Hemispherectomy at The Hospital for Sick Children: expanded indications and lessons learned over 35 years
Bibliographic record
Abstract
OBJECTIVE: Functional hemispherectomy is an effective surgical intervention for select patients with drug-resistant epilepsy. The last several decades have seen dramatic evolutions in preoperative evaluation, surgical techniques, and postoperative care. Here, the authors present a retrospective review of the medical records of 146 children who underwent hemispherectomy between 1987 and 2022 at The Hospital for Sick Children, providing a unique overview of the evolution of the procedure and patient outcomes over 35 years. METHODS: The medical records of all children who underwent hemispherectomy at The Hospital for Sick Children between 1987 and 2022 were reviewed. Demographic information, preoperative clinical features, short-term and long-term seizure outcomes, and details regarding postoperative complications were recorded. RESULTS: The seizure outcomes of 146 children were analyzed. There were 68 females and 78 males with a mean age of 5.08 years, 123 of whom demonstrated seizure freedom (Engel class IA) in the short-term postoperative follow-up period and 89 in the long term. The effectiveness of hemispherectomy in achieving long-term seizure control has improved over time (β = 0.06, p < 0.001). Factors associated with overall seizure freedom included younger age at the time of hemispherectomy and stroke as the etiology of seizures, as well as complete disconnection during the first surgery. Additionally, the etiologies of epilepsy for which hemispherectomy is performed have expanded over time, while complication rates have remained unchanged. CONCLUSIONS: Hemispherectomy is an increasingly effective treatment for certain cases of drug-resistant epilepsy. The etiologies of epilepsy for which hemispherectomy is performed are broadening, with no change in its safety profile. Seizure outcomes are better when the etiology of epilepsy is an ischemic injury, and the most common complication after the procedure is hydrocephalus. These findings reinforce the ongoing use of hemispherectomy as a safe and effective treatment option for certain individuals with drug-resistant epilepsy, support its application to a broader range of etiologies, and highlight areas of future investigation.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".