstructive CAD was found in 47.1% of immigrants and 47.4% of non-immigrants. Immigrants from South Asia had the highest rate of obstructive CAD at 53.7% and those from the Caribbean had the lowest rate at 32.5%. South Asian men and women had the highest odds of obstructive CAD compared to non-immigrants (Figure). Despite the conventional belief that immigrants have better health status, we found that immigrants in Canada had higher odds of obstructive CAD than non-immigrants. In addition, significant variation exists among patients by country of origin even after accounting for the traditional cardiac risk factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".