Exercise Trials in Pediatric Brain Tumor: A Systematic Review of Randomized Studies
Bibliographic record
Abstract
In pediatric brain tumor patients, treatment advances have increased survival rates to nearly 70%, while consequently shifting the burden of disease to long-term management. Exercise has demonstrated potential in improving multiple health impairments secondary to brain tumor treatment. However, these effects have not been consolidated through review. Therefore, we performed a systematic review of 6 health sciences databases (Medline, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Central Database). Two reviewers screened studies against predefined inclusion criteria, namely that the study must: (i) be pediatric-specific; (ii) examine the effects of an exercise intervention; and (iii) employ a randomized or quasi-randomized trial design. The same 2 reviewers performed data extraction and analyses. From a pool of 4442, 5 articles-based on 2 independent trials-were included in our review (N=41). Exercise interventions were primarily aerobic, but included balance or muscle building components. Exercise had a positive effect on volumetric or diffusion-based neuroimaging outcomes, as well as motor performance and cardiorespiratory fitness. The effects of exercise on cognition remains unclear. Exercise did not worsen any of the outcomes studied. This review captures the state of the science, suggesting a potential role for exercise in children treated for brain tumor.
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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 | 0.014 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".