Sex differences in outcomes after coronary artery bypass grafting: a pooled analysis of individual patient data
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Data suggest that women have worse outcomes than men after coronary artery bypass grafting (CABG), but results have been inconsistent across studies. Due to the large differences in baseline characteristics between sexes, suboptimal risk adjustment due to low-quality data may be the reason for the observed differences. To overcome this limitation, we undertook a systematic review and pooled analysis of high-quality individual patient data from large CABG trials to compare the adjusted outcomes of women and men. METHODS AND RESULTS: The primary outcome was a composite of all-cause mortality, myocardial infarction (MI), stroke, and repeat revascularization (major adverse cardiac and cerebrovascular events, MACCE). The secondary outcome was all-cause mortality. Multivariable mixed-effect Cox regression was used. Four trials involving 13 193 patients (10 479 males; 2714 females) were included. Over 5 years of follow-up, women had a significantly higher risk of MACCE [adjusted hazard ratio (HR) 1.12, 95% confidence interval (CI) 1.04-1.21; P = 0.004] but similar mortality (adjusted HR 1.03, 95% CI 0.94-1.14; P = 0.51) compared to men. Women had higher incidence of MI (adjusted HR 1.30, 95% CI 1.11-1.52) and repeat revascularization (adjusted HR 1.22, 95% CI 1.04-1.43) but not stroke (adjusted HR 1.17, 95% CI 0.90-1.52). The difference in MACCE between sexes was not significant in patients 75 years and older. The use of off-pump surgery and multiple arterial grafting did not modify the difference between sexes. CONCLUSIONS: Women have worse outcomes than men in the first 5 years after CABG. This difference is not significant in patients aged over 75 years and is not affected by the surgical technique.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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