In-Hospital Switching Between Clopidogrel and Prasugrel Among Patients With Acute Myocardial Infarction Treated With Percutaneous Coronary Intervention
Bibliographic record
Abstract
BACKGROUND: Although randomized clinical trials have compared clopidogrel with higher potency ADP receptor inhibitors (ADPris) among patients with myocardial infarction, little is known about the frequency and factors associated with switching between ADPris in clinical practice. METHODS AND RESULTS: We studied 47 040 patients with myocardial infarction treated with percutaneous coronary intervention, who received either clopidogrel or prasugrel within 24 hours of admission at 361 US hospitals from July 2009 to June 2011 using the merged Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With the Guidelines and CathPCI Registry database. Hierarchical logistic regression modeling was used to determine factors independently associated with in-hospital ADPri switching. Among 40 531 patients treated initially in-hospital with clopidogrel, 2125 (5.2%) were discharged on prasugrel; this frequency steadily increased from 0% to 7% during the study period. Among 6509 patients treated initially in-hospital with prasugrel, 751 (11.5%) were discharged on clopidogrel. The frequency of this switch increased from 6% to 18% during the first 2 quarters of the study period and decreased to 9% by the end. Switching clopidogrel to prasugrel was associated with high-risk angiographic characteristics (thrombotic, long, and bifurcating lesions), reinfarction in-hospital, and private health insurance coverage. Older age, previous cerebrovascular event, in-hospital coronary artery bypass grafting, in-hospital bleeding, and warfarin use at discharge were associated with switching prasugrel to clopidogrel. CONCLUSIONS: Clopidogrel and prasugrel are not uncommonly switched in-hospital in patients with myocardial infarction undergoing percutaneous coronary intervention. In contemporary US practice, in addition to risk for bleeding and recurrent ischemic events, medical drug coverage is a major determinant of ADPri selection.
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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 | 0.001 |
| 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".