A Clinical Trial of Estrogen-Replacement Therapy after Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Observational studies have suggested that estrogen-replacement therapy may reduce a woman's risk of stroke and death. METHODS: We conducted a randomized, double-blind, placebo-controlled trial of estrogen therapy (1 mg of estradiol-17beta per day) in 664 postmenopausal women (mean age, 71 years) who had recently had an ischemic stroke or transient ischemic attack. Women were recruited from 21 hospitals in the United States and were followed for the occurrence of stroke or death. RESULTS: During a mean follow-up period of 2.8 years, there were 99 strokes or deaths among the women in the estradiol group, and 93 among those in the placebo group (relative risk in the estradiol group, 1.1; 95 percent confidence interval, 0.8 to 1.4). Estrogen therapy did not reduce the risk of death alone (relative risk, 1.2; 95 percent confidence interval, 0.8 to 1.8) or the risk of nonfatal stroke (relative risk, 1.0; 95 percent confidence interval, 0.7 to 1.4). The women who were randomly assigned to receive estrogen therapy had a higher risk of fatal stroke (relative risk, 2.9; 95 percent confidence interval, 0.9 to 9.0), and their nonfatal strokes were associated with slightly worse neurologic and functional deficits. CONCLUSIONS: Estradiol does not reduce mortality orthe recurrence of stroke in postmenopausal women with cerebrovascular disease. This therapy should not be prescribed for the secondary prevention of cerebrovascular 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".