One‐Year Clinical Outcomes after Sirolimus‐Eluting Coronary Stent Implantation for Acute Myocardial Infarction in the Worldwide e‐SELECT Registry
Bibliographic record
Abstract
Background: The aim was to ascertain the 1‐year clinical outcomes of 1,234 patients who underwent implantations of sirolimus‐eluting stents (SES) for acute myocardial infarction (MI) in the multinational e‐SELECT registry. Methods: Fifteen thousand and one hundred and forty‐seven patients treated with SES were entered in the e‐SELECT registry, of whom 1,234 presented within <24 hours of onset of acute MI. Results: At 1 year, the rates of major adverse cardiac events (MACE) (5.5% vs. 4.8%; P = 0.28) were similarly low in the acute and no acute MI groups. The rates of definite/probable stent thrombosis (ST) were higher in the acute MI group (2.1%vs; 0.88%, P < 0.001). ST was a strong independent predictor of death at 1 year (HR 13.4; 95% CI 5.0, 36.0; P < 0.001) and MI (HR 58.9; 95% CI 26.9, 129.1; P < 0.001). Dual antiplatelet therapy (DAPT) compliance at 6 months was 96.0% in the acute MI versus 94.5% in the no acute MI group (P = 0.03). Conclusion: In selected patients presenting within <24 hours of acute MI onset and highly compliant with DAPT, SES implantation was associated with similar rates of MACE, though higher rates of ST, as compared to no acute MI patients. Condensed abstract In the e‐SELECT registry which included 15,147 patients treated with sirolimus‐eluting stent (SES), we ascertained the 1‐year clinical outcomes of 1,234 patients who presented within <24 hours of acute MI onset. In acute MI patients SES implantation was associated with similar rates of MACE, though higher rates of ST, as compared to no acute MI patients (MACE: 5.5% vs. 4.8%; P = 0.28; ST: 2.1 vs. 0.88%, P < 0.001). (J Interven Cardiol 2012;25:253–261)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".