Stent thrombosis in the setting of ST-segment elevation acute myocardial infarction in the contemporary practice: results from the TOTAL randomized trial
Bibliographic record
Abstract
The aim was to know the risk and predictive factors of stent thrombosis (ST) in patients with ST-elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI) in the contemporary practice. The TOTAL [ThrOmbecTomy with percutaneous coronary intervention (PCI) versus PCI ALone] randomized trial, being the largest trial performed in the setting of STEMI with a general application of the recent recommendations, represents a unique opportunity to know the current real-world incidence of ST as well as its associated factors. A total of 10 064 patients that received ≥1 coronary stent in the TOTAL trial comprise the study population. The risk, predictive factors, and clinical implications of ST was studied. During 1-year follow-up, 155 patients (1.54%) suffered definitive or probable ST (59 acute, 67 subacute, and 29 late). Previous infarction, the number of stents, the previous use of clopidogrel, and the use of diuretics at discharge were independent predictors for ST, whereas the use of upfront glycoprotein IIb/IIIa inhibitors, radial access, and treatment with statins at discharge were independent protective factors. The number of stents, stent diameter, upfront treatment with IIb/IIIa inhibitors, previous treatment with clopidogrel, and treatment with statins at discharge were independently associated with the risk of early ST. Only previous infarction was associated with the risk of late ST. In the contemporary practice, ST still constitutes a frequent complication of primary PCI for STEMI, occurring in 1.5% of patients. Independent predictors are different depending on the time of 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".