Upstream anticoagulation for patients with ST‐elevation myocardial infarction undergoing primary percutaneous coronary intervention: Insights from the TOTAL trial
Bibliographic record
Abstract
OBJECTIVES: To assess the relationship between preprocedural anticoagulation use and clinical and angiographic outcomes. BACKGROUND: For patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI), the optimal timing of anticoagulant administration remains uncertain. METHODS: Patients enrolled in the TOTAL trial were stratified based on whether or not they had received any parenteral anticoagulant prior to randomization and PCI. Baseline and procedural characteristics were compared. For one-year clinical outcomes, Cox proportional modeling adjusted on a propensity score was used to analyze differences between groups. Angiographic endpoints were analyzed by logistic regression models adjusted for propensity scores. RESULTS: In the trial, 10,064 patients were enrolled and underwent PCI. Preprocedural anticoagulation was used in 6,381 patients (63%).The most common anticoagulant was intravenous unfractionated heparin (5,188, 81%). Patients who received preprocedural anticoagulation had higher rates of TIMI-2-3 or TIMI-3 flow and lower grades of thrombus prior to PCI. Pretreatment with anticoagulation was associated with lower use of bailout thrombectomy, GP IIb/IIIa inhibitors, and intra-aortic balloon pump. After adjustment, preprocedural anticoagulation was associated with lower rates of CABG and minor bleeding at 1 year but there were no significant differences in death, stroke, recurrent MI, cardiogenic shock, or congestive heart failure. CONCLUSIONS: Preprocedural anticoagulation is associated with improved flow and reduced thrombus in the IRA prior to PCI, less bailout thrombectomy during PCI but no difference in death, recurrent infarction, or heart failure at 1 year.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".