Ethnic Disparity in Mortality Among Ischemic Heart Disease Patients. A-20 Years Outcome Study From Israel
Bibliographic record
Abstract
Background: Long-term morbidity and mortality data among ischemic heart disease (IHD) patients of different ethnicities are conflicting. We sought to determine the independent association of ethnicity and all-cause mortality over two decades of follow-up of Israeli patients. Methods: Our study comprised 15,524 patients including 958 (6%) Arab patients who had been previously enrolled in the Bezafibrate Infarction Prevention (BIP) registry between February 1, 1990, and October 31, 1992, and subsequently followed-up for long-term mortality. We compared clinical characteristics and outcomes of Israeli Arabs and Jews. Propensity score matching (PSM) (1:2 ratios) was used for validation. Results: Arab patients were significantly younger (56 ± 7 years vs. 60 ± 7 years; p < 0.001; respectively), and had more cardiovascular disease (CVD) risk factors. Kaplan-Meier survival analysis showed that all-cause mortality was significantly higher among Arab patients (67 vs. 61%; log-rank p < 0.001). Multivariate adjusted analysis showed that mortality risk was 49% greater (HR 1.49; 95% CI: 1.37–1.62; p < 0.001) among Arabs. Conclusions: Arab ethnicity is independently associated with an increased 20-year all-cause mortality among patients with established IHD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".