Meta-Analysis of Complete versus Culprit-Only Revascularization in Patients with ST-Segment Elevation Myocardial Infarction and Multivessel Coronary Disease
Bibliographic record
Abstract
Approximately half of patients with ST-segment elevation myocardial infarction (STEMI) present with noninfarct related multivessel coronary artery disease (CAD) during primary percutaneous coronary intervention (PCI). However, questions remain concerning whether patients with STEMI and multivessel CAD should routinely undergo complete revascularization. Our objective was 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. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing complete revascularization to culprit-only PCI. RCTs were identified via a systematic search of MEDLINE, Embase, and Cochrane CENTRAL. Count data were pooled using DerSimonian and Laird random-effects models with inverse variance weighting to obtain relative risks (RRs) and 95% confidence intervals (CIs). A total of 9 RCTs (n = 6,751) were included, with mean/median follow-up times ranging from 6 to 36 months. Compared with culprit-only PCI, complete revascularization was associated with a substantial reduction in major adverse cardiovascular events (13.1% vs 22.1%; RR: 0.54; 95%CI: 0.43 to 0.66), repeat myocardial infarction (4.9% vs 6.8%; RR: 0.64; 95%CI: 0.48 to 0.84), and repeat revascularization (3.7% vs 12.3%; RR: 0.33; 95%CI: 0.25 to 0.44). Complete revascularization may have beneficial effects on all-cause and cardiovascular mortality, but 95%CIs were wide. Findings for stroke, major bleeding, and contrast-induced acute kidney injury were inconclusive. In conclusion, complete coronary artery 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.031 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".