The potential interaction between clopidogrel and proton pump inhibitors: a systematic review
Bibliographic record
Abstract
BACKGROUND: Recently, several publications have investigated a possible drug interaction between clopidogrel and proton pump inhibitors (PPIs), and regulatory agencies have issued warnings despite discordant study results. In an attempt to clarify the situation, we performed a systematic review with a critical analysis of study methodologies to determine whether varying study quality (that is, bias) could explain the discordant results. METHODS: A systematic review of all studies reporting clinical outcomes was performed using an electronic literature search of the MEDLINE and EMBASE databases, abstracts from the major cardiology conferences and a hand-search of bibliographies from identified articles. Each study was evaluated for its risk of bias according to a prespecified quality measure scale. RESULTS: A total of 18 studies were identified. Ten of 13 studies judged to be of low scientific quality reported a statistically positive interaction between clopidogrel and the general class of PPIs, and each concluded this was likely a clinically meaningful effect. None of the five studies judged to be of moderate or high quality reported a statistically significant association. Multiple sources of heterogeneity (that is, different populations, outcomes assessed, drug exposure methods and study quality) prevented a formal quantitative analysis of all studies. An increased risk of bias was observed in the positive studies, resulting in an inverse correlation between study quality and a reported statistically positive interaction (10/13 versus 0/5; P = p = 0.007). There was also no clinical evidence for a positive interaction according to specific PPIs. CONCLUSION: The observed association between clopidogrel and PPIs is found uniquely in studies judged to be of low quality and with an increased risk of bias. High-quality evidence supporting a clinically significant clopidogrel/PPI interaction is presently lacking.
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 | 0.022 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".