Pharmacokinetics of Dexamethasone in Children and Adolescents with Obesity
Bibliographic record
Abstract
Dexamethasone is a synthetic glucocorticoid approved for treating disorders of various organ systems in both adult and pediatric populations. Currently, approved pediatric dosing recommendations are weight-based, but it is unknown whether differences in dexamethasone drug disposition and exposure exist for children with obesity. This study aimed to develop a population pharmacokinetic (PopPK) model for dexamethasone with data collected from children with obesity. Dexamethasone was given as either IV or oral/enteral administration, and a salt factor correction was used for dexamethasone sodium phosphate injection. A PopPK analysis using dexamethasone plasma concentration versus time was performed using the software NONMEM. A virtual population of 1000 children with obesity across three age groups was generated for dosing simulations. Data from 59 study participants with 82 PK plasma samples were used in the PopPK analysis. A one-compartment model with first-order absorption and the inclusion of total body weight as a covariate characterized the data. No other covariates were included in the PopPK model. Single and multiple IV dose(s) of 0.5 and 1 mg/kg every 8 h resulted in 68% or more of virtual children with obesity attaining simulated exposures that were within exposure ranges previously reported in adult studies. In conclusion, this was the first study to characterize dexamethasone's PopPK in children with obesity. Simulation results suggest that virtual children with obesity receiving oral doses of 0.5 and 1 mg/kg had generally comparable dexamethasone exposures as adult estimates. Additional studies are needed to characterize the dexamethasone's target exposure in children.
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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 | 0.000 | 0.001 |
| 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 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".