Retention Rate and Efficacy of Perampanel with a Slow Titration Schedule in Adults
Bibliographic record
Abstract
RATIONALE: The manufacturer of perampanel (PER) suggests an initial adult dose of 2-4 mg/day and an upward dose titration of 2 mg at no more frequently than 1- or 2-week intervals when used with enzyme-enhancing antiepileptic drugs (AEDs) or nonenzyme-enhancing AEDs, respectively. The general practice in our clinic is an initial dose of PER 2 mg/day and titrated by 2 mg/4 weeks to an initial target of 6 mg/day. METHODS: Retrospective chart audit of patients starting PER in an adult epilepsy clinic between September 2013 and November 2016 with at least one 6-month follow-up visit was reviewed. Data collection included patient demographics, seizure characteristics, past and concurrent therapy, monthly seizure frequency before PER and at 6-month visit, and characteristics of PER discontinuation. Efficacy of treatment was assessed with the Engel classification and 50% responder rate. RESULTS: N = 102 patients; mean age = 40 years and 54% females. Focal onset seizures 85%, generalized 13%, and unknown 2%. Median prior AED exposure = 6 (range 3-20); median concomitant AED use = 2 (range 1-5). Follow-up range was 6-37 months. The median seizure frequency/month prePER treatment was 6 (range 0-30) for focal onset seizures and 1 (range 0-6) for generalized seizures. The retention rate amongst all patients at 6 months was 78.4%. At 6-month follow-up, 36% of all patients achieved Engel class I (seizure freedom) (30.7% of patients with focal onset seizures and 63.6% with generalized epilepsy). The 50% responder rate was 52% and 82% for focal and generalized epilepsy, respectively. CONCLUSION: PER has a good retention rate when titrated slowly and thus encouraging seizure freedom results in an otherwise medically refractory epilepsy population.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".