Vascular consequences of operculoinsular corticectomy for refractory epilepsy
Bibliographic record
Abstract
OBJECT: Surgery in the insular region is considered challenging because of its vascular relationships, the proximity of functional structures, and its deep location in the sylvian fissure. The authors report the incidence and consequences of ischemic lesions after operculoinsular corticectomy for refractory epilepsy. METHODS: The authors retrospectively reviewed the data of all patients who underwent an insular resection with or without an opercular resection for refractory epilepsy at their center. All patients underwent postoperative MRI, enabling a radiological analysis of the ischemic lesions as a result of the corticectomies. The resections were classified according to the location and extent of the insular corticectomy and the type of operculectomy. Each patient underwent clinical follow-up. RESULTS: Twenty patients underwent surgery. All patients underwent insular corticectomy with or without an operculectomy. Ischemic lesions were identified in 12 patients (60%). In these patients, 11 ischemic lesions (55%) were related to the insular corticectomy, and 1 was related to the associated periinsular resection. The ischemic lesions associated with the insulectomies were typically located in the corona radiata running from the insula to the periventricular region. Nine patients (45%) developed a postoperative neurological deficit, among whom 6 (67%) had an insular corticectomy-related ischemic lesion. All reported neurological deficits were transient. Five patients (25%) had ischemic lesions without neurological deficit. CONCLUSIONS: Operculoinsular corticectomies are associated with ischemic lesions in approximately 60% of patients. However, given that no patient had a definitive postoperative deficit, these ischemic lesions have few clinical consequences. Therefore, this surgical procedure can be considered reasonably safe for the treatment of refractory epilepsy.
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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 | 0.000 |
| 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) | 0.002 | 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".