Percutaneous coronary revascularization versus medical therapy in chronic coronary syndromes: An updated meta‐analysis of randomized controlled trials
Bibliographic record
Abstract
INTRODUCTION: Coronary artery disease (CAD) is a main cause of morbidity and mortality. The effectiveness of coronary revascularization in chronic coronary syndromes (CCS) is still debated. Our recent study showed the superiority of coronary revascularization over optimal medical therapy (OMT) in reducing cardiovascular (CV) mortality and myocardial infarction (MI). The recent publication of the ORBITA-2 trial suggested superiority of percutaneous coronary revascularization (PCI) in reducing angina and improving quality of life. Therefore, we aimed to provide an updated meta-analysis evaluating the impact of PCI on both clinical outcomes and angina in CCS. METHODS: Relevant studies were screened in PubMed/Medline until 08/01/2024. Randomized controlled trials (RCTs) comparing PCI to OMT in CCS were selected. The primary outcome was CV death. Secondary outcomes were MI, all-cause mortality, stroke, major bleeding and angina severity. RESULTS: Nineteen RCTs involving 8616 patients were included. Median follow-up duration was 3.3 years. Revascularization significantly reduced CV death (4.2% vs. 5.5%; OR = .77; 95% CI .62-.96, p = .02). Subgroup analyses favoured revascularization in patients without chronic total occlusions (CTOs) (p = .052) and those aged <65 years (p = .02). Finally, a follow-up duration beyond 3 years showed increased benefit of coronary revascularization (p = .04). Secondary outcomes analyses showed no significant differences, except for a lower angina severity in the revascularization group according to the Seattle Angina Questionnaire (SAQ) (p = .04) and to the Canadian Cardiovascular Society (CCS) classification (p = .005). CONCLUSIONS: PCI compared to OMT significantly reduces CV mortality and angina severity, improving quality of life in CCS patients. This benefit was larger without CTOs, in patients aged <65 years and with follow-up duration beyond 3 years.
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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 | 0.022 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.035 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".