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Am J Med Genet A. 2017 Jan 26. doi: 10.1002/ajmg.a.38137. [Epub ahead of print]

A predictive model for obstructive sleep apnea and Down syndrome.

Author information

  • 1Down Syndrome Program, Division of Medical Genetics, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts.
  • 2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.
  • 3Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
  • 4Rulex, Inc., Boston, Massachusetts.
  • 5Institute of Electronics, Computer, and Telecommunication Engineering, Italian National Research Council, Genoa, Italy.
  • 6Down Syndrome Program, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts.
  • 7Department of Orthodontics, The University of Iowa College of Dentistry and Dental Clinics, Iowa City, Iowa.
  • 8Division of Orthodontics, Department of Craniofacial Sciences, University of Connecticut School of Dental Medicine, Farmington, Connecticut.
  • 9Department of Dentistry, Boston Children's Hospital, Boston, Massachusetts.
  • 10Children's Dentistry, El Cerrito, California.
  • 11Beth Israel Deaconess Medical Center, Boston, Massachusetts.
  • 12Department of Pediatrics, University of Chicago, Chicago, Illinois.
  • 13Division of Respiratory Diseases, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts.


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.


Down syndrome; obstructive sleep apnea; trisomy 21

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