Age Difference Explains Gender Difference in Cardiac Intervention Rates After Acute Myocardial Infarction
Bibliographic record
Abstract
Many investigators have reported higher rates of cardiac procedures for males than females after acute myocardial infarction (AMI), suggesting that men are treated more aggressively than women. However, others have reported no significant differences after controlling for age, resulting in uncertainty about the existence of a true gender bias in cardiac care. In this study, a population-based cohort approach was used to calculate age-specific procedure rates by sex from administrative data. Chi-square tests and generalized linear modelling were used to assess gender differences and interactions. For all four procedures studied, rates were significantly higher for males than females (p<0.01). However, age-specific rates revealed few significant differences by gender and a sharp decrease in intervention rates with age for both males and females. Generalized linear modelling confirmed that patient age was a significant predictor of intervention rates, whereas sex was not. The significant gender difference in overall rates was completely confounded by the older age profile of female AMI patients compared to their male counterparts.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".