Clopidogrel Pharmacogenetics
Bibliographic record
Abstract
Common genetic variation in CYP2C19 (cytochrome P450, family 2, subfamily C, polypeptide 19) *2 and *3 alleles leads to a loss of functional protein, and carriers of these loss-of-function alleles when treated with clopidogrel have significantly reduced clopidogrel active metabolite levels and high on-treatment platelet reactivity resulting in increased risk of major adverse cardiovascular events, especially after percutaneous coronary intervention. The Food and Drug Administration has issued a black box warning advising practitioners to consider alternative treatment in CYP2C19 poor metabolizers who might receive clopidogrel and to identify such patients by genotyping. However, routine clinical use of genotyping for CYP2C19 loss-of-function alleles in patients undergoing percutaneous coronary intervention is not recommended by clinical guidelines because of lack of prospective evidence. To address this critical gap, TAILOR-PCI (Tailored Antiplatelet Initiation to Lessen Outcomes due to Decreased Clopidogrel Response After Percutaneous Coronary Intervention) is a large, pragmatic, randomized trial comparing point-of-care genotype-guided antiplatelet therapy with routine care to determine whether identifying CYP2C19 loss-of-function allele patients prospectively and prescribing alternative antiplatelet therapy is beneficial.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".