Representation of Women in Randomized Trials in Cardiac Surgery: A Meta‐Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Background Women have traditionally been underrepresented in randomized clinical trials (RCTs). We performed a systematic evaluation of the inclusion of women in cardiac surgery RCTs published in the past 2 decades. Methods and Results MEDLINE, EMBASE, and the Cochrane Library were searched (2000 to July 2020) for RCTs written in English, comparing ≥2 adult cardiac surgical procedures. The percentage of women enrolled and its association with year of publication, sample size, mean age, funding source, geographic location, number of sites involved, and interventions tested were analyzed using a meta‐analytic approach. Fifty‐one trials were included. Of 25 425 total patients, 5029 were women (20.8%; 95% CI, 17.6–24.4; range, 0.5%–57.9%). The proportion of women dropped significantly during the study period (29.6% in 2000 versus 13.1% in 2019, P <0.001). Women were significantly more represented in European trials (26.2%; 95% CI, 21.2–31.9), and less represented in trials of coronary bypass surgery versus other interventions (16.8%; 95% CI, 12.3–22.7 versus 33.6%; 95% CI, 27.4–40.5; P =0.0002) and in trials enrolling younger patients ( P =0.009); the percentage of women was higher in industry‐sponsored versus non‐industry sponsored trials (31.7%; 95% CI, 27.2–36.6 versus 15.5%; 95% CI, 10.0–23.2; P =0.0004) and was not associated with trial sample size ( P =0.52) or study design (multicenter versus monocenter: P =0.22). After exclusion of trials conducted at Veteran Affairs centers, women representation was 24.4% (95% CI, 21.1–28.0; range, 10.4%–57.9%), with no significant changes during the study period. Conclusions The proportion of women in cardiac surgery trials is low and likely inadequate to provide meaningful estimates of the treatment effect.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.073 | 0.063 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.059 | 0.047 |
| Bibliometrics | 0.001 | 0.004 |
| 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 it