Impact of diabetes on coronary artery disease in women and men: a meta-analysis of prospective studies.
Bibliographic record
Abstract
OBJECTIVE: Women are at a much lower risk of coronary disease mortality than men are. It is widely believed that diabetes "erases" this female advantage, increasing the risk of heart disease much more in women than in men. In reality, the extent of this increased risk is controversial, with studies showing conflicting results and wide confidence intervals. Clarification of this issue has implications for the pathogenesis of coronary disease, and for public health efforts to reduce coronary disease in women. RESEARCH DESIGN AND METHODS: We performed a meta-analysis to calculate a summary estimate of the relative risk of coronary death among women with diabetes as compared to those without. For comparison, we also calculated the analogous risk among men. All prospective cohort studies containing both men and women, and both patients with and without diabetes, were examined. Sixteen studies were identified; 10 had sufficient data for statistical analysis. RESULTS: After combining studies that adjusted for other cardiac risk factors, the relative risk of coronary death from diabetes was 2.58 (95% CI 2.05-3.26) for women and 1.85 (1.47-2.33) for men. This difference is statistically significant (P = 0.045). Other sensitivity analyses did not change these estimates appreciably. CONCLUSIONS: The impact of diabetes on the risk of coronary death is significantly greater for women than men. Further research is required to explain this clinically meaningful difference between the sexes.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.048 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".