127 Coronary Artery Bypass Grafting Versus Percutaneous Coronary Intervention in Heart Failure with Reduced Ejection Fraction Patients: A Systematic Review and Meta-Analysis Stratified by Left Ventricular Ejection Fraction
Bibliographic record
Abstract
Abstract Aim The primary objectives were to assess differences in mortality, repeat revascularization, new postoperative myocardial infarction (MI), and cerebrovascular accidents (CVA/stroke) between PCI and CABG in HFrEF patients, stratified by the degree of LVEF reduction. Method A comprehensive search of electronic databases was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria comprised clinical trials or observational cohort studies with ≥20 patients per group, comparing long-term outcomes in HFrEF patients (LVEF <50%) who underwent PCI or CABG. Data was extracted, and quality was assessed using the New Castle Ottawa (NOS) Risk of Bias tool. Hazard ratios (HRs) were pooled for time-to-event outcomes, with subgroup analysis based on LVEF. Heterogeneity was assessed, sensitivity analysis conducted, and publication bias evaluated. Results Twenty studies involving 25,031 patients met the inclusion criteria. In the severe LVEF reduction group (<35%), CABG was associated with significantly higher long-term survival, reduced repeat revascularization, and fewer postoperative MIs compared to PCI. In patients with moderate LVEF reduction (<40%), there was no difference in long-term survival, but repeat revascularization was lower in the CABG group . In the mild LVEF reduction group (<50%), CABG was associated with superior long-term survival and reduced repeat revascularization. Stroke rates were similar between PCI and CABG in all groups. Conclusions Individualized patient care should consider the degree of LVEF reduction when selecting between PCI and CABG, with CABG generally favored for improved outcomes in HFrEF patients. However, clinical presentation, patient characteristics, and cost-effectiveness should also be considered in the decision-making process.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".