Brivaracetam: First Canadian Experience in an Intractable Epilepsy Population
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness and tolerability of brivaracetam (BRV) in a refractory epilepsy population in an outpatient clinical setting. METHODS: Retrospective medical information system review and self-report questionnaire for all patients treated with BRV until the end of 2017. RESULTS: Thirty-eight patients were included, 73.7% female and mean age 36.2. The mean number of antiepileptic drugs (AEDs) for previous use was 8.9, and for current use was 2.5. Mean seizure frequency in the last 3 months was 12 per month. At 3, 6, 12, and 15 months, the 50% responder rates were 36.1%, 32%, 41.2%, and 45.5%, respectively. Patients took BRV for a median duration of 8.25 months, ranging from 7 days to 60 months. Retention rate was 75.0%, 72.0%, 59.2%, and 47.9% at 3, 6, 12, and 15 months, respectively. Overall, the main reasons for discontinuation were adverse events (AEs) (52.3%), lack of efficacy (35.3%), or both (11.8%). The rate of total AEs was 60.5% according to medical records and 85.7% according to questionnaire, including mostly tiredness, psychiatric, and memory complaints. Psychiatric side effects occurred in 31.6% according to medical records and 47.4% according to questionnaire results, which is higher than previously reported and persisted throughout the study period. CONCLUSIONS: BRV appears to be a useful and safe add-on treatment, even in a very refractory group of patients. In this real-life clinical setting, psychiatric AEs were found at a higher rate than previously published.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".