title: Validation of overnight oximetry to diagnose patients with moderate to severe obstructive sleep apnea.
abstract: BACKGROUND
  Polysomnography (PSG) is treated as the gold standard for diagnosing obstructive sleep apnea (OSA). However, it is labor-intensive, time-consuming, and expensive. This study evaluates validity of overnight pulse oximetry as a diagnostic tool for moderate to severe OSA patients.
  
  
  METHODS
  A total of 699 patients with possible OSA were recruited for overnight oximetry and PSG examination at the Sleep Center of a University Hospital from Jan. 2004 to Dec. 2005. By excluding 23 patients with poor oximetry recording, poor EEG signals, or respiratory artifacts resulting in a total recording time less than 3 hours; 12 patients with total sleeping time (TST) less than 1 hour, possibly because of insomnia; and 48 patients whose ages less than 20 or more than 85 years old, data of 616 patients were used for further study. By further considering 76 patients with TST < 4 h, a group of 540 patients with TST ≥ 4 h was used to study the effect of insufficient sleeping time. Alice 4 PSG recorder (Respironics Inc., USA) was used to monitor patients with suspected OSA and to record their PSG data. After statistical analysis and feature selection, models built based on support vector machine (SVM) were then used to diagnose moderate and moderate to severe OSA patients with a threshold of AHI = 30 and AHI = 15, respectively.
  
  
  RESULTS
  The SVM models designed based on the oxyhemoglobin desaturation index (ODI) derived from oximetry measurements provided an accuracy of 90.42-90.55%, a sensitivity of 89.36-89.87%, a specificity of 91.08-93.05%, and an area under ROC curve (AUC) of 0.953-0.957 for the diagnosis of severe OSA patients; as well as achieved an accuracy of 87.33-87.77%, a sensitivity of 87.71-88.53%, a specificity of 86.38-86.56%, and an AUC of 0.921-0.924 for the diagnosis of moderate to severe OSA patients. The predictive outcome of ODI to diagnose severe OSA patients is better than to diagnose moderate to severe OSA patients.
  
  
  CONCLUSIONS
  Overnight pulse oximetry provides satisfactory diagnostic performance in detecting severe OSA patients. Home-styled oximetry may be a tool for severe OSA diagnosis.
authors.affiliation: Sleep Medicine Center, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan. lungwen.hang@gmail.com.|Department of Respiratory Therapy, College of Health Care, China Medical University, Taichung, Taiwan. lungwen.hang@gmail.com.
authors.forename: Liang-Wen
authors.initials: LW
authors.lastname: Hang
authors.affiliation: Department of Beauty Science, National Taichung University of Science and Technology, Taichung, Taiwan. charmaine@nutc.edu.tw.
authors.forename: Hsiang-Ling
authors.initials: HL
authors.lastname: Wang
authors.affiliation: Department of Health Services Administration, China Medical University, Taichung, Taiwan. jen801019@yahoo.com.tw.
authors.forename: Jen-Ho
authors.initials: JH
authors.lastname: Chen
authors.affiliation: Department of Internal Medicine, Taipei Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan. jinchyr.hsu@msa.hinet.net.
authors.forename: Jiin-Chyr
authors.initials: JC
authors.lastname: Hsu
authors.affiliation: Department of Management Information System, Central Taiwan University of Science and Technology, Taichung, Taiwan. shlin@ctust.edu.tw.
authors.forename: Hsuan-Hung
authors.initials: HH
authors.lastname: Lin
authors.affiliation: Department of Health Services Administration, China Medical University, Taichung, Taiwan. chung.w53@msa.hinet.net.|Department of Internal Medicine, Taichung Hospital, Ministry of Health and Welfare, Taichung, Taiwan. chung.w53@msa.hinet.net.|Department of Healthcare Administration, Central Taiwan University of Science and Technology, Taichung, Taiwan. chung.w53@msa.hinet.net.
authors.forename: Wei-Sheng
authors.initials: WS
authors.lastname: Chung
authors.affiliation: Department of Health Services Administration, China Medical University, Taichung, Taiwan. yfchen@ctust.edu.tw.|Department of Healthcare Administration, Central Taiwan University of Science and Technology, Taichung, Taiwan. yfchen@ctust.edu.tw.|Department of Dental Technology and Materials Science, Central Taiwan University of Science and Technology, Taichung, Taiwan. yfchen@ctust.edu.tw.
authors.forename: Yung-Fu
authors.initials: YF
authors.lastname: Chen
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010092:Oximetry / Q000379:methods*; D010108:Oxyhemoglobins; D017286:Polysomnography; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis*; D060388:Support Vector Machine
chemical_list: D010108:Oxyhemoglobins