Functional hemispherectomy: can preoperative imaging predict outcome?
Bibliographic record
Abstract
OBJECTIVE: Although hemispherectomy is an effective treatment for children with intractable hemispheric epilepsy syndromes, as many as 40% of patients eventually develop seizure recurrence. The causes of seizure recurrence in these patients are incompletely understood. The authors sought to evaluate the efficacy of hemispherectomy at their center and determine whether contralateral MRI abnormalities can predict seizure recurrence. METHODS: A retrospective review of consecutive hemispherectomies performed at Miami Children's Hospital between January 2000 and June 2014 was performed. Time-to-event analysis was performed. The "event" was defined as any seizures following resective epilepsy surgery (not including seizures in the first postoperative week and auras). Several preoperative variables were analyzed to determine their suitability to predict seizure recurrence following surgery. RESULTS: Sixty-nine patients (44 boys) with a mean age of 8.2 ± 5.9 years (range 0.1-20.8 years) underwent 72 hemispherectomies; 67 of these were functional hemispherectomies, while another 5 were completion of a previous functional hemispherectomy (2 completions of functional hemispherectomies, 3 anatomical hemispherectomies). The duration of epilepsy was 5.8 ± 5.5 years with 66 cases (91.7%) having daily seizures. Etiology included stroke (n = 28), malformation of cortical development (n = 11), hemimegalencephaly (n = 11), encephalitis (n = 13), and other (n = 7). Engel class I outcome was achieved in 59 (86%) and 56 (81%) patients at 1 and 2 years of follow-up, respectively. The mean time to seizure recurrence was 33.5 ± 31.1 months. In univariate analyses, the absence of contralateral abnormalities on MRI (HR 4.09, 95% CI 1.41-11.89, p = 0.009) was associated with a longer duration of seizure freedom. The presence of contralateral MRI abnormalities was associated with contralateral ictal seizures on preoperative scalp EEG (p = 0.002). Fifteen patients experienced 20 complications (20/72, 27.8%), including the development of hydrocephalus necessitating CSF diversion in 9 cases (13%), hygroma in 1, hemispheric edema in 1, aseptic meningitis in 2, postoperative hemorrhage in 2, infection in 2, ischemic stroke in 2, and blood transfusion-contracted hepatitis C in 1 case. CONCLUSIONS: Patients with bihemispheric abnormalities, as evidenced by contralateral MRI abnormalities, have a higher risk of earlier seizure recurrence following functional hemispherectomy. ABBREVIATIONS: EVD = external ventricular drain; MCD = malformation of cortical development; MEG = magnetoencephalography; PVWM = periventricular white matter; TTE = time-to-event; VPS = ventriculoperitoneal shunt.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".