Seizure Outcome after Resection of Cavernous Malformations Is Better When Surrounding Hemosiderin‐stained Brain Also Is Removed
Bibliographic record
Abstract
PURPOSE: Considering the epileptogenic effect of cavernoma-surrounding hemosiderin, assumptions are made that resection only of the cavernoma itself may not be sufficient as treatment of symptomatic epilepsy in patients with cavernous malformations. The purpose of this study was to test the hypothesis whether seizure outcome after removal of cavernous malformations may be related to the extent of resection of surrounding hemosiderin-stained brain tissue. METHODS: In this retrospective study, 31 consecutive patients with pharmacotherapy-refractory epilepsy due to a cavernous malformation were included. In all patients, cavernomas were resected, and all patients underwent pre- and postoperative magnetic resonance imaging (MRI). We grouped patients according to MRI findings (hemosiderin completely removed versus not/partially removed) and compared seizure outcome (as assessed by the Engel Outcome Classification score) between the two groups. RESULTS: Three years after resection of cavernomas, patients in whom hemosiderin-stained brain tissue had been removed completely had a better chance for a favorable long-term seizure outcome compared with those with detectable postoperative hemosiderin (p=0.037). CONCLUSIONS: Our study suggests that complete removal of cavernoma-surrounding hemosiderin-stained brain tissue may improve epileptic outcome after resection of cavernous malformations.
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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".