Gender and ethnic disparities in outcome following acute myocardial infarction among Bedouins and Jews in Southern Israel
Bibliographic record
Abstract
BACKGROUND: Previous studies have documented gender-ethnic disparities in outcomes following acute myocardial infarction (AMI). This study evaluates such disparities in the Negev, Israel, and reviews potentially responsible mechanisms. METHODS: Patients discharged with AMI were classified into young (<70 years), elders (≥70 years) and gender-ethnicity groups: Female Bedouins (FB), Female Jews (FJ), Male Bedouins (MB) and Male Jews (MJ). The primary outcome was 1-year all-cause mortality. Prognosis was assessed using Kaplan-Meier approach. Multivariable analyses assessing hazard ratios (HRs) for mortality were performed using the Cox proportional hazards regression models in two steps controlling for (i) the Ontario Acute Myocardial Infarction Mortality Prediction Rules (OAMIMPRs) and (ii) the OAMIMPR and additional potential confounders. RESULTS: Of 2669 subjects, 45.8% were elders, 66.2% male and 10.9% Bedouin. The mortality rate was 12.3% (young 4.6%, elders 22%). Survival was significantly lower in FB compared with MB in the elderly stratum (P = 0.025). Multivariate analyses demonstrated similar risks for dying among the young. In the elders, the first multivariate analysis showed greater risk for mortality in FB. Using FB as the reference group, the HRs were as follows: HR((MB)) = 0.36 [95% confidence interval (CI): 0.14-0.9]; HR((FJ)) = 0.5 (95% CI: 0.27-0.9) and HR((MJ)) = 0.5 (95% CI: 0.28-0.91). In the second analysis, the HRs were as follows: HR((MB)) = 0.37 (95% CI: 0.14-0.93); HR((FJ)) = 0.58 (95% CI: 0.32-1.07) and HR((MJ)) = 0.56 (95% CI: 0.31-1.03). CONCLUSIONS: Elderly FB have poor 1-year prognosis following AMI compared with MB, MJ and FJ when controlling for the OAMIMPR model, yet when controlling for other potential confounders the differences are of borderline significance in relation to Jewish subjects. A culturally and economically sensitive programme focusing on tertiary prevention in these patients is warranted.
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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 | 0.000 |
| 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".