Utility of Antiepileptic Drug Monitoring in the Pediatric Emergency Department
Bibliographic record
Abstract
Convulsive disorders are common in the pediatric age group, and measurement of serum concentration of an antiepileptic drug (AED) is frequently ordered for epileptic patients in the emergency department (ED). The objective of this study was to develop a better understanding of the indications for, and consequences of, monitoring AED serum concentrations in the pediatric ED. Charts of 116 patients who visited the ED and were tested for blood levels of AED were retrospectively reviewed. Main outcome measures were number and percentage of levels outside the therapeutic range, discontinuation of an AED or introduction of a new one, dosage modifications, and admission to hospital. Two pediatricians and a pediatric neurologist aware only of patients' age, weight, diagnosis, history, clinical presentation, and drug details reviewed each case and on the basis of predetermined criteria decided whether measurement of AED was indicated. Mean age (+/- SD) of the study population was 7 +/- 5 years (range, 2 months-17 years). Forty-two patients (36%) were on monotherapy, and 74 (64%) were on polytherapy. Sixty-eight patients (59%) presented with increased seizure frequency, 7 (6%) with status epilepticus, and 13 (11%) with suspected AED toxicity. The remainder of the children presented with problems unrelated to epilepsy. No significant difference was found between patients with AED levels within the therapeutic range and those with levels outside it in the proportion of children needing dosage change, change in medication, or hospital admission (P = 0.5, 0.8, and 0.8, respectively). None of the patients presenting with status epilepticus and only 15% of those with increased seizure activity had subtherapeutic levels. Review of the cases suggested that measuring serum AED level was not indicated in 57 (49.1%) patients. In the pediatric ED, abnormal AED levels do not correlate with clinical management. Before ordering tests, physicians should consider whether their results would alter patient treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".