Management of status epilepticus in the emergency department: Systematic review and clinical update
Bibliographic record
Abstract
OBJECTIVE: To update the available evidence on the management of all types of status epilepticus (SE) in hospital emergency departments (EDs) and prehospital emergency medical services (EMS). METHODS: We conducted a systematic review following PRISMA 2020 methodology. A comprehensive search was conducted across biomedical databases (PubMed, Embase, Cochrane, Web of Science, and Spanish databases) from January 2015 through October 2025. Studies on treatment, validated prognostic scales, and multicenter registries of convulsive and nonconvulsive SE were included. Quality assessment was performed using GRADE and the Newcastle-Ottawa Scale. RESULTS: A total of 47 studies were included. Benzodiazepines remain the first-line therapy (high certainty of evidence, GRADE). As second-line therapy, levetiracetam, phenytoin, and valproate showed comparable efficacy (50-60%; moderate certainty). The ESETT trial demonstrated no superiority among second-line antiseizure drugs. Spanish evidence includes the ACESUR Registry (664 patients) and the validated RACESUR (AUC 0.72) and ADAN scales (predictive accuracy 90.9%; 95% CI, 88.4-93.4), providing context-specific evidence for the Spanish healthcare system. CONCLUSIONS: SE management requires rapid sequential treatment with benzodiazepines followed by second-line antiseizure drugs. Comparable efficacy among second-line options allows individualized treatment. The Spanish RACESUR and ADAN scales are validated tools that facilitate risk stratification in emergency settings.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 0.001 |
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".