Postmenopausal Hormone Use in Women with Acute Coronary Syndromes
Bibliographic record
Abstract
BACKGROUND: Recent trials reveal no benefit and possible harm from chronic hormone replacement therapy (HRT). Less is known about intermediate-term outcomes associated with HRT use in the setting of acute coronary syndromes (ACS). METHODS: To examine the prevalence of HRT use and relationships with intermediate-term outcomes among women with ACS, we classified as HRT users or nonusers 4029 postmenopausal women (age > 50 years or postmenopausal by case report form) randomized in the Sibrafiban versus Aspirin to Yield Maximum Protection from Ischemic Heart Events Post-Acute Coronary Syndromes (SYMPHONY) and 2nd SYMPHONY trials. Outcomes included 90-day and 1-year death and 90-day stroke, death, or myocardial infarction (MI); death, MI, or stroke; and death, MI, or severe recurrent ischemia (SRI). RESULTS: HRT use was 13% overall and varied by region (Asia, 0%; Eastern Europe, 0.2%; Latin America, 0.8%; Western Europe, 4%; Australia/New Zealand, 12%; Canada, 14%; United States, 24%); estrogen-only regimens were most common (90%). HRT users were younger, had higher estimated creatinine clearance, more frequently were smokers and had prior revascularization, but less frequently had diabetes, prior angina, or heart failure. Unadjusted 90-day and 1-year mortality rates were lower among HRT users (hazard ratios [95% CI] 0.48 [0.23-0.98] and 0.35 [0.18-0.68], respectively) but after multivariable adjustment, were not significantly different. Ninety-day stroke and composite end points did not differ between HRT users and nonusers. CONCLUSIONS: HRT use (predominantly estrogen-only) was low among patients with ACS but varied by region and was not associated with improved intermediate-term outcomes. These results are consistent with the absence of benefit from HRT use (combination or estrogen only) in previous studies in more stable populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".