Impact of diabetes on coronary artery disease in women and men: a meta-analysis of prospective studies.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 it