Sports and childhood brain tumors: Can I play?
Bibliographic record
Abstract
Abstract Background It is unknown whether children with brain tumors have a higher risk of complications while participating in sports. We sought to estimate the prevalence of such events by conducting a systematic review of the literature, and we surveyed providers involved with pediatric central nervous system (CNS) tumor patients. Methods A systematic review of the literature in the PubMed, Scopus, and Cochrane databases was conducted for original articles addressing sport-related complications in the brain-tumor population. An online questionnaire was created to survey providers involved with pediatric CNS tumor patients about their current recommendations and experience regarding sports and brain tumors. Results We retrieved 32 subjects, including 19 pediatric cases from the literature. Most lesions associated with sport complications were arachnoid cysts (n = 21), followed by glioma (n = 5). The sports in which symptom onset most commonly occurred were soccer (n = 7), football (n = 5), and running (n = 5). We surveyed 111 pediatric neuro-oncology providers. Sport restriction varied greatly from none to 14 sports. Time to return to play in sports with contact also varied considerably between providers. Rationales for limiting sports activities were partly related to subspecialty. Responders reported 9 sport-related adverse events in patients with brain tumor. Conclusions Sport-related complications are uncommon in children with brain tumors. Patients might not be at a significantly higher risk and should not need to be excluded from most sports activities.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".