Investigation of an interaction between statins and clopidogrel after percutaneous coronary intervention: a cohort study
Bibliographic record
Abstract
BACKGROUND: Clopidogrel is an antiplatelet drug that is prescribed after percutaneous coronary intervention (PCI) to prevent stent thrombosis. Previous studies have suggested that some statins may inhibit the antiplatelet effects of clopidogrel via competitive metabolism of its activating enzyme cytochrome P450 3A4 (CYP3A4). OBJECTIVES: To investigate a possible interaction between statins and clopidogrel after a PCI procedure in a population-based cohort study. METHODS: A population-based cohort study was carried out between January 2001 and December 2004 using the health insurance databases from Quebec, Canada. The primary endpoint was a composite of death from any cause, myocardial infarction (MI), unstable angina, repeat revascularization and cerebrovascular events. PCI patients >or= 66 years of age were followed from their initial post-discharge clopidogrel prescription until the earliest of study endpoint occurrence, end of clopidogrel exposure or end of study (90 days post discharge). Time-dependent Cox regression analysis was performed. RESULTS: We identified 10491 patients who were prescribed clopidogrel post-PCI and 43.5% were also prescribed statins at the baseline discharge. During 1793 patient years of follow-up, 623 composite endpoints were observed. Compared to the reference group (non-CYP3A4-metabolized statins), the co-prescription of CYP3A4-metabolized statins (hazard ratio (HR) 1.16, 95% confidence interval (CI) 0.91-1.47), or no statin use (HR 1.22, 95%CI 0.93-1.59) were not statistically associated with an increase in adverse outcomes. CONCLUSIONS: In this PCI cohort, the association of clopidogrel with CYP3A4-metabolized statins did not demonstrate an increased early risk of adverse cardiovascular events, although a small risk could not be completely excluded.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".