Neurocognitive outcome 12 months following cerebellar mutism syndrome in pediatric patients with medulloblastoma
Bibliographic record
Abstract
The aim is to prospectively assess early neurocognitive outcome of children who developed cerebellar mutism syndrome (CMS) following surgical resection of a posterior fossa embryonal tumor, compared with carefully matched control patients. Children who were enrolled on an ongoing IRB-approved protocol for treatment of embryonal tumors, were diagnosed with postoperative CMS, and had completed prospectively planned neuropsychological evaluation at 12 months postdiagnosis were considered eligible. The cognitive outcomes of these patients were examined in comparison to patients without CMS from the same treatment protocol and matched with regard to primary diagnosis, age at diagnosis, and risk/corresponding treatment (n = 22 pairs). Seventeen were also matched according to gender, and 14 were also matched according to race. High-risk patients received 36-39.6 Gy CSI and 3D conformal boost to the primary site to 55.8-59.4 Gy. Average-risk patients received 23.4 Gy CSI and 3D conformal boost to the primary site to 55.8 Gy. Significant group differences were found on multiple cognitive outcomes. While the matched control patients exhibited performance in the average range, patients who developed CMS postsurgery were found to have significantly lower performance in processing speed, attention, working memory, executive processes, cognitive efficiency, reading, spelling, and math. Patients treated for medulloblastoma who experience postoperative CMS show an increased risk for neurocognitive impairment, evident as early as 12 months following diagnosis. This study highlights the need for careful follow-up with neuropsychological evaluation and for obtaining critical support for patients and their families.
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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 | 0.000 |
| 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) | 0.000 | 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 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".