The role of surgery in refractory epilepsy secondary to polymicrogyria in the pediatric population
Bibliographic record
Abstract
OBJECTIVE: Polymicrogyria (PMG) is a common malformation of cortical development. Many patients with PMG will have medically refractory epilepsy but the role of epilepsy surgery is unclear. The objective of this study was to assess the efficacy of surgical resection/disconnection in achieving seizure control in pediatric patients with PMG. METHODS: A retrospective review of children undergoing epilepsy surgery for PMG between 2002 and 2017 at The Hospital for Sick Children in Toronto, Canada, was performed. RESULTS: A total of 12 children aged 6 months to 17.8 years (median 8.8 years) underwent resective surgery (7 children) or functional hemispherectomy (5 children). Gross total resection or complete disconnection of PMG was carried out in 7 of 12 children. Follow-up duration was between 1 and 9 years (median 2.1 years). Nine children remained seizure-free at last follow-up. Complete resection or disconnection of PMG led to seizure freedom in 6 of 7 patients (86%), whereas subtotal resection produced seizure freedom in 3 of 5 patients (60%). SIGNIFICANCE: We present one of the largest surgical series of pediatric PMG patients. Seizure outcomes were best with complete resection/disconnection of PMG. However, tailored resections based on electroclinical and neuroradiologic data can produce good outcomes and remain an appropriate strategy for patients with extensive PMG.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".