In pediatric patients, age has more impact on dosing of vitamin K antagonists than VKORC1 or CYP2C9 genotypes
Bibliographic record
Abstract
Anticoagulation with vitamin K antagonists (VKAs) is problematic because of difficulties in safely managing dosing. Polymorphisms in cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase genes (VKORC1) have been shown to affect VKA dosing in adults. The association of these polymorphisms on VKA dosing in children has not been investigated. The objective of the study was to assess associations of CYP2C9 and VKORC1 polymorphisms and clinical variables on VKA dosing in children. A nonselected cohort of pediatric patients receiving VKA were tested for CYP2C9 and VKORC1 polymorphisms, and clinical data were collected. Multiple linear regression modeling was used to assess relationships of VKA dose with genetic and clinical variables. Fifty-nine patients were recruited; 55.9% were receiving warfarin, and 44.1% were on phenprocoumon. There was a negative association of age with VKA dose (P < .001). Comparing VKORC1 genotypes, the AA group required significantly lower daily doses than GG group (P = .011). In the full model including age, VKORC1 and CYP2C9 genotypes accounted for 38% of dose variation. Age explained 28.3% of VKA dose variations; VKORC1 and CYP2C9 explained only 3.7% and 0.4%, respectively. In children, the most critical factor in determining VKA dose is age. VKORC1/CYP2C9 genotypes only marginally explain dose variations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".