Interaction of CYP2C19 G681A polymorphism and omeprazole on clopidogrel responsiveness and impact in patients with acute coronary syndrome
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to explore the individual effects of the CYP2C19 G681A polymorphism and omeprazole use and their interaction on clopidogrel responsiveness in acute coronary syndrome (ACS). The CYP2C19 G681A polymorphism and omeprazole use were both known for retarding the effects of clopidogrel under broad cardiovascular conditions; however, data from ACS patients were limited. METHODS: We conducted a cross-sectional study of 102 ACS patients who received clopidogrel before percutaneous coronary intervention. The platelet function was assessed by a Platelet Function Analyzer-200, in which clopidogrel hyporesponsiveness was defined as a closure time (CT) of ≤ 106 s. The CYP2C19 G681A polymorphism was investigated using the PCR-RFLP technique. Statistical analysis was performed by using χ test, Student's t-test, binary logistic regression, and receiver-operating characteristic (ROC) curve. RESULTS: Carriages of the CYP2C19 681A allele and omeprazole use were present in 47.1 and 37.3% patients, respectively. The mean CT ± SD was 103.1 ± 1.7 s and the prevalence of clopidogrel hyporesponsiveness was 66.7%. The CT was significantly shorter in carriages of the 681A allele compared with the 681G allele (P = 0.002), but had no significant difference in patients with vs. without omeprazole use (P = 0.467). The ROC analysis of an effect on clopidogrel hyporesponsiveness of CYP2C19 G681A alone and combination with omeprazole use had area under the curve values of 0.654 and 0.672, respectively. CONCLUSION: In ACS patients, the effect of the CYP2C19 G681A polymorphism on clopidogrel responsiveness, but not omeprazole use, is strong. However, a combination of both factors enhances clopidogrel hyporesponsiveness.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".