Hemispherotomy for Epilepsy: The Procedure Evolution and Outcome
Bibliographic record
Abstract
Hemispherectomy is a unique epilepsy surgery procedure that has undergone significant modification and evolution since Dandy's early description. This procedure is mainly indicated to treat early childhood and infancy medically intractable epilepsy. Various epileptic syndromes have been treated with this procedure, including hemimegalencephaly (HME), Rasmussen's encephalitis, Sturge-Weber syndrome (SWS), perinatal stroke, and hemispheric cortical dysplasia. In terms of seizure reduction, hemispherectomy remains one of the most successful epilepsy surgery procedures. The modification of this procedure over many years has resulted in lower mortality and morbidity rates. HME might increase morbidity and lower the success rate. Future studies should identify the predictors of outcomes based on the pathology and the type of hemispherectomy. Here, based on a literature review, we discuss the evolution of hemispherectomy techniques and their outcomes and complications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".