Incidence, predictors, and clinical outcomes of early stent thrombosis in acute myocardial infarction patients treated with primary percutaneous coronary angioplasty (insights from the <scp>U</scp>niversity of <scp>O</scp>ttawa <scp>H</scp>eart <scp>I</scp>nstitute STEMI registry)
Bibliographic record
Abstract
BACKGROUND: Early stent thrombosis (ST) remains an important complication of primary percutaneous intervention (PCI). To date, our information on angiographic and clinical predictors of early ST in ST-segment elevation myocardial infarction (STEMI) patients treated with primary PCI is limited. METHODS: We tried to evaluate the incidence, predictors, and outcomes of early ST in real-world patients treated with primary PCI. We identified all the patients presenting with STEMI between June 2004 and January 2011 who underwent primary PCI as the primary mode of revascularization. Diagnosis of ST was made as per the standard definition proposed by the Academic Research Consortium. RESULTS: The incidence of early ST was 1% among 2,303 patients treated with primary PCI. Definite and probable early ST occurred in 22 and 2 patients, respectively. Patients with early ST had higher in-hospital (P = 0.03) and 30-day mortality (P = 0.048). The rate of cardiogenic shock (P = 0.0006) and cerebrovascular accident (P = 0.0004) was also greater in the early ST group. Smaller stent diameter and lower use of intracoronary glycoprotein IIb/IIIa inhibitor were associated with higher rate of early ST. There was a trend of higher bivalirudin use in ST group, which did not reach significance (P = 0.07) On IVUS imaging, stent malapposition and uncovered plaque area were noted in 6 out of 11 cases. CONCLUSION: The incidence of early ST in primary PCI cohort is low. However, it is still associated with higher mortality and morbidity. Small stent diameter and disuse of intracoronary glycoprotein IIb/IIIa inhibitor may be associated with early ST.
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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 | 0.000 |
| 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".