Statin Therapy, Cardiovascular Events, and Total Mortality in the Heart and Estrogen/Progestin Replacement Study (HERS)
Bibliographic record
Abstract
BACKGROUND: Although effects of statins on cardiovascular outcomes are well established in men, fewer data exist for women. Furthermore, the effects of statins plus hormone replacement therapy (HRT) on cardiovascular outcomes are uncertain. METHODS AND RESULTS: We examined statin use, cardiovascular events, and total mortality in the Heart and Estrogen/progestin Replacement Study (HERS), a randomized clinical trial of estrogen plus progestin versus placebo in postmenopausal women with heart disease (n=2763). A nonrandomized comparison of statin users and nonusers revealed lower rates of the primary outcome, nonfatal myocardial infarction or coronary heart disease death (relative hazard [RH]=0.79, 95% confidence intervals [CI] 0.63 to 0.99, P=0.04), and total mortality (RH=0.67, 95% CI 0.51 to 0.87, P=0.003). Rates of venous thromboembolic events were also lower among statin users (RH=0.45, 95% CI 0.23 to 0.88, P=0.02). HRT resulted in a significant increase in early risk for primary events in women who did not use statins (RH=1.75, 95% CI 1.02 to 3.03, P=0.04) but not in statin users (RH=1.34, 95% CI 0.63 to 2.86, P=0.45). Adjustment for postrandomization statin use showed no effect of HRT on risk for the primary outcome (RH=0.96, 95% CI 0.77 to 1.29; P=0.72). CONCLUSIONS: In HERS, statin use was associated with lower rates of cardiovascular events, venous thromboembolic events, and total mortality. These data provide strong support for statin use in eligible women with coronary disease.
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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 | 0.003 |
| 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".