P.038 Clinical experience with perampanel for refractory pediatric epilepsy in one Canadian center
Bibliographic record
Abstract
Background: Perampanel (PER) is a new anti-seizure medication that inhibits the α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) class of glutamate receptors. It is available in Canada for children since 2014. It is important for physicians to be aware of the efficacy and tolerability of drugs in the post-marketing phase. Methods: We did a retrospective review of our experience with PER at BC Children’s Hospital. Patients on PER were identified. Clinical data, including demographics, efficacy, tolerability, adverse effects (AE) and retention rates were obtained by review of clinical records. Results: Of 24 patients pediatric patients prescribed PER, 21 (87%) had focal and three had symptomatic generalized epilepsy. Ten (42%) had greater than 50% reduction in seizures. In fifteen patients, (63%) PER was discontinued due to AE or poor response. Twelve (50%) had behavioral AE and eight (33%) had non-behavioral AE. PER was effective, at lower doses than required for adults. One third experienced serious AE. One patient experienced oculogyric crisis, not previously reported with PER. AE were not associated with high doses and were reversible. Possible risk factors for behavioral AE include behavioral problems with other medications and pre-existing behavioral co-morbidities. Conclusions: It is important for clinicians to be aware of and counsel patients about serious AE, particularly behavioral, when prescribing PER.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.006 | 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".