Efficacy and Safety of Glycoprotein IIb/IIIa Inhibitors on Top of Ticagrelor in STEMI: A Subanalysis of the ATLANTIC Trial
Bibliographic record
Abstract
Abstract Background Glycoprotein IIb/IIIa inhibitors (GPIs) in combination with clopidogrel improve clinical outcome in ST-elevation myocardial infarction (STEMI); however, finding a balance that minimizes both thrombotic and bleeding risk remains fundamental. The efficacy and safety of GPI in addition to ticagrelor, a more potent P2Y12-inhibitor, have not been fully investigated. Methods 1,630 STEMI patients who underwent primary percutaneous coronary intervention (PCI) were analyzed in this subanalysis of the ATLANTIC trial. Patients were divided in three groups: no GPI, GPI administration routinely before primary PCI, and GPI administration in bailout situations. The primary efficacy outcome was a composite of death, myocardial infarction, urgent target revascularization, and definite stent thrombosis at 30 days. The safety outcome was non-coronary artery bypass graft (CABG)-related PLATO major bleeding at 30 days. Results Compared with no GPI (n = 930), routine GPI (n = 525) or bailout GPI (n = 175) was not associated with an improved primary efficacy outcome (4.2% no GPI vs. 4.0% routine GPI vs. 6.9% bailout GPI; p = 0.58). After multivariate analysis, the use of GPI in bailout situations was associated with a higher incidence of non-CABG-related bleeding compared with no GPI (odds ratio [OR] 2.96, 95% confidence interval [CI] 1.32–6.64; p = 0.03). However, routine GPI use compared with no GPI was not associated with a significant increase in bleeding (OR 1.78, 95% CI 0.88–3.61; p = 0.92). Conclusion Use of GPIs in addition to ticagrelor in STEMI patients was not associated with an improvement in 30-day ischemic outcome. A significant increase in 30-day non-CABG-related PLATO major bleeding was seen in patients who received GPIs in a bailout situation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".