The frequency of intractable seizures after stopping AEDs in seizure-free children with epilepsy
Bibliographic record
Abstract
BACKGROUND: After 1 to 4 years, seizure-free children with epilepsy are encouraged to stop daily antiepileptic drug (AED) treatment. Approximately 70% are successful. The authors examined how often intractable epilepsy follows discontinuation of AED treatment in a population-based cohort of children with epilepsy. METHODS: The Nova Scotia population-based epilepsy cohort was used to identify children who discontinued AEDs but subsequently developed intractable epilepsy. All patients studied (ages 1 month to 16 years) developed epilepsy between 1977 and 1985, had epilepsies characterized by partial or convulsive seizures, and had at least 5 years of follow-up evaluation (n = 367). Those with benign rolandic epilepsy were excluded. Intractability was defined as one or more seizures every 3 months during the last year of follow-up review or until successful seizure surgery and failure of three or more AEDs at maximum tolerated doses. RESULTS: Overall, 71% (260/367) of eligible children became free of seizure for 1 to 4 years and discontinued AED treatment. Of this group, 70% remained seizure-free without AED treatment, but 30% had recurrences. Only three children with recurrences later developed intractable epilepsy. Two then underwent a temporal lobectomy, one successful and one only partially successful (20-year follow-up periods). The third patient continued to have intractable epilepsy for 7 years after discontinuing AED treatment but eventually entered remission. CONCLUSION: Approximately 1% of children who became free of seizure and discontinued antiepileptic drug treatment had recurrent seizures that could not be controlled again with medication. The authors were unable to predict this outcome. It remains unclear whether a similar outcome would have occurred if antiepileptic drugs had not been discontinued.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".