Management and prognosis of pediatric status epilepticus
Bibliographic record
Abstract
Abstract Background Pediatric status epilepticus is a neurological emergency with the potential for severe developmental and neurological consequences. Prompt diagnosis and management are necessary. Objectives To outline the existing best available evidence for managing pediatric and neonatal status epilepticus, in the light of emerging randomized controlled studies. We also focus on short and long-term prognoses. Materials and methods This is a systematic overview of the existing literature. Results Status epilepticus, its treatment, and prognosis are usually based on the continuation of seizure activity at 5 and 30 min. Refractory and super-refractory status epilepticus further complicates management and requires continuous EEG monitoring with regular reassessment and adjustment of therapy. Benzodiazepines have been accepted as the first line of treatment on the basis of reasonable evidence. Emerging randomized controlled trials demonstrate equal efficacy for parenterally administered phenytoin, levetiracetam, and valproic acid as second-line agents. Beyond this, the evidence for third-line options is sparse. However, encouraging evidence for midazolam and ketamine exists with further data required for immunological, dietary, and surgical interventions. Conclusion Our overview of the management of pediatric and neonatal status epilepticus based on available evidence emphasizes the need for evidence-based guidelines to manage status epilepticus that fails to respond to second-line treatment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".