Sex, Prescribing Practices and Guideline Recommended, Blood Pressure, and LDL Cholesterol Targets at Baseline in the BARI 2D Trial
Bibliographic record
Abstract
Background. Research has shown less aggressive treatment and poorer control of cardiovascular disease (CVD) risk factors in women than men. Methods. We analyzed sex differences in pharmacotherapy strategies and attainment of goals for hemoglobin A1c (HbA1c), blood pressure (BP), and low density lipoprotein cholesterol (LDL-C) in patients with type 2 diabetes and established coronary artery disease enrolled into the BARI 2D trial. Results. Similar numbers of drugs were prescribed in both women and men. Women were less frequent on metformin or sulfonylurea and more likely to take insulin and to be on higher doses of hydroxymethylglutaryl-CoA reductase inhibitors (statins) than men. After adjusting for baseline differences and treatment prescribed, women were less likely to achieve goals for HbA1c (OR = 0.71, 95% CI 0.57, 0.88) and LDL-C (OR = 0.64, 95% CI 0.53, 0.78). More antihypertensives were prescribed to women, and yet BP ≤ 130/80 mmHg did not differ by sex. Conclusions. Women entering the BARI 2D trial were as aggressively treated with drugs as men. Despite equivalent treatment, women less frequently met targets for HbA1c and LDL-C. Our findings suggest that there may be sex differences in response to drug therapies used to treat diabetes, hypertension, and hyperlipidemia.
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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 | 0.006 |
| 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) | 0.002 | 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".