Five-Year Comparative Efficacy of Everolimus-Eluting vs. Resolute Zotarolimus-Eluting Stents in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention
Bibliographic record
Abstract
Among drug-eluting stents (DESs), the durable polymer everolimus-eluting stent (EES) and resolute zotarolimus-eluting stent (R-ZES) are widely used in clinical practice and have contributed to improve the outcomes of patients undergoing percutaneous coronary intervention (PCI). Few studies addressed their long-term comparative performance in patients with acute coronary syndrome (ACS). We aimed to investigate the 5 year comparative efficacy of EES and R-ZES in ACS. We queried ACTION-ACS, a large-scale database of ACS patients undergoing PCI. The treatment groups were analyzed using propensity score matching. The primary endpoint was a composite of mortality, myocardial infarction (MI), stroke, repeat PCI, and definite or probable stent thrombosis, which was addressed at the five-year follow-up. A total of 3497 matched patients were analyzed. Compared with R-ZES, a significant reduction in the primary endpoint at 5 years was observed in patients treated with EES (hazard ratio (HR) [95%CI] = 0.62 [0.54–0.71], p < 0.001). By landmark analysis, differences between the two devices emerged after the first year and were maintained thereafter. The individual endpoints of mortality (HR [95%CI] = 0.70 [0.58–0.84], p < 0.01), MI (HR [95%CI] = 0.55 [0.42–0.74], p < 0.001), and repeat PCI (HR [95%CI] = 0.65 [0.53–0.73], p < 0.001) were all significantly lower in the EES-treated patients. Stroke risk did not differ between EES and R-ZES. In ACS, a greater long-term clinical efficacy with EES vs. R-ZES was observed. This difference became significant after the first year of the ACS episode and persisted thereafter.
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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 | 0.004 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".