Pharmacokinetics and Drug Dosing in Obese Children
Bibliographic record
Abstract
OBJECTIVES: To review pharmacokinetics in obese children and to provide medication dosing recommendations. METHODS: EMBASE, MEDLINE, AND INTERNATIONAL PHARMACEUTICAL ABSTRACTS DATABASES WERE SEARCHED USING THE FOLLOWING TERMS: obesity, morbid obesity, overweight, pharmacokinetics, drug, dose, kidney function test, creatinine, pediatric, and child. RESULTS: We identified 10 studies in which the authors examined drug dosing or pharmacokinetics for obese children. No information was found for drug absorption or metabolism. Obese children have a higher percent fat mass and a lower percent lean mass compared with normal-weight children. Therefore, in obese children, the volume of distribution of lipophilic drugs is most likely higher, and that of hydrophilic drugs is most likely lower, than in normal-weight children. Serum creatinine concentrations are higher in obese than normal-weight children. Total body weight is an appropriate size descriptor for calculating doses of antineoplastics, cefazolin, and succinylcholine in obese children. Initial tobramycin doses may be determined using an adjusted body weight, although using total body weight in the context of monitoring serum tobramycin concentrations would also be an appropriate strategy. We found no information for any of the opioids; antibiotics such as penicillins, carbapenems, vancomycin, and linezolid; antifungals; cardiac drugs such as digoxin and amiodarone; corticosteroids; benzodiazepines; and anticonvulsants. In particular, we found no information about medications that are widely distributed to adipose tissue or that can accumulate there. CONCLUSIONS: The available data are limited because of the small numbers of participating children, study design, or both. The number and type of drugs that have been studied limit our understanding of the pharmacokinetics in obese children. In the absence of dosing information for obese children, it is important to consider the nature and severity of a child's illness, comorbidities, organ function, and side effects and physiochemical properties of the drug. Extrapolating from available adult data is possible, as long as practitioners consider the effects of growth and development on the pharmacokinetics relevant to the child's age.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".