Higher mortality in women undergoing coronary artery bypass grafting
Bibliographic record
Abstract
Purpose: Until recently, men have had higher rates of cardiovascular disease than women. Most studies report women having higher mortality after cardiac surgery, reasons to which are unclear. We compared characteristics and outcomes of coronary artery bypass grafting (CABG) by sex at our centre. Methods: All patients undergoing isolated CABG during July 2010-June 2012 were grouped by sex, and retrospective comparative analyses performed. Results: A total of 650 (79.4%) men and 168 (20.5%) women having isolated CABG were included, with mean follow-up of 1.4±0.6 years. Women were associated with increased age (66.4 vs 64.0 years, p=0.007), body mass index (30.1 vs 28.8 kg/m2, p=0.004), higher Canadian Cardiovascular Society angina class (2.8 vs 2.6 p=0.037), increased prevalence of hypertension (78.9% vs 67.8%, p=0.008), current smokers (20.2% vs 13.1%, p=0.027), chronic respiratory disease (22.6% vs 15.4%, p=0.028), impaired renal function (74 vs 81mL/min, p=0.007) and higher logistic EuroSCORE 1 (6.6% vs 4.0%, p<0.001). Women also had less vessels grafted (3.1 vs 3.3, p=0.014) and less use of radial grafts (14.9% vs 25.2%, p=0.004) during the operation. Women were independent associated with higher 30-day mortality odds ratio 5.63, 95% confidence interval 1.67-19.0, p=0.005 (4.8% vs 0.8%) and medium-term mortality hazards ratio 2.49, 1.06-5.84, p=0.037 (1-year survival 93.9% vs 98.1%); but not composite morbidity (21.4% vs 16.9%, p=0.661). Conclusion: Women were older and had higher prevalence of cardiovascular risk factors and co-morbidities, but even upon adjusting for these variables, they were independently associated with higher 30-day and medium-term mortality after CABG.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".