The Initial Experience of Eslicarbazepine in Children at Three Canadian Tertiary Pediatric Care Centers
Bibliographic record
Abstract
INTRODUCTION: Eslicarbazepine (ESL) is a once-daily, third-generation antiseizure medication for focal-onset seizures. The primary mechanism of action is enhancing the slow inactivation of voltage-gated sodium channels. The study objective was to review real-world experience regarding retention rate, efficacy, and tolerability of eslicarbazepine, soon after it became available for children in Canada. METHODS: A retrospective review was performed on all patients prescribed eslicarbazepine from September 2017 to June 2020, with at least 3 years of follow-up data, at 3 Canadian tertiary care pediatric centers. RESULTS: Fifty patients were identified, and the mean age of eslicarbazepine initiation was 12.4 years (range 3-19 years). Most patients had drug-resistant epilepsy, trying a mean of 5.04 (range 0-14) antiseizure medications before the initiation of eslicarbazepine. Twenty-four patients (48.0%) experienced adverse effects, including dizziness (n = 10), drowsiness (n = 6), dizziness and drowsiness (n = 1), nausea and abdominal pain (n = 4), transient unsteadiness and diplopia (n = 1), and negative mood changes (n = 2). None had serious adverse effects, including rash. The retention rate of eslicarbazepine at last follow-up was 70%. Fifteen (30%) had ≥50% seizure reduction, with 2 of these patients becoming seizure free. Ten (20%) had 25% to 50% reduction, 2 (4%) had worsening of seizures, and 17 (34%) had no change in seizure frequency. CONCLUSION: The study results support the long-term effectiveness and tolerability of eslicarbazepine in a cohort of children with predominantly drug-resistant epilepsy in a real-life setting from 3 Canadian centers with initial use after approval. Adverse effects were nonserious, infrequently leading to eslicarbazepine discontinuation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".