Conservative vs. Liberal Glycoprotein IIb-IIIa Antagonist Strategies in the Treatment of ST-Elevation Myocardial Infarction: A Dual-Center Analysis
Bibliographic record
Abstract
Abstract Background While the efficacy of GpIIb-IIIa-inhibitors during primary PCI (pPCI) for ST-elevated myocardial infarction (STEMI) has previously been demonstrated, its ongoing role and safety in combination with newer P2Y12-inhibitors is unclear. We therefore sought to compare outcomes between two centers with divergent approaches to the use of GpIIbIIIa antagonists in pPCI. Methods We performed a retrospective chart review of all-comer STEMI patients treated with pPCI at two high-volume Montreal academic tertiary care centers. One center tended to use GpIIb-IIIa-inhibitors up-front in a large proportion of patients (liberal strategy) and the other preferring a bail-out approach (conservative strategy). Baseline patient characteristics and procedural data were compared between the two groups. The main efficacy outcome was rate of no-reflow/slow-reflow and the main safety outcome was BARC ³ 2 bleeding events. Results A total of 459 patients were included, of whom 167 (36.5%) were exposed to a GpIIb-IIIa-antagonist. There was a significant overall difference in use of GpIIb-IIIa-antagonist between the two centers (60.5% vs 16.1%, p<0.01) Rate of no-reflow/slow-reflow was similar between groups (2.6% vs 1.4%, p=0.22). In-hospital rates of unplanned revascularization, stroke and death were aslo not different between groups. Use of a liberal GpIIb-IIIa-antagonist strategy was associated with a higher risk of bleeding (OR 3.16, p<0.01), which persisted after adjustment for covariables (adjusted OR 2.85, p<0.01). Conclusions In this contemporary retrospective cohort, a conservative GpIIb-IIIa-antagonist strategy was associated with a lower incidence of clinically relevant bleeding without any signal for an increase in no-reflow/slow-reflow or ischemic clinical events.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".