Sex‐related differences in outcomes after coronary artery bypass surgery—A patient‐level pooled analysis of randomized controlled trials: rationale and study protocol
Bibliographic record
Abstract
INTRODUCTION: The impact of sex on the outcomes after coronary artery bypass grafting (CABG) is controversial. The majority of CABG studies are retrospectively collected clinical or registry data, women comprise only a minority, and the reported findings represent the male predominated cohort. This individual patient meta-analysis is aimed at evaluating sex-related differences in outcomes after CABG using high quality data from randomized controlled trials (RCTs). METHODS AND ANALYSIS: A systematic literature search will be performed to identify all CABG RCTs (minimum follow-up: 5 years). Detailed specification for the minimum deidentified patient records' data requirements will be provided to RCT primary contact to request their deidentified data for pooling. The pooled analysis will follow the prospective register of systematic reviews (PROSPERO) and the preferred reporting items for systematic reviews and meta-analyses for individual patient data systematic reviews (PRISMA-IPD) recommendations and will compare sex-related outcomes after CABG. The main hypothesis is that outcomes after CABG are worse in women than in men. We will also test whether treatment effects for off-pump and the use of multiple arterial grafts are present within each sex, and also, whether there are differential treatment effects between sexes. The primary endpoint will be a composite of all-cause mortality, myocardial infarction, stroke, and repeat revascularization at long-term follow up. ETHICS AND DISSEMINATION: Ethics approval and participant consent for the study will be obtained locally by each study team if needed. Data will be disseminated and submitted to peer-reviewed scientific journals and meetings irrespective of study outcome.
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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 | 0.176 | 0.237 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.015 | 0.021 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.043 | 0.010 |
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".