Epilepsy surgery in the first 3 years of life: A Canadian survey
Bibliographic record
Abstract
OBJECTIVE: To determine the clinical characteristics, surgical challenges, and outcome in children younger than 3 years of age undergoing epilepsy surgery in Canada. METHODS: Retrospective data on patients younger than age 3 years who underwent epilepsy surgery at multiple centers across Canada from January 1987 to September 2005 were collected and analyzed. RESULTS: There were 116 patients from eight centers. Seizure onset was in the first year of life in 82%, and mean age at first surgery was 15.8 months (1-35 months). Second surgeries were done in 27 patients, and a third surgery in 6. Etiologies were malformations of cortical development (57), tumor (22), Sturge-Weber syndrome (19), infarct (8), and other (10). Surgeries comprised 40 hemispheric operations, 33 cortical resections, 35 lesionectomies, 7 temporal lobectomies, and one callosotomy. There was one surgical mortality. The most common surgical complications (151 operations in 116 patients) were infection (17) and aseptic meningitis in 13. Of 107 patients with seizure outcome assessed more than one year postoperatively, 72 (67.3%) were seizure free (Engel I), 15(14%) had >90% improvement (Engel II), 12 had >50% improvement (Engel III), and 8 did not benefit from surgery (Engel IV). Development improved in 55.3% after surgery. CONCLUSION: Epilepsy surgery in children younger than 3 years of age is relatively safe and is effective in controlling seizures. Very young age is not a contraindication to surgery in children with refractory epilepsy, and early surgery may impact development positively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".