B.6 High dose diazepam treatment for Electrical Status Epilepticus in Sleep (ESES): Is it effective?
Bibliographic record
Abstract
Background: Epileptic encephalopathy with electrical status epilepticus in sleep (ESES) is a pediatric epilepsy syndrome with sleep induced epileptic discharges and acquired impairment in cognition, language and/or behavior. Despite the widespread use of high dose diazepam, there is limited research on its efficacy. Methods: Single-center, retrospective case-series of children presenting with cognitive/ language regression and ESES from 2014-2019. All children underwent baseline overnight EEG followed by diazepam (1mg/kg) administered per rectum, and continuation of 0.5 mg/kg of oral diazepam for 3 months. Follow up EEGs were performed following the first dose and after 6-9 weeks of treatment. Results: 23 children were included [male 14 (60%); mean age 7 years (4 -12)]. 10 children (45%) had symptomatic epilepsy (defined by abnormal MRI and/or genetic evaluation). Decrease in more than 25% of the spike activity was seen in 18 (78%). This effect was sustained in 11 children (47%) after 6 weeks. Only 6 (60%) children from the symptomatic group had EEG response, while 11 (91%) responded from the idiopathic group. 5 children (21%) had clinically significant cognitive/ language improvement. Conclusions: Treatment with diazepam reduces epileptiform activity in ESES in majority of children. Despite this reduction only minority of patients experience clinically significant cognitive improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".