Levetiracetam Versus Phenytoin or Fosphenytoin for Second-Line Treatment of Pediatric Status Epilepticus: A Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: To synthesize the available evidence examining the efficacy and safety of levetiracetam compared with phenytoin or fosphenytoin in benzodiazepine-refractory pediatric status epilepticus. DATA SOURCES: We searched (from inception until April 27, 2020) Ovid MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials. STUDY SELECTION: Two reviewers, independently and in duplicate, screened citations and manuscripts for eligible randomized controlled trials. DATA EXTRACTION AND SYNTHESIS: Independently and in duplicate, we performed data abstraction, risk of bias assessment, and certainty assessment using Grading of Recommendations, Assessment, Development, and Evaluation. We performed meta-analyses using random-effect models or, if insufficient data, presented findings narratively. RESULTS: We identified seven randomized controlled trials (n = 1,575). Pooled analysis demonstrated low certainty evidence for no difference of levetiracetam on time to seizure cessation (mean difference, -3.11 min; 95% CI, -6.67 to 0.45), early seizure cessation (relative risk, 1.09, 95% CI, 0.95-1.26), or late seizure cessation (relative risk, 1.05; 95% CI, 0.93-1.18). Adverse event outcomes were limited by low event numbers. We found low certainty evidence for less respiratory depression with levetiracetam (relative risk, 0.28; 95% CI, 0.12-0.69). CONCLUSIONS: The efficacy of levetiracetam is comparable with phenytoin or fosphenytoin in children with benzodiazepine-refractory status epilepticus (low certainty evidence). Levetiracetam may cause less respiratory depression. Clinicians and guideline developers should weigh safety profiles when choosing between these agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.065 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".