A population‐based study of the drug interaction between clopidogrel and angiotensin converting enzyme inhibitors
Bibliographic record
Abstract
AIMS: Clopidogrel and angiotensin converting enzyme (ACE) inhibitors are commonly co-prescribed drugs. Clopidogrel inhibits carboxylesterase 1 (CES1), the enzyme responsible for converting prodrug ACE inhibitors (such as ramipril and perindopril) to their active metabolites. The clinical implications of this potential drug interaction are unknown. The clinical consequences of the potential drug interaction between clopidogrel and prodrug ACE inhibitors were examined. METHODS: We conducted a nested case-control study of Ontarians aged 66 years and older treated with clopidogrel between September 1 2003 and March 31 2013 following acute myocardial infarction. Cases were subjects who died or were hospitalized for reinfarction or heart failure in the subsequent year, and each was matched with up to four controls. The primary outcome was a composite of reinfarction, heart failure or death. The primary analysis examined whether use of the prodrug ACE inhibitors ramipril or perindopril was more common among cases than use of lisinopril, an active ACE inhibitor. RESULTS: Among 45 918 patients treated with clopidogrel following myocardial infarction, we identified 4203 cases and 14 964 controls. After adjustment, we found no association between the composite outcome and use of perindopril (adjusted odds ratio (aOR) 0.94, 95% confidence interval (CI) 0.76, 1.16) or ramipril (aOR 0.97, 95% CI 0.80, 1.18), relative to lisinopril. Secondary analyses of each element of the composite outcome yielded similar findings. CONCLUSIONS: Following myocardial infarction, use of clopidogrel with ACE inhibitors activated by CES1 is not associated with an increased risk of adverse cardiovascular outcomes relative to lisinopril. These findings suggest that the recently described drug interaction between clopidogrel and prodrug ACE inhibitors is of little clinical relevance.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".