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Obstructive sleep apnea (OSA) occurs frequently in people with Down syndrome (DS) with reported prevalences ranging between 55% and 97%, compared to 1-4% in the neurotypical pediatric population. Sleep studies are often uncomfortable, costly, and poorly tolerated by individuals with DS. The objective of this study was to construct a tool to identify individuals with DS unlikely to have moderate or severe sleep OSA and in whom sleep studies might offer little benefit. An observational, prospective cohort study was performed in an outpatient clinic and overnight sleep study center with 130 DS patients, ages 3-24 years. Exclusion criteria included previous adenoid and/or tonsil removal, a sleep study within the past 6 months, or being treated for apnea with continuous positive airway pressure. This study involved a physical examination/medical history, lateral cephalogram, 3D photograph, validated sleep questionnaires, an overnight polysomnogram, and urine samples. The main outcome measure was the apnea-hypopnea index. Using a Logic Learning Machine, the best model had a cross-validated negative predictive value of 73% for mild obstructive sleep apnea and 90% for moderate or severe obstructive sleep apnea; positive predictive values were 55% and 25%, respectively. The model included variables from survey questions, medication history, anthropometric measurements, vital signs, patient's age, and physical examination findings. With simple procedures that can be collected at minimal cost, the proposed model could predict which patients with DS were unlikely to have moderate to severe obstructive sleep apnea and thus may not need a diagnostic sleep study., (© 2017 Wiley Periodicals, Inc.)

Obstructive sleep apnea (OSA) occurs at a high prevalence in patients with Down syndrome (DS). A polysomnogram, which is often cumbersome and challenging, remains the gold standard method of diagnosing OSA. OSA in patients with DS is often attributed to skeletal and soft-tissue structural alterations that are characteristic of the DS phenotype; as such, we hypothesized that assessing anthropometric facial measurements may be predictive of OSA in patients with DS. We used the 3dMDface sterophotography system to capture and create 3D facial images, and we subsequently identified facial landmarks using a single, experienced investigator and utilizing proprietary software to calculate inter-landmark distances and angles. We compared our findings with similar data for neurotypically developing participants. We further compared the findings in participants with DS with and without OSA. Participants with DS had maxillomandibular hypoplasia with smaller ear, nose, and eye measurements compared to neurotypically developing peers. We found no statistically significant differences in 3D photogrammetric measurements between participants with DS with or without OSA. [ABSTRACT FROM AUTHOR]

Study Objectives: The study aimed to compare urinary biomarkers in patients with Down syndrome (DS) with and without obstructive sleep apnea (OSA) to those of age- and sex-matched neurotypically developing healthy controls (HC). We further investigated whether we could predict OSA in patients with DS using these biomarkers.Methods: Urine samples were collected from 58 patients with DS the night before or the morning after their scheduled overnight polysomnogram or both, of whom 47 could be age- and sex-matched to a sample of 43 HC. Concentrations of 12 neurotransmitters were determined by enzyme-linked immunosorbent assay. Log-transformed creatinine-corrected assay levels were normalized. Normalized z-scores were compared between patients with DS vs. HC, between patients with DS with vs. without OSA, and to derive composite models to predict OSA.Results: Most night-sampled urinary biomarkers were elevated among patients with DS relative to matched HC. No urinary biomarker levels differed between patients with DS with vs. without OSA. A combination of four urinary biomarkers predicted AHI > 1 with a positive predictive value of 90% and a negative predictive value of 68%.Conclusions: Having DS, even in the absence of concurrent OSA, is associated with a different urinary biomarker profile when compared to that of HC. Therefore, while urinary biomarkers may be predictive of OSA in the general pediatric population, a different approach is needed in interpreting urinary biomarker assays in patients with DS. Certain biomarkers also seem promising to be predictive of OSA in patients with DS. No clinical trial was indicated in the undertaking of this work. [ABSTRACT FROM AUTHOR]