Epilepsy surgery in tuberous sclerosis complex: the BC Children’s Hospital experience
Bibliographic record
Abstract
Background: Epilepsy occurs in up to 90% of patients with Tuberous Sclerosis Complex (TSC) and is often refractory to medications. Our objective was to assess the safety and outcome of epilepsy surgery in children with TSC at our institution. Methods: We performed a systematic, retrospective chart review of children with TSC who underwent epilepsy surgery at our institution. Patients were identified through epilepsy and clinical neurophysiology databases. Results: 19 patients (out of 81 with TSC) underwent surgery between 1995-2014. Median age at surgery was 4.2 (Range 1.1-15.6) years, with patients having failed a median 4 (Range 0-10) anti-seizure medications. Surgery comprised corpus callosotomy in 2 and resection of one or more tubers in 17. 2 patients had a subsequent second resection. Minor neurologic deficits occurred after 14% of surgeries. Median follow-up was 2.4 years (Range 0.3 -13.8 years) following surgery . At last follow-up, 47% were seizure free, including 2 patients off anti-seizure medication. Conclusions: Epilepsy surgery is safe and effective in carefully selected TSC patients, with the majority having a good seizure outcome. Children with epilepsy secondary to TSC should be referred for epilepsy surgery assessment.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".