Childhood epilepsy with a small number of seizures may be left untreated: an international prospective study
Bibliographic record
Abstract
It is unknown whether treatment with antiepileptic drugs in children with epilepsy with a presumed good prognosis is always necessary. We aimed to study the course of newly diagnosed epilepsy in children with a presumed good prognosis who are managed without AED treatment. A total of 151 children (one month to 12 years of age) with two to five lifetime unprovoked seizures (excluding febrile convulsions), were followed for three years. Treatment was initially withheld. Children with symptomatic epilepsy, or absence or myoclonic epilepsy, were excluded. AED treatment was started after >10 lifetime seizures or an episode of status epilepticus during follow-up, or if the parents or treating physician deemed it otherwise necessary. During follow-up, 113 children continued to meet our criteria for refraining from treatment with antiepileptic drugs, yet 30 started treatment at the request of the parents. Thirty-eight children at some time met the criteria to start treatment, but the parents of 16 declined treatment. In all, 99 (66%) children maintained the no-treatment regime. Ninety-eight children (65% of 151) reached terminal remission for at least one year, including 83 who did not receive antiepileptic drug treatment (84% of the untreated 99). Mean terminal remission was significantly longer in the group with a total of <10 seizures compared to those with >10 seizures. Treatment did not increase the length of terminal remission. Adverse events, including traumatic injury, occurred equally in the treated and untreated children. Measures of quality of life suggested a better outcome in those without treatment. Children with newly diagnosed epilepsy with a presumed good prognosis may not need immediate AED treatment. Postponing treatment does not alter the chance of remission or the risk of accidents and adverse events and appears to be associated with a good quality of life.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".