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Validation of a predictive model for obstructive sleep apnea in people with Down syndrome |
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| Authors: | Brian G. Skotko Alexandra Garza Flores Ibrahim Elsharkawi Vasiliki Patsiogiannis Mary Ellen McDonough Damiano Verda Marco Muselli Roberto Hornero David Gozal Eric A. Macklin |
| Affiliation: | 1. Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA;2. Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA Department of Genetics, Cook Children's Hospital, Fort Worth, Texas, USA;3. Down Syndrome Program, Division of Medical Genetics and Metabolism, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA Mitochondrial Medicine, Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA;4. Rulex Innovation Labs, Genoa, Italy;5. Rulex Innovation Labs, Genoa, Italy Institute of Electronics, Computer and Telecommunication Engineering, National Research Council of Italy, Genoa, Italy;6. Biomedical Engineering Group, University of Valladolid, Valladolid, Spain Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain;7. Department of Child Health and The Child Health Research Institute, The University of Missouri School of Medicine, Columbia, Missouri, USA;8. Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA |
| Abstract: | Detecting obstructive sleep apnea (OSA) is important to both prevent significant comorbidities in people with Down syndrome (DS) and untangle contributions to other behavioral and mental health diagnoses. However, laboratory-based polysomnograms are often poorly tolerated, unavailable, or not covered by health insurance for this population. In previous work, our team developed a prediction model that seemed to hold promise in identifying which people with DS might not have significant apnea and, consequently, might be able to forgo a diagnostic polysomnogram. In this study, we sought to validate these findings in a novel set of participants with DS. We recruited an additional 64 participants with DS, ages 3–35 years. Caregivers completed the same validated questionnaires, and our study team collected vital signs, physical exam findings, and medical histories that were previously shown to be predictive. Patients then had a laboratory-based polysomnogram. The best modeling had a validated negative predictive value of 50% for an apnea–hypopnea index (AHI) > 1/hTST and 73.7% for AHI >5/hTST. The positive predictive values were 60% and 39.1%, respectively. As such, a clinically reliable screening tool for OSA in people with DS was not achieved. Patients with DS should continue to be monitored for OSA according to current healthcare guidelines. |
| Keywords: | Down syndrome obstructive sleep apnea trisomy 21 |