Relationship Between Polysomnographic Sleep Architecture and Behavior in Medication-free Children with TS, ADHD, TS and ADHD, and Controls
Bibliographic record
Abstract
OBJECTIVE: To describe the relationship between sleep architecture and behavioral measures in unmedicated children and adolescents with Tourette syndrome (TS), attention-deficit hyperactivity disorder (ADHD), TS and comorbid ADHD (TS + ADHD), and healthy controls. The study also set out to examine differences in sleep architecture with each diagnosis. METHOD: A cross-sectional, 2-night consecutive polysomnographic sleep study was conducted in 90 children. All participants were matched for age, gender, and level of intelligence. RESULTS: Scores on the Child Behavior Checklist delinquency measure were modestly but significantly correlated with the number of movements during REM sleep (r = .36, p = .003). Significant correlations were also noted among the number of total arousals and arousals from slow wave sleep (SWS), and scores on the measures of conduct disorder, hyperactivity/immaturity, and restless/disorganized behaviors. There were a few significant differences in sleep architecture among the diagnostic groups. The ADHD-only group exhibited a significantly higher number of total arousals (p < .01) and arousals from SWS (p < .01) compared with the other three study groups. DISCUSSION: Our findings indicate that children with TS and/or ADHD and who have more arousals from sleep are significantly more likely to have issues with conduct disorder, hyperactivity/immaturity, and restless/disorganized behavior. It was also noted that having ADHD, alone or comorbid with TS, is associated with a significantly greater number of movements during both non-REM and REM sleep. This study underscores the compelling need for the diagnosis and treatment of any sleep disorders in children with TS and/or ADHD so as to facilitate better management of problem behaviors.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".