Psychosocial outcomes in children two years after epilepsy surgery: Has anything changed?
Bibliographic record
Abstract
Summary Purpose: We prospectively explored psychosocial outcomes in children (7–18 years) 2 years after epilepsy surgery. This study built on our previous one that examined these children 1 year after surgery. Methods: Twenty children were studied using the Child Behavior Checklist (CBCL; a parent report instrument of potential behavioral and social problems) preoperatively, 1 year and 2 years after surgery. A comparison group of 12 children with medically refractory seizures was examined at comparable times. We conducted mixed factorial ANOVAs to determine group, time, and interaction effects, and regression analyses to assess factors driving significant (p ≤ 0.05) interactions. We also investigated the proportion of children scoring in the abnormal range over time. Results: Significant main effects of time were observed on total behavior, externalizing, aggression, and delinquent behavior scales, with both groups reporting improvement. Main effects of group were observed for withdrawn and total competence scales, with the surgical group demonstrating favorable scores. Significant group × time interactions were observed on the social and social problems subscales. On both subscales, the surgical group demonstrated improvement over time, whereas the nonsurgical group experienced decline. Fifty percent of the surgical group remained seizure‐free. Seizure status and number of antiepileptic medications predicted changes in social scores. We did not observe a significant regression model for the social problems subscale. Discussion: These findings suggest that change in social function may take time to develop after surgery. Prospective studies designed for longer periods are required to determine if improvements in other psychosocial domains are seen over time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".