P.124 Meta-analysis comparing predictors of good postoperative seizure control in children with dysembryoplastic neuroepithelial tumors and gangliogliomas
Bibliographic record
Abstract
Background: Dysembryoplastic neuroepithelial tumors (DNETs) and gangliogliomas are the most common cause of tumor-related seizures in children and adolescents. Little is known about predictors of surgical success, in terms of seizure freedom. All relevant papers since 1995 were identified. Methods: Over 4000 abstracts were screened on MedLine to identify data comparing tumor type (DNET vs. ganglioglioma) and predictors of post-operative seizure freedom. Results: Seventeen papers were identified encompassing 97 DNET and 95 ganglioglioma patients. Fifteen patients were found with other neuroglial tumors (NGT) or NGT not-otherwise-specified. DNET patients were found to have less frequent seizures, more likely to have second lobe involvement, and to achieve gross total resection. Seizure freedom was achieved in roughly 80% of patients, with no distinction by tumor type, with no surgery-related or peri-operative deaths. For DNETs, seizure freedom was associated with shorter seizure duration, simple lesionectomy, gross total resection, and shorter duration of follow-up. In ganglioglioma patients, seizure freedom was associated with younger age at surgery, secondary generalization (unexpectedly), absence of dysplasia, and gross total resection. Gross total resection was the strongest predictor. Conclusions: Epilepsy surgery for DNET and ganglioglioma had similar outcomes with gross total resection being the strongest predictor.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.031 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".