Predictors of sleep disordered breathing in children with Down syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
Children with Down syndrome are at increased risk of sleep disordered breathing (SDB). SDB is associated with significant morbidity including neurocognitive impairment, cardiometabolic disease and systemic inflammation. The identification of clinical markers that may predict SDB is critical in facilitating early diagnosis and treatment, and ultimately, preventing morbidity. The objective of this systematic review was to identify predictors of SDB in patients with Down syndrome. A search was conducted using MEDLINE, Embase, the Cochrane Central Register of Controlled Trials and the Cumulative Index to Nursing and Allied Health Literature. A meta-analysis was performed according to the Meta-analyses of Observational Studies in Epidemiology checklist. Our review of the literature identified inconsistent associations between a variety of variables and SDB in children with Down syndrome, although the quality of evidence was poor. Meta-analysis of age and sex identified that children with OSA were older than those without OSA, and there was a similar risk of OSA in males and females, although risk favoured males. Currently, the American Academy of Pediatrics guidelines recommend that children with Down syndrome undergo polysomnography by the age of 4 years. Our review supports the recommendation for routine screening of children with Down syndrome. However, results from our meta-analysis suggest a need for longitudinal screening to diagnose children who may develop SDB as they get older.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.021 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".