Initial Experience with Cenobamate for Drug Refractory Epilepsy at a Canadian Pediatric Tertiary Care Center
Bibliographic record
Abstract
ABSTRACT Introduction: Cenobamate is a novel anti-seizure medication (ASM) in the alkyl carbamate family with a dual mechanism of action: targeting persistent sodium currents and positively modulating γ-aminobutyric acid type A receptors independent of benzodiazepines. Approved by Health Canada in June 2023, it offers an additional treatment option for seizures. This study’s objective was to review the real-world experience with cenobamate in a Provincial Comprehensive Epilepsy Program, soon after its availability in Canada. Methods: A retrospective study of all patients prescribed cenobamate from June 2023 to May 2025. Results: The study population comprised 36 patients with a median age of 18 years (range: 8–23 years). Seizure etiology was structural ( n = 18) and genetic ( n = 13). Prior to starting cenobamate, patients had tried a mean of 10 ASMs. Additionally, 19 (53%) had undergone epilepsy surgery, 3 (8%) had failed the ketogenic diet and 11 (31%) were treated with neuromodulation. Following a mean duration of 10.5 months of treatment with cenobamate, 50% (18/36) had a > 50% seizure reduction, and 20% (7/36) had a 25%–50% reduction of seizures. Fourteen percent (5/38) of patients were seizure-free at the most recent follow-up. The median dose was 200 mg (range: 62.5–400 mg). Eighteen patients (50%) experienced adverse effects (AEs), including dizziness, drowsiness, nausea and vomiting. However, only two patients discontinued cenobamate due to AEs. No patients discontinued cenobamate due to a lack of efficacy. Conclusion: This real-world study demonstrates the efficacy and tolerability of cenobamate in patients with highly drug-resistant epilepsy
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".