Is there a clinically significant gender bias in post-myocardial infarction pharmacological management in the older (>60) population of a primary care practice?
Bibliographic record
Abstract
Background: Differences in the management of coronary artery disease between men and women have been reported in the literature.There are few studies of potential inequalities of treatment that arise from a primary care context.This study investigated the existence of such inequalities in the medical management of post myocardial infarction in older patients.Methods: A comprehensive chart audit was conducted of 142 men and 81 women in an academic primary care practice.Variables were extracted on demographic variables, cardiovascular risk factors, medical and non-medical management of myocardial infarction.Results: Women were older than men.The groups were comparable in terms of cardiac risk factors.A statistically significant difference (14.6%: 95% CI 0.048-28.7 p = 0.047) was found between men and women for the prescription of lipid lowering medications.25.3% (p = 0.0005, CI 11.45, 39.65) more men than women had undergone angiography, and 14.4 % (p = 0.029, CI 2.2, 26.6) more men than women had undergone coronary artery bypass graft surgery.Conclusion: Women are less likely than men to receive lipid-lowering medication which may indicate less aggressive secondary prevention in the primary care setting.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".