Congenital Tumors of the Central Nervous System: The MCH Experience
Bibliographic record
Abstract
INTRODUCTION: Congenital brain tumors in the younger pediatric population are rare lesions that are histologically distinct from those in the older pediatric population. Malignant histology is common, with persistently poor outcomes despite accessible neuroimaging and evolving adjuvant therapy. There remains scant literature about the natural history of these patients because of rarity and varied institutional experiences. METHODS: A retrospective review was performed of congenital brain tumor patients surgically treated at the Montreal Children's Hospital (MCH) over a 22-year period. Patients presenting in the first year of life were evaluated for demographic information, presenting symptoms, lesion location, and management. Analysis was by median rank test and chi(2) statistics. RESULTS: 13 cases of congenital brain tumors were identified: 5 supratentorial and 8 infratentorial. Median age (p = 0.93) and gender (p = 0.57) did not differ by location, and predominant histologies were choroid plexus papilloma and primitive neuroectodermal tumor. Seizure activity was exclusive to supratentorial lesions (40%, p = 0.03), with hypotonia observed only among infratentorial lesions (50%, p = 0.02). There was equal incidence of hydrocephalus (69%, p = 0.57) and increasing head circumference (38%, p = 0.27) by lesion location. Supratentorial lesions were treated by total resection (n = 3), subtotal resection (n = 1), and biopsy (n = 1). Infratentorial lesions were treated by total resection (n = 1), subtotal resection (n = 2), biopsy (n = 1), no operation (n = 2), and decompressive laminectomy for two spinal lesions. CONCLUSIONS: Congenital brain tumor patients represent fewer than 2% of patients treated at MCH. An evolving understanding of management objectives for these lesions requires understanding institutional experiences. Patients with supratentorial lesions frequently present with seizures, hydrocephalus, and macrocrania, and more frequently underwent total resection at surgery.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".