Direct Stenting Versus Pre‐Dilation in ST‐Elevation Myocardial Infarction: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVES: This study aimed at comparing direct stenting (DS) versus stenting with pre-dilation (SP) in patients with ST-elevation myocardial infarction (STEMI), using a systematic review and meta-analysis of published evidence. BACKGROUND: There is conflicting evidence whether stenting strategy impacts clinical outcomes in patients with STEMI. METHODS: We searched EMBASE, MEDLINE, and CENTRAL, from inception to December 2014. The primary endpoint was mortality. Secondary endpoints included major adverse cardiac events (MACEs), ST-segment resolution, and angiographic outcomes. RESULTS: A total of 9,331 patients enrolled in 12 studies (3 randomized controlled trials, RCTs; 9 non-randomized studies, NRSs) were included. DS was associated with lower mortality (OR 0.55; 95%CI: 0.33-0.94; P = 0.03) in NRSs, and overall (OR 0.56; 95%CI: 0.37-0.86; P = 0.008). Mortality was non-significantly reduced in RCTs (OR 0.56; 95%CI: 0.26-1.23; P = 0.15). DS was also associated with lower MACE rate (OR 0.71; 95%CI 0.60-0.84; P < 0.0001) in NRSs, but not in RCTs (OR 0.99; 95%CI: 0.61-1.60; P = 0.96). ST-segment resolution, no reflow, final thrombolysis in myocardial infarction (TIMI) flow and final TIMI myocardial perfusion or blush grade were significantly better with DS in NRSs, and non-significantly better in RCTs. CONCLUSIONS: The available evidence suggests that DS in STEMI might be associated with better clinical and procedural outcomes, as compared with SP. However, the fact that RCTs account for the minority of available data and that most of the available studies poorly reflect current clinical practice, as well as the existence of publication bias, preclude drawing definitive conclusions.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".