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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".