Risk factors for postoperative cerebellar mutism syndrome in pediatric patients: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: A review article assessing all the risk factors reported in the literature for postoperative cerebellar mutism syndrome (pCMS) among children remains absent. The authors sought to perform a systematic review and meta-analysis to evaluate this issue. METHODS: PubMed, Embase, and Web of Science were queried to systematically extract potential references. The articles relating to pCMS were required to be written in the English language, involve pediatric patients (≤ 18 years of age), and provide extractable data, which included a comparison group of patients who did not develop pCMS. The quality of the included studies was evaluated using the Newcastle-Ottawa Scale. Data were pooled using RevMan 5.4, and publication bias was assessed by visual inspection for funnel plot asymmetry. The study protocol was registered through PROSPERO (ID: CRD42021256177). RESULTS: Overall, 28 studies involving 2276 patients were included. Statistically significant risk factors identified from univariate analysis were brainstem invasion (OR 4.28, 95% CI 2.23-8.23; p < 0.0001), fourth ventricle invasion (OR 12.84, 95% CI 4.29-38.44; p < 0.00001), superior cerebellar peduncle invasion (OR 6.77, 95% CI 2.35-19.48; p = 0.0004), diagnosis of medulloblastoma (OR 3.26, 95% CI 1.93-5.52; p < 0.0001), medulloblastoma > 50 mm (OR 8.85, 95% CI 1.30-60.16; p = 0.03), left-handedness (OR 6.57, 95% CI 1.25-34.44; p = 0.03), and a vermis incision (OR 5.44, 95% CI 2.09-14.16; p = 0.0005). On the other hand, a tumor located in the cerebellar hemisphere (OR 0.23, 95% CI 0.06-0.92; p = 0.04), cerebellar hemisphere compression (OR 0.23, 95% CI 0.11-0.45; p < 0.0001), and intraoperative imaging (OR 0.36, 95% CI 0.18-0.72; p = 0.004) reduced the risk of pCMS. CONCLUSIONS: This study provides the largest and most reliable review of risk factors associated with pCMS. Although some risk factors may be dependent on one another, the data may be used by surgeons to better identify patients at risk for pCMS and for intervention planning.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".