Do Cognitively Normal Children With Epilepsy Have a Higher Rate of Injury Than Their Nonepileptic Peers?
Bibliographic record
Abstract
The objective of this study was to determine if cognitively normal children with epilepsy have higher accidental injury rates than their age- and sex-matched friends without epilepsy and what factors may predict this. Patients 5 to 16 years old, with a developmental quotient >70, without major motor or sensory impairments, with a 1-year history of epilepsy and who either had a seizure or had been on antiepileptic drugs within the past year, were identified from the pediatric neurology database of the Royal University Hospital. Twenty-five of 31 cases and their best friend controls agreed to participate. Seizure-related factors including type, duration, frequency, timing, date of diagnosis, antiepileptic drug initiation and discontinuation, and specific types and total antiepileptic drugs used were assessed by interview. Questionnaires about accidental injury including type, number, severity, and, if applicable, injuries resulting from seizures, as well as general safety practices, activity restrictions, and presence of attention-deficit hyperactivity disorder, were completed by cases and controls. No significant differences in injury numbers (specific types or total) or severity were found, although a small number of epileptic children were very predisposed to injury. Seizure-related factors did not predict injury in cases. Safety practices were similar, and restrictions in cases were not excessive. Children with attention-deficit hyperactivity disorder had a higher injury rate, both in cases and controls. Cognitively normal children with epilepsy do not have a higher injury rate than their nonepileptic peers. If consciousness is impaired in seizures, extra supervision for swimming and bathing and restricted climbing heights are suggested. All other safety restrictions for epileptic children should follow those appropriate to nonepileptic children to allow a normal lifestyle.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".