Sex-Stratified Trends in Enrollment, Patient Characteristics, Treatment, and Outcomes Among Non–ST-Segment Elevation Acute Coronary Syndrome Patients
Bibliographic record
Abstract
BACKGROUND: Adequate representation by sex in trials allows generalizability of results. We examined representation of women in clinical trials during a 17-year period in which inclusion criteria were broadened and federal mandates for representativeness were launched. METHODS AND RESULTS: Using mixed models, we studied sex-stratified temporal trends in enrollment, clinical characteristics, treatment, and outcomes among 76 148 non-ST-segment elevation acute coronary syndrome patients using patient-level data merged from 11 phase III trials conducted from 1994 to 2010. Overall, 33.3% of patients were women, which changed minimally over time. Women were consistently 4 to 5 years older than men (median age 68 [interquartile range 61-75] versus 64 [interquartile range 56-72] years) and more frequently had diabetes mellitus, hypertension, and heart failure; men more frequently had prior myocardial infarction and revascularization. GRACE risk scores increased over time for both sexes with the inclusion of older patients with more comorbidities. Use of percutaneous coronary intervention, in-hospital and discharge angiotensin-converting enzyme inhibitor/angiotensin II receptor blockers, β-blockers, and lipid-lowering drugs also increased among both sexes. Kaplan-Meier estimates of 6-month mortality declined from 7.0% [95% confidence interval 6.5%-7.6%] to 4.5% [95% confidence interval 4.0%-5.0%] among women and 6.3% [95% confidence interval 6.0%-6.7%] to 3.1% [95% confidence interval 2.9%-3.4%] among men during the 17-year period. CONCLUSIONS: The relative proportion of women in non-ST-segment elevation acute coronary syndrome trials changed minimally over time. Nevertheless, in parallel with men, use of evidence-based care and outcomes improved significantly over time among women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".