Obstructive Sleep Apnea and Mental Health Disorders in the Pediatric Population: A Retrospective, Population-Based Cohort Study
Bibliographic record
Abstract
Abstract Rationale Information is limited about the association between obstructive sleep apnea (OSA) and mental health disorders in children. Objectives In children, 1) to evaluate the association between OSA and new mental healthcare encounters; and 2) to compare mental healthcare encounters 2 years after to 2 years before OSA treatment initiation. Methods We conducted a retrospective longitudinal cohort study using Ontario health administrative data (Canada). Children (0–18 yr) who underwent diagnostic polysomnography (PSG) 2009–2016 and met criteria for definition of moderate-severe OSA (PSG-OSA) were propensity score weighted by baseline characteristics and compared with children who underwent PSG in the same period but did not meet the OSA definition (PSG-No-OSA). Children were followed until March 2021. Weighted cause-specific Cox proportional hazards and modified Poisson regression models were used to compare time from PSG to first mental healthcare encounter and frequency of new mental healthcare encounters per person time, respectively. Among those who underwent adenotonsillectomy (AT) or were prescribed and claimed positive airway pressure therapy (PAP), we used age-adjusted conditional logistic regression models to compare 2 years post-treatment to pretreatment odds of mental healthcare encounters. Results Of 32,791 children analyzed, 7,724 (23.6%) children met criteria for moderate-severe OSA. In the PSG-OSA group, 7,080 (91.7%) were treated (AT or PAP). Compared with PSG-No-OSA, the PSG-OSA group had a shorter time from PSG to first mental healthcare encounter (hazard ratio, 1.08; 95% confidence interval [CI], 1.05–1.12) but less frequent mental healthcare encounters in follow-up (rate ratio, 0.92; 95% CI, 0.87–0.97). OSA treatment (AT or PAP) was associated with lower odds of mental healthcare encounters 2 years after treatment initiation compared with 2 years before (odds ratio, 0.69; 95% CI, 0.65–0.74). Conclusions In this large, population-based study of children who underwent PSG for sleep disorder assessment, OSA diagnosis/treatment was associated with an improvement in some mental health indicators, such as fewer new mental healthcare encounters compared with no OSA and lower odds of mental healthcare encounters compared with before OSA treatment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".