1090 Routine Screening for Excessive Daytime Sleepiness in Pediatric Brain Tumor
Bibliographic record
Abstract
Abstract Introduction Youth with brain tumor may experience excessive daytime sleepiness (EDS) associated with central disorders of hypersomnolence (CDH).1 EDS impairs daily functioning, negatively affects mood and quality of life, and further exacerbates cognitive and academic difficulties associated with brain tumor.2 The aim of this study is to summarize findings from universal screening of these issues in pediatric brain tumor. Methods Youth receiving treatment or surveillance for pediatric brain tumor presenting to inpatient or outpatient settings were screened for symptoms of EDS using the Modified Epworth Sleepiness Scale (M-ESS) and the Pediatric Hypersomnolence Survey (PHS). A cut off score of 6 was utilized on the M-ESS.3 The PHS has not yet been used in pediatric cancer, therefore, it was trialed to determine level of agreement with other screening methods. The standard cut off score of 24 or 8 on the sleepiness subscale score was used. Elevated ratings were discussed with the primary oncologist, and a referral was made to Sleep Medicine if deemed necessary. Results Eighteen youth with brain tumor completed screening for sleep problems (61% Low Grade Astrocytoma, 83.3% White). A total of 38.9% (n=7) scored above the cut off on the M-ESS, indicating concern for EDS. On the PHS, a total of 16.6% (n = 3) scored above the cut off for Total score and the Sleepiness subscale, indicating concern for narcolepsy or hypersomnia. Three (16.6%) participants were referred to Sleep Medicine for further evaluation and three others (16.6%) were already established with Sleep Medicine at the time of screening. Conclusion EDS and CDH may be common in pediatric brain tumor.1,2 Screening measures led to increased referral to Sleep Medicine. Despite this, due to discrepancy between measures, further research is needed to determine the best screening methods to accurately determine the presence of EDS in pediatric brain tumor. Support (if any) This study is supported by the Kentucky Pediatric Cancer Research Trust Fund.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".