Treatment of seizures in the neonate:Guidelines and consensus-based recommendations—Special report from the ILAE Task Force on Neonatal Seizures
Bibliographic record
Abstract
Seizures are common in neonates, but there is substantial management variability. The Neonatal Task Force of the International League Against Epilepsy (ILAE) developed evidence-based recommendations about antiseizure medication (ASM) management in neonates in accordance with ILAE standards. Six priority questions were formulated, a systematic literature review and meta-analysis were performed, and results were reported following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 standards. Bias was evaluated using the Cochrane tool and risk of Bias in non-randomised studies - of interventions (ROBINS-I), and quality of evidence was evaluated using grading of recommendations, assessment, development and evaluation (GRADE). If insufficient evidence was available, then expert opinion was sought using Delphi consensus methodology. The strength of recommendations was defined according to the ILAE Clinical Practice Guidelines development tool. There were six main recommendations. First, phenobarbital should be the first-line ASM (evidence-based recommendation) regardless of etiology (expert agreement), unless channelopathy is likely the cause for seizures (e.g., due to family history), in which case phenytoin or carbamazepine should be used. Second, among neonates with seizures not responding to first-line ASM, phenytoin, levetiracetam, midazolam, or lidocaine may be used as a second-line ASM (expert agreement). In neonates with cardiac disorders, levetiracetam may be the preferred second-line ASM (expert agreement). Third, following cessation of acute provoked seizures without evidence for neonatal-onset epilepsy, ASMs should be discontinued before discharge home, regardless of magnetic resonance imaging or electroencephalographic findings (expert agreement). Fourth, therapeutic hypothermia may reduce seizure burden in neonates with hypoxic-ischemic encephalopathy (evidence-based recommendation). Fifth, treating neonatal seizures (including electrographic-only seizures) to achieve a lower seizure burden may be associated with improved outcome (expert agreement). Sixth, a trial of pyridoxine may be attempted in neonates presenting with clinical features of vitamin B6-dependent epilepsy and seizures unresponsive to second-line ASM (expert agreement). Additional considerations include a standardized pathway for the management of neonatal seizures in each neonatal unit and informing parents/guardians about the diagnosis of seizures and initial treatment options.
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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 | 0.000 | 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) | 0.001 | 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".