Retrospective review of the epidemiology of epilepsy in special schools for children with cerebral palsy, learning difficulties, and language and communication difficulties
Bibliographic record
Abstract
PURPOSE OF THE STUDY: To determine in children the proportion and characteristics of epilepsy associated with cerebral palsy, learning difficulties and language and communication difficulties in a specific population of two special schools. BASIC PROCEDURES: Retrospective review of case notes for 142 children in two special schools (school A and school B) in Newcastle, UK MAIN FINDINGS: School A had more children with learning difficulties (X2=32.41, p<0.01) and active epilepsy (X2=3.03, p=0.08) than school B. There were more children with cerebral palsy (X2=9.56, p<0.01) and language and communication problems (X2=4.25, p=0.03) at school B compared to school A. Active epilepsy is significantly more common in children with cerebral palsy (X2=7.58, p=0.01). All children with cerebral palsy and learning difficulties had epilepsy (n=6). Although not statistically significant, those children who developed epilepsy within the first 24 hours of life were more likely to have cerebral palsy than those who developed epilepsy later in life (X2=3.10, p=0.08). Those children with cerebral palsy tended to have a lower birth weight (t=3.15, p<0.01) and a shorter gestation (t=3.17, p<0.01) than children without cerebral palsy. PRINCIPAL CONCLUSIONS: The data supports evidence from previous studies, demonstrating that epilepsy commonly accompanies cerebral palsy, thus complicating this difficult chronic condition. We show an association between both low birth weight and gestational age, and early age of onset of seizures, in children with cerebral palsy. This illustrates the importance, in these children, of past medical history from birth to determine risk factors for epilepsy later in 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".