Hemispheric Surgery in Children with Refractory Epilepsy: Seizure Outcome, Complications, and Adaptive Function
Bibliographic record
Abstract
PURPOSE: To describe seizure control, complications, adaptive function and language skills following hemispheric surgery for epilepsy. METHODS: Retrospective chart review of patients who underwent hemispheric surgery from July 1993 to June 2004 with a minimum follow-up of 12 months. RESULTS: The study population comprised 24 children, median age at seizure onset six months and median age at surgery 41 months. Etiology included malformations of cortical development (7), infarction (7), Sturge-Weber Syndrome (6), and Rasmussen's encephalitis (4). The most frequent complication was intraoperative bleeding (17 transfused). Age <2 yr, weight <11 kg, and hemidecortication were risk factors for transfusion. Postoperative complications included aseptic meningitis (6), and hydrocephalus (3). At median follow-up of 7 yr, 79% of patients are seizure free. Children with malformations of cortical development and Rasmussen's encephalitis were more likely to have ongoing seizures. Overall adaptive function scores were low, but relative strengths in verbal abilities were observed. Shorter duration of epilepsy prior to surgery was related significantly to better adaptive functioning. CONCLUSIONS: Hemispheric surgery is an effective therapy for refractory epilepsy in children. The most common complication was bleeding. Duration of epilepsy prior to surgery is an important factor in determining adaptive outcome.
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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 | 0.000 | 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".