Editorial: Seizures in brain tumors
Bibliographic record
Abstract
Epileptic seizures can be the first presenting symptom before a diagnosis is confirmed in approximately 30-60% of primary brain tumor patients [1]. In addition, seizures due to tumors of the central nervous system are the second most common cause of epilepsy in adults (following hippocampal sclerosis) or children (following focal cortical dysplasia) [2]. Seizure-related complications can significantly affect clinical prognosis and directly affect quality of life, including mental health [3][4]. In comparison to metastatic lesions and high-grade tumors, such as glioblastoma, a higher seizure incidence is observed in low-grade tumors, especially in association with dysembryoplastic neuroepithelial tumors (DNET) and gangliogliomas, known as "long-term epilepsy-associated brain tumors" (LEATs), as well as oligodendrogliomas and low-grade astrocytomas [5-6]. therapy was adopted by using a higher maintenance dose of lacosamide and levetiracetam by 25% 63 administered 48 hours prior to the surgery. In addition, intravenous infusion of fosphenytoin (20 64 mg/kg) prior to direct electrical stimulation, followed by a maintenance dosing of 300 mg/day for 14 65 days, prevented EPS occurrence. This case highlighted that aggressive prophylactic usage of anti-66 seizure medication therapy perioperatively could be considered in the management of patients with 67 tumor-related epilepsy who are at risk of EPS. Future double-blinded randomized controlled trials are 68 required to further validate and extend these observations. Also, the side effect profile of aggressive 69 prophylactic anti-seizure medications and their effect on postoperative recovery need to be explored. 70Seizure is a common presentation in patients with ganglioglioma; however, some patients still 71 experience postoperative seizures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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".