Hemispherectomy for the Control of Intractable Epilepsy in Childhood: Comparison of 2 Surgical Techniques in a Single Institution
Bibliographic record
Abstract
BACKGROUND: Hemispherectomy is an established neurosurgical procedure for catastrophic epilepsy in childhood. However, the technique used to achieve an optimum outcome remains to be determined. OBJECTIVE: We examined the influence of hemidecortication (HD) vs peri-insular hemispherotomy (PIH) on patient outcome. METHODS: The medical records of 41 children undergoing hemispherectomy were reviewed for patient demographics, clinical criteria, and surgical outcomes. RESULTS: HD and PIH were performed in 21 and 20 children, respectively. The mean age at surgery for HD was 54 months and 61 months for PIH. The median durations of surgery for HD and PIH were 5 hours and 7 hours, respectively (P < .001). For HD, 6 patients required a second surgery and 3 required a third. One PIH patient required a second procedure. Postoperative shunting was required in 5 HD patients, but only 1 PIH patient. All patients had increased hemiparesis after surgery. The overall mean follow-up time was 72 months. Engel class I or II outcomes after initial surgery were better after PIH (85%) compared with HD (48%) (P < .02). After subsequent surgeries for seizure control, 4 HD patients and 1 PIH patient improved to Engel class I or II. CONCLUSION: Hemispherectomy is an effective surgical procedure for childhood intractable catastrophic epilepsy. In patients with diffuse hemispheric disorder, PIH tends to have fewer major complications, more favorable seizure outcomes, and a decreased need for subsequent surgical procedures, including shunting for hydrocephalus, compared with HD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".