Complete versus culprit-only PCI in patients with STEMI and multivessel disease: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Abstract Background Approximately half of patients with ST-segment elevation myocardial infarction (STEMI) present with multivessel coronary artery disease (CAD) during primary percutaneous coronary intervention (PCI). Purpose To compare the risks of major cardiovascular outcomes and procedural complications in patients with STEMI and multivessel CAD randomized to complete revascularization versus culprit-only PCI. Methods We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing complete to culprit-only PCI, identified via a systematic search of MEDLINE, Embase, and the Cochrane Libraries. Count data were pooled using DerSimonian and Laird random-effects models with inverse variance weighting to obtain relative risks (RRs) and corresponding 95% confidence intervals (CIs). Results A total of 8 RCTs (n=6,632) were included, with mean/median follow-up times ranging from 6 to 36 months. Compared to culprit-only PCI, complete PCI was associated with a substantial reduction in MACE (12.6% vs. 22.0%), repeat myocardial infarction (4.5% vs. 6.9%), and repeat revascularization (3.3% vs. 12.1%) (Table 1). Complete PCI may also improve all-cause and cardiovascular mortality, but estimates were accompanied by wide 95% CIs. Findings for stroke, major bleeding, and contrast-induced AKI were inconclusive. Conclusion Complete revascularization appears to confer benefit over culprit-only PCI in patients with STEMI and multivessel CAD, and should be considered a first-line strategy in these patients. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Mr. Levett is supported by a Dr. Clarke K. McLeod Memorial Scholarship, funded through the McGill University Faculty of Medicine Research Bursary Program. Dr. Filion is supported by a Junior 2 Research Scholar award from the Fonds de recherche du Québec – Santé and a William Dawson Scholar award from McGill University.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.034 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".