Sex‐specific associations between cardiovascular risk factors and myocardial infarction in patients with type 2 diabetes: The <scp>ADVANCE‐ON</scp> study
Bibliographic record
Abstract
AIM: To examine possible sex differences in the excess risk of myocardial infarction (MI) consequent to a range of conventional risk factors in a large-scale international cohort of patients with diabetes, and to quantify these potential differences both on the relative and absolute scales. MATERIALS AND METHODS: Eleven thousand and sixty-five participants (42% women) with type 2 diabetes in the ADVANCE trial and its post-trial follow-up study, ADVANCE-ON, were included. Cox regression models were used to estimate hazard ratios (HRs) for associations between risk factors and MI (fatal and non-fatal) by sex, and the women-to-men ratio of HRs (RHR). RESULTS: Over a median of 9.6 years of follow-up, 719 patients experienced MI. Smoking status, smoking intensity, higher systolic blood pressure (SBP), HbA1c, total and LDL cholesterol, duration of diabetes, triglycerides, body mass index (BMI) and lower HDL cholesterol were associated with an increased risk of MI in both sexes. Furthermore, some variables were associated with a greater relative risk of MI in women than men: RHRs were 1.75 (95% CI: 1.05-2.91) for current smoking, 1.53 (1.00-2.32) for former smoking, 1.18 (1.02-1.37) for SBP, and 1.13 (95% CI, 1.003-1.26) for duration of diabetes. Although incidence rates of MI were higher in men (9.3 per 1000 person-years) compared with women (5.8 per 1000 person-years), rate differences associated with risk factors were greater in women than men, except for HDL cholesterol and BMI. CONCLUSIONS: In patients with type 2 diabetes, smoking, higher SBP and longer duration of diabetes had a greater relative and absolute effect in women than men, highlighting the importance of routine sex-specific approaches and early interventions in women with diabetes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".