Clopidogrel and Proton Pump Inhibitors: A New Drug Interaction?
Bibliographic record
Abstract
C lopidogrel is a thienopyridine platelet antagonist that irreversibly inhibits the binding of adenosine diphosphate to platelet receptors, ultimately leading to inhibition of platelet aggregation.1 Clopidogel is a prodrug requiring hepatic bioactivation via cytochrome P450 isozymes (CYP2C19, CYP3A4, CYP3A5) to its pharmacologically active form.Inhibition of cytochrome P450 may interfere with metabolic activation of clopidogrel, reducing its antiplatelet activity and potentially increasing the risk of thrombosis.More recently, the cytochrome P450 2C19 pathway has been identified as the key pathway in clopidogrel bioactivation. 2 Medications and, more recently, genetic mutations have been shown to affect the activity of the cytochrome P450 2C19 pathway.3 Proton pump inhibitors (PPIs), commonly used for prophylaxis and treatment of gastrointestinal bleeding, have been shown to inhibit the cytochrome P450 2C19 pathway to various degrees.4 Thus, it is biologically plausible that use of a PPI could impair the metabolic activation of clopidogrel through inhibition of this pathway.Recent clinical studies have illustrated the potential metabolic interaction between PPIs and clopidogrel, which could result in inhibition of the antiplatelet activity of clopidogrel.The clinical significance of these studies is reviewed below. METHODSPubMed and MEDLINE were searched for the period January 1990 to July 2009 using the terms "clopidogrel", "thienopyridine", "proton pump inhibitor", "drug interaction", "lansoprazole", "omeprazole", "pantoprazole", "esomeprazole", and "rabeprazole".Review articles, letters, commentaries, and unpublished abstracts were excluded.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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".