A population-based study of the drug interaction between proton pump inhibitors and clopidogrel
Bibliographic record
Abstract
BACKGROUND: Most proton pump inhibitors inhibit the bioactivation of clopidogrel to its active metabolite. The clinical significance of this drug interaction is unknown. METHODS: We conducted a population-based nested case-control study among patients aged 66 years or older who commenced clopidogrel between Apr. 1, 2002, and Dec. 31, 2007, following hospital discharge after treatment of acute myocardial infarction. The cases in our study were those readmitted with acute myocardial infarction within 90 days after discharge. We performed a secondary analysis considering events within 1 year. Event-free controls (at a ratio of 3:1) were matched to cases on age, percutaneous coronary intervention and a validated risk score. We categorized exposure to proton pump inhibitors before the index date as current (within 30 days), previous (31-90 days) or remote (91-180 days). RESULTS: Among 13 636 patients prescribed clopidogrel following acute myocardial infarction, we identified 734 cases readmitted with myocardial infarction and 2057 controls. After extensive multivariable adjustment, current use of proton pump inhibitors was associated with an increased risk of reinfarction (adjusted odds ratio [OR] 1.27, 95% confidence interval [CI] 1.03-1.57). We found no association with more distant exposure to proton pump inhibitors or in multiple sensitivity analyses. In a stratified analysis, pantoprazole, which does not inhibit cytochrome P450 2C19, had no association with readmission for myocardial infarction (adjusted OR 1.02, 95% CI 0.70-1.47). INTERPRETATION: Among patients receiving clopidogrel following acute myocardial infarction, concomitant therapy with proton pump inhibitors other than pantoprazole was associated with a loss of the beneficial effects of clopidogrel and an increased risk of reinfarction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".