Ticagrelor or clopidogrel dual antiplatelet therapy following a pharmacoinvasive strategy in <scp>ST</scp>‐segment elevation myocardial infarction
Bibliographic record
Abstract
OBJECTIVES: To describe and evaluate outcomes in STEMI patients sustained on clopidogrel compared to those switched to ticagrelor following fibrinolysis. BACKGROUND: World-wide, many STEMI patients cannot achieve timely PCI and therefore require fibrinolysis. Although comparable 30-day and 1-year safety was shown with clopidogrel or ticagrelor in the TREAT study, there is paucity of long-term outcomes in pharmacoinvasive treated STEMI. METHODS: We conducted an observational cohort study evaluating consecutive pharmacoinvasive STEMI patients treated in a network, comparing those switched to ticagrelor to those sustained on clopidogrel. The primary efficacy composite was one-year all-cause death, recurrent myocardial infarction, and stroke with major bleeding and intracranial hemorrhage (ICH) as the safety outcomes. Multivariable Cox regression model was used to examine the association between P2Y12 inhibitor and outcomes with inverse probability weighting. RESULTS: Of 1426 pharmacoinvasive STEMI patients, 28% (n = 396) were converted to ticagrelor at a mean of 9.9 h after fibrinolysis with comparable GRACE Risk Scores (median; 158 vs 157, p0.352). The primary composite occurred in 3.5% of ticagrelor and 7.0% of clopidogrel treated patients (p0.014). Following adjustment, ticagrelor was associated with a 54% lower composite outcome (adjusted HR 0.46, 95% confidence interval 0.26-0.84). Major bleeding 6.3% vs 6.1% (NS) and ICH 0.0% vs 0.2% (NS) were similar. CONCLUSIONS: In a prospective STEMI cohort, switching to ticagrelor compared with sustaining clopidogrel following fibrinolysis pharmacoinvasive reperfusion reduced recurrent ischemic events at 1-year with no differences in major bleeding or ICH. Aligned with randomized data, these findings provide support to switch pharmaco-invasively treated STEMI patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".