Resective Epilepsy Surgery for Tuberous Sclerosis in Children
Bibliographic record
Abstract
BACKGROUND: There are no established variables that predict the success of curative resective epilepsy surgery in children with tuberous sclerosis complex (TSC). OBJECTIVE: We performed a multicenter observational study to identify preoperative factors associated with seizure outcome in children with TSC undergoing resective epilepsy surgery. METHODS: A retrospective chart review was performed in eligible children at New York Medical Center, Miami Children's Hospital, Cleveland Clinic Foundation, BC Children's Hospital, Hospital for Sick Children, and Sainte-Justine Hospital between January 2005 and December 2013. A time-to-event analysis was performed. The "event" was defined as seizures after resective epilepsy surgery. RESULTS: Seventy-four patients (41 male) were included. The median age of the patients at the time of surgery was 120 months (range, 3-216 months). The median time to seizure recurrence was 24.0 ± 12.7 months. Engel Class I outcome was achieved in 48 (65%) and 37 (50%) patients at 1- and 2-year follow-up, respectively. On univariate analyses, younger age at seizure onset (hazard ratio [HR]: 2.03, 95% confidence interval [CI]: 1.03-4.00, P = .04), larger size of predominant tuber (HR: 1.03, 95% CI: 0.99-1.06, P = .12), and resection larger than a tuberectomy (HR: 1.86, 95% CI: 0.92-3.74, P = .084) were associated with a longer duration of seizure freedom. In multivariate analyses, resection larger than a tuberectomy (HR: 2.90, 95% CI: 1.17-7.18, P = .022) was independently associated with a longer duration of seizure freedom. CONCLUSION: In this large consecutive cohort of children with TSC and medically intractable epilepsy, a greater extent of resection (more than just the tuber) is associated with a greater probability of seizure freedom. This suggests that the epileptogenic zone may include the cortex surrounding the presumed offending tuber.
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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 | 0.001 |
| 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".