Women with chronic coronary artery disease: long-term outcomes after percutaneous coronary intervention vs coronary artery bypass grafting
Bibliographic record
Abstract
BACKGROUND AND AIMS: Real-world evidence comparing percutaneous coronary intervention (PCI) to coronary artery bypass grafting (CABG) in women with chronic severe coronary artery disease (CAD) is limited. This study aimed to compare long-term outcomes of PCI and CABG in women with chronic severe CAD. METHODS: This propensity score-matched retrospective cohort study linked clinical and administrative databases in Ontario, Canada to identify women with chronic severe CAD undergoing PCI or CABG from 2012 to 2021. Major adverse cardiovascular and cerebrovascular events (MACCE), defined as a composite of all-cause mortality, myocardial infarction (MI), stroke, or repeat revascularization, as well as the individual components of MACCE and cardiovascular readmission (MI, heart failure [HF], or stroke), were evaluated using the Cox proportional hazards model. RESULTS: A total of 2469 and 3721 women underwent PCI and CABG, respectively. After propensity score matching, 2033 well-balanced pairs were identified. The mean (±SD) age of patients was 66.5 (±8.6) years. At a median follow-up of 5.1 (inter-quartile range: 2.9-7.5) years, MACCE was higher with PCI compared with CABG (hazard ratio [HR] 1.81, 95% confidence interval [CI]: 1.63-2.01], P < .001). All-cause mortality was higher with PCI compared with CABG (HR 1.34 [95% CI: 1.16-1.54], P < .001). Cardiovascular readmission (MI, HF, or stroke) was higher with PCI compared with CABG (HR 1.40 [95% CI: 1.32-1.49], P < .001). CONCLUSIONS: In women with chronic severe CAD, CABG appears to be associated with a long-term reduction in MACCE and all-cause mortality compared with PCI. These findings support consideration of CABG as the preferred revascularization strategy in appropriately selected women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".