Abstract WMP118: The Association Between Sleep Related Breathing Disorders and Neuropsychological Function in Pediatric Stroke
Bibliographic record
Abstract
Introduction: Sleep-related breathing disorders (SRBDs) in childhood are associated with adverse outcomes including developmental and behavioral disorders. The association of SRBDs with pediatric stroke is poorly understood. We aimed to assess the risk of SRBDs in children with stroke or non-stroke high risk arteriopathies (NSA) and to evaluate their association with cognitive and behavioral function. Hypothesis: Children with stroke or NSA have a higher rate of SRBD and associated poor cognitive and behavioral function. Methods: We conducted a cross-sectional study of children with arterial ischemic stroke (AIS), cerebral sinovenous thrombosis (CSVT) and NSA such as moyamoya. All children completed the Pediatric Sleep Questionnaire (PSQ). High risk for SRBDs was defined as a PSQ score ≥0.33. Children completed the Adaptive Behavior Assessment System (ABAS-2) parent and teacher forms and/or The Wechsler Intelligence Scale for Children (WISC-V) within 1 year of completing the PSQ. Results: Overall, 213 were included (54% males, median age: 9 years [IQR 5-14]). Forty-nine children (23%) were at high risk of SRBDs. The risk of SRBDs did not vary with age, gender or stroke subtype: AIS (25%), CSVT (20%), other stroke subtypes (20%) and NSA (24%) (p= 0.8). Children with SRBD had higher mean BMI z-scores (0.9±1.5 vs 0.4±1.3, p=0.06). Twenty-four and 15 children underwent ABAS-2 parent and teacher assessment, respectively. The global adaptive composite scores of both forms significantly correlated with the total PSQ scores (r s =-0.6, p<0.01 for the parent form and r s =-0.63, p=0.01 for the teacher form). Correlation coefficients remained statistically significant upon controlling for BMI. In 19 children who completed the WISC-V, those at risk of SRBDs (n=7) had significantly lower Full Scale IQ (70±24.7 vs 91±17, p=0.03), processing speed (55±44 vs 96±19, p=0.02) and working memory (77±23 vs 98±15, p=0.02) compared to children at no risk. Cognitive and behavioral function did not differ across stroke subtypes. Conclusions: Pediatric stroke or NSA is commonly associated with SRBDs which in turn is linked to significant decline in cognitive and behavioral function. Further studies are required to understand the underlying pathological mechanisms.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".