title: Detection of sleep apnea by case-finding and home monitoring with Somnolter®: a pilot study.
abstract: BACKGROUND
  Obstructive sleep apnea and hypopnea syndrome (OSAHS) is a disorder that causes clinical symptoms (e.g. snoring, excessive daytime sleepiness and impaired concentration) that may increase the risk of traffic accidents, cardiovascular disease, type 2 diabetes and reduce the quality of life. A recently developed device (Somnolter®) detects apneas and hypopneas in a home setting, allowing to detect OSAHS in a more comfortable environment compared to the gold standard polysomnography. The aim of our study was to investigate whether the Somnolter® is useful in family practice to identify patients with OSAHS.
  
  
  METHODS
  Questionnaires were offered to patients in five general practitioner (GP) practices.Based on the questionnaire and body mass index, patients with an increased risk of OSAHS were contacted to collaborate in the study. In this convenience sample, 18 patients were successfully tested with the Somnolter® measuring SaO2, mandibular movements, body position, heart rate, nasal air flow and thoracic and abdominal breathing movements. The Somnolter® automatically analyses the data and different parameters to detect OSAHS. Afterwards, the data were manually revised by the researchers.
  
  
  RESULTS
  Out of 365 subjects, 31 met the inclusion criteria and 18 were successfully tested at home. Sixteen out of 18 patients had an Apnea Hypopnea Index (AHI) ≥ 5, ten of them had mild OSAHS, 3 were categorized as moderate OSAHS and finally 3 matched the criteria of severe OSAHS.
  
  
  CONCLUSIONS
  The proposed case-finding strategy still needs optimization, but is considered helpful in selecting patients at high risk of OSAHS. OSAHS was detected in 14 out of 18 patients tested with the Somnolter®. In the future the Somnolter® might be a feasible alternative to diagnose OSAHS.
authors.forename: Fabienne
authors.initials: F
authors.lastname: Cattrysse
authors.forename: Mathias
authors.initials: M
authors.lastname: Peeters
authors.forename: Sanne
authors.initials: S
authors.lastname: Calaerts
authors.forename: Karen
authors.initials: K
authors.lastname: Ferson
authors.affiliation: Department of Public Health and Primary Care, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. jan.degryse@med.kuleuven.be.
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Degryse
mesh_terms: D000328:Adult; D000368:Aged; D001331:Automation; D015415:Biomarkers / Q000097:blood; D015992:Body Mass Index; D004867:Equipment Design; D005194:Family Practice; D005260:Female; D006339:Heart Rate; D006699:Home Care Services; D006801:Humans; D008297:Male; D008334:Mandible / Q000503:physiopathology; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D009038:Motion; D010100:Oxygen / Q000097:blood; D010865:Pilot Projects; D011237:Predictive Value of Tests; D012119:Respiration; D012307:Risk Factors; D012720:Severity of Illness Index; D012891:Sleep Apnea Syndromes / Q000097:blood / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology / Q000628:therapy; D011795:Surveys and Questionnaires
chemical_list: D015415:Biomarkers; D010100:Oxygen