Intra- and interindividual variability of glucuronidation of paracetamol during repeated administration of propacetamol in neonates
Bibliographic record
Abstract
Background: Major changes in drug clearance and metabolism are observed during infancy, in part based on ontogenic regulation of various metabolic pathways. Since paracetamol provides a good substrate to study UGT (1A6) activity, urinary metabolites of propacetamol were determined in neonates in whom propacetamol was repeatedly administered. Methods: Paracetamol glucuronide (APAP-G), paracetamol sulphate (APAP-S) and free paracetamol were determined in urine samples of neonates during repeated administration of propacetamol. Spearman rank and linear multiple regression (MedCalc®, Mariakerke, Belgium) were used to study the effect of postnatal age, of postconceptional age and of repeated administration on the relative contribution of APAP-G to overall urine paracetamol (APAP-G + APAP-S + free paracetamol) elimination (G/T ratio). Results: 147 samples were collected in 23 neonates. Molar median G/T ratio was 14% (range 1-53). Besides increasing G/T ratio with increasing postnatal (p<0.0001) and postconceptional age (p<0.01), repeated administration (p<0.01) also correlated with an increasing G/T ratio, and repeated administration remained significant (p<0.01) after correction of postnatal and postconceptional age in a multiple regression model. Conclusion: Major variability in the ontogeny of UGT activity to overall elimination of paracetamol was documented in neonates. Besides postnatal and postconceptional age, a significant effect of repeated administration on UGT activity was documented.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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".