Neurosurgical management of intracranial epidermoid tumors in children
Bibliographic record
Abstract
OBJECT: Epidermoid tumors are benign lesions representing 1% of all intracranial tumors. There have been few pediatric series of intracranial epidermoid tumors reported previously. The authors present their experience in the management of these lesions. METHODS: The neurosurgical database at the Hospital for Sick Children was searched for children with surgically managed intracranial epidermoid tumors. The patients' charts were reviewed for demographic data, details of clinical presentation, surgical therapy, and follow-up. Ethics board approval was obtained for this study. RESULTS: Seven children, all girls, were identified who met the inclusion criteria between 1980 and 2007. The average age at surgery was 11.2 years (range 8-15 years), and the mean maximal tumor diameter was 2.1 cm. Headache was the most common presenting symptom, and 1 tumor was found incidentally. Most patients had normal neurological examinations, but meningism was found in 2 cases. There were 3 cerebellopontine angle lesions, 1 pontomedullary lesion, and 3 supratentorial tumors. Hydrocephalus developed in 1 patient after aseptic meningitis, and she underwent shunt placement. There were no operative deaths. Complete resection could be performed in 2 patients. One patient experienced a small recurrence that did not require a repeated operation, while 1 subtotally resected lesion recurred and the patient underwent a second operation. CONCLUSIONS: Intracranial epidermoid tumors are rare in the pediatric population. Total resection is desirable to minimize the risk of postoperative aseptic meningitis, hydrocephalus, and tumor recurrence. Aggressive neurosurgical resection may be associated with cranial nerve or ischemic deficits, however. In these cases, neurosurgical judgment at the time of surgery is warranted to ensure maximum resection while minimizing postoperative neurological deficits.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".