Population Pharmacokinetics of Ibuprofen Enantiomers in Very Premature Neonates
Bibliographic record
Abstract
The objective of the present study was to evaluate the pharmacokinetic parameters for both S- and R-ibuprofen enantiomers in very premature neonates (gestational age strictly inferior to 28 weeks) and possible relationships between the pharmacokinetic parameters and various covariates. Newborns were randomized to receive ibuprofen or placebo for the prophylactic treatment of patent ductus arteriosus (PDA) at an initial dose of 10 mg/kg ibuprofen within 6 hours after birth, followed by two 5-mg/kg doses at 24-hour intervals (n = 52). If a PDA was still present afterwards, a curative course of ibuprofen using the same dosage regimen was administered (n = 10). A sparse sampling strategy was used because only 2 samples were collected after the third prophylactic injection and 1 after the third curative injection. A model including the chiral transformation of R- to S-ibuprofen was fitted to the concentration-time data using a population approach (NONMEM). R- and S-ibuprofen t(1/2) were about 10 hours and 25.5 hours, respectively. After prophylactic treatment, the mean clearance of R-ibuprofen (CLR = 12.7 mL/h) was about 2.5-fold higher than for S-ibuprofen (CLS = 5.0 mL/h). In addition, clearance of R- and S-ibuprofen increased significantly with gestational age. The mean estimation of R-ibuprofen clearance was found to be higher than for S-ibuprofen, and the clearance of both enantiomers increased with gestational age. This should be considered to assess pharmacokinetic-pharmacodynamic relationships of ibuprofen in premature neonates and subsequently to understand and refine the use of ibuprofen in managing PDA either as a prophylactic or curative treatment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".