Pharmacokinetic and Pharmacodynamic Evaluation of Intravenous Levetiracetam in Children With Epilepsy
Bibliographic record
Abstract
This study aimed to evaluate the safety and tolerability of intravenous (IV) levetiracetam (LEV) as a monotherapy in children aged 1 month-16 years and to explore the pharmacokinetics (PK) of IV LEV and the time to seizure after IV then oral administration of LEV in pediatric children with epilepsy. Children diagnosed with acute unprovoked seizures requiring in-hospital IV LEV administration were included. After administration, the clinical seizure outcomes, side effects, and the Korean-Child Behavior Checklist were monitored and the PK and repeated time to seizure were analyzed via modeling using NONMEM software. Overall, 37 children with epilepsy were enrolled and underwent a PK analysis (median age, 4.6 years; median weight, 18.0 kg). Nine children (24.3%) had seizure recurrence during the follow-up period (median, 3.8 months) and 5 children (13.5%) experienced LEV-associated adverse events such as irritability (n = 2; 5.4%) and somnolence (n = 3; 8.1%). The plasma LEV concentrations after IV LEV were best described by a one-compartment linear PK model. Only body weight was associated with both the clearance and volume of distribution of LEV. The Weibull distribution model described the time to seizure recurrence well; no statistically significant predictor for the time to seizure was identified. Therefore, IV LEV was a well-tolerated and effective alternative in children with acute unprovoked seizures, and models for the PK and time to repeated seizure recurrence after LEV were successfully developed. In particular, the current use of a weight-based IV LEV dosing regimen in pediatric children is practical.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".