Determinants of Variability in Divalproex Sodium (VPA) Glucuronidation in Children
Bibliographic record
Abstract
Sources of variability in VPA glucuronidation (VPA‐G) were investigated in 92 children (38F, 54M) treated with VPA for seizure disorders. Urine collected over a steady state dosing interval was analyzed for VPA and 15 metabolites by LC‐ and GC‐MS. DNA in a subset of patients (n=47) was genotyped for UGT1A6, UGT1A9, and UGT2B7 SNPs, and UGT2B17 copy number variation (CNV). IRB approval was obtained at each clinical site. Urinary VPA‐G concentration (nmol/mg creatinine) varied 800‐fold and accounted for 62.5±17.9% (mean±SD) of the total molar recovery of drug and metabolites. VPA‐G concentrations correlated with daily dose (mg/kg; p<0.0001), increased with concurrent enzyme‐inducing medications (p<0.001) and 2 copies of UGT2B17 (p<0.05), and decreased with age (p<0.05). By contrast, no age association was observed with fractional recovery of VPA‐G although dose, enzyme‐inducing meds and UGT2B17 CNV remained significant. A general linear model confirmed the associations between fraction recovery of VPA‐G and dose (p=0.006) and UGT2B17 CNV (p=0.031). VPA dose is the primary determinant of VPA‐G variability in children, and UGT2B17 copy number may also contribute. Supported by grant HD044239 from NICHD.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".