[History of epilepsy surgery at The Hospital for Sick Children in Toronto, Canada].
Bibliographic record
Abstract
OBJECTIVE: To review the development of epilepsy surgery for pediatric patients with intractable epilepsy at The Hospital for Sick Children in Toronto, Canada. METHODS: We retrospectively collected and reviewed published papers regarding pediatric epilepsy surgery since 1930's. RESULTS: First, McKenzie started a hemispherectomy for children. Hendrick established anatomical hemispherectomy for pediatric patients with hemiparesis and intractable seizures since 1964. Hoffman performed anterior temporal lobectomy and neocortical temporal resection for lesional tempolal lobe epilepsy with or without mesial temporal sclerosis since 1974. Thereafter, multimodal neuroimaging studies of CT scan, MRI, and XenonCT, SPECT and PET have been used to identify and remove the epileptogenic lesion and zone. In 1996, magnetoencephalography (MEG) was introduced to localize interictal spike sources and somatosensory evoked fields for children with intractable seizures. Snead and Rutka started subdural grid electrodes that were constructed by scalp video EEG, MRI and MEG findings. The clustered MEG spike source coregistered with the intraoperative neuronavigation system delineated the epileptogenic zone requiring completely excision for neocortical lesional epilepsy from 2000. CONCLUSION: The pediatric epilepsy surgery at the Hospital for Sick Children has been progressing from anatomical hemispherectomy to complete clusterectomy of MEG spikes sources that localized the epileptogenic zone. Cortical excision, lobectomy, hemisphelotomy, corpus callosotomy and vagal nerve stimulation have been applied to appropriate seizure types identified by advanced neurodiagnostic modalities. We furthermore develop non-invasive methods for localizing and understanding the epileptic network in pediatric epilepsy patients with developing brain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.010 |
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".