Bipolar Electrocoagulation on Cortex after AVMs Lesionectomy for Seizure Control
Bibliographic record
Abstract
BACKGROUND: The findings of previous studies remain controversial on the optimal management required for effective seizure control after surgical excision of arteriovenous malformations (AVMs). We evaluated the efficacy of additional bipolar electrocoagulation on the electrically positive cortex guided by intraoperative electrocorticography (ECoG) for controlling cerebral AVMs-related epilepsy. CLINICAL MATERIAL AND METHODS: Sixty consecutive patients with seizure due to cerebral AVMs, who underwent surgical excision of cerebral AVMs and intraoperative ECoG, were assessed. The AVMs and surrounding hemosiderin stained tissue were completely removed, and bipolar electrocoagulation was applied on the surrounding cerebral cortex where epileptic discharges were monitored via intraoperative ECoG. Patients were followed up at three to six months after the surgery and then annually. We evaluated seizure outcome by using Engel's classification and postoperative complications. RESULTS: Forty-nine patients (81.6%) were detected of epileptic discharges before and after AVMs excision. These patients underwent the removal of AVMs plus bipolar electrocoagulation on spike-positive site cortex. After electrocoagulation, 45 patients' epileptic discharges disappeared, while four obviously diminished. Fifty-five of 60 patients (91.7%) had follow-up lasting at least 22 months (mean 51.1 months; range 22-93 months). Determined by the Engel Seizure Outcome Scale, 39 patients (70.9%) were Class I, seven (12.7%) Class II, five (9.0%) Class III, and four (7.2%) Class IV. CONCLUSION: Even after the complete removal of AVM and surrounding gliotic and hemosiderin stained tissue, a high-frequency residual spike remained on the surrounding cerebral cortex. Effective surgical seizure control can be achieved by carrying out additional bipolar electrocoagulation on the cortex guided by the intraoperative ECoG.
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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 | 0.000 | 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".