Influence of Previous Coronary Artery Bypass Grafting on Clinical Outcomes After Percutaneous Coronary Intervention: A Meta-Analysis of 250 684 Patients
Bibliographic record
Abstract
Background: Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is the preferred strategy for treating obstructive coronary artery disease. Existing literature suggests the worsening of clinical outcomes in patients with previous coronary artery bypass grafting (CABG) history. In light of this, a comprehensive systematic review and meta-analysis was performed. Methods: Databases including PubMed, Cochrane Library, and ScienceDirect were utilized for the inclusive systematic search dating from inception to September 01, 2023. The risk of bias assessment was performed using the Newcastle-Ottawa scale for cohort studies, and the Cochrane Risk of Bias Tool for randomized controlled trials. Results: Ultimately, there were 16 eligible studies pooled together, involving a total of 250 684 patients, including 231 552 CABG-naïve patients, and 19 132 patients with a prior history of CABG. Overall, patients with CABG history were associated with significantly greater short-term mortality ( P = .004), long-term mortality ( P = .005), myocardial infarction ( P < .00001), major adverse cardiovascular events ( P = .0001), and procedural perforation ( P < .00001). Contrastingly, CABG-naïve patients were associated with significantly greater risk of cardiac tamponade ( P = .02) and repeat CABG ( P = .03). No significant differences in stroke, bleeding, revascularization, or repeat PCI were observed. Conclusion: Comparatively worsened clinical outcomes were observed, as patients with prior CABG history typically exhibit complex coronary anatomy, and have higher rates of comorbidities in comparison to their CABG-naïve counterparts. The refinement of current procedural and surgical techniques, in conjunction with continued research endeavors, are needed in order to effectively address this trend.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.045 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".