Comprehensive Review of Complete Versus Culprit-only Revascularization for Multivessel Disease in ST-segment Elevation Myocardial Infarction
Bibliographic record
Abstract
Several organizations have developed guidelines for the management of ST-segment elevation myocardial infarction (STEMI). However, the optimal strategy regarding revascularization in the setting of multivessel disease, specifically with regards to culprit vessel versus complete revascularization, continues to evolve. While previous observational studies promoted culprit vessel-only intervention in patients with STEMI, recent randomized controlled trials suggest potential benefits with multivessel revascularization, either at the time of the index event or in a staged fashion, in patients without cardiogenic shock. This may be due to the known instability of non-culprit lesions in the setting of acute coronary syndrome, and the diffuse coronary processes involved. As additional literature examines culprit vessel versus multivessel revascularization strategies, clinicians continue to be tasked with determining optimal treatment plans for their patients and understanding the factors that promote selected revascularization strategies. This review summarizes and discusses observational studies, randomized control trials and current guidelines in order to evaluate optimal reperfusion strategies for patients presenting with STEMI in the setting of multivessel disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".