[Diagnosis of obstructive sleep apnea syndrome using pulse oximeter derived photoplethysmographic signals]

Zhonghua Yi Xue Za Zhi. 2016 May 24;96(19):1527-9. doi: 10.3760/cma.j.issn.0376-2491.2016.19.014.
[Article in Chinese]

Abstract

Objective: To evaluate the diagnosis value of photoplethysmography (PPG)-based device for detecting obstructive sleep apnea syndrome.

Methods: Patients who visited sleep medicine center in West China hospital from March 2014 to March 2015 with a main complain of snoring were selected into this study, and they were simultaneously monitored with the PPG-based device while undergoing polysomnography (PSG). Using PSG as"gold standard", the sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) as well as corresponding areas under the receiver operator curves for an apnea hypopnea index (AHI) ≥5/h, ≥15/h and ≥30/h were calculated for PPG.

Results: Valid results were available for 93 subjects, among them there were 64 men and 29 women with a mean age of (44±13) years old.There were no significant difference between total sleep time, wake time after sleep onset, AHI and oxygen saturation derived by PPG and PSG.Positive correlation was found between PPG-derived and PSG-derived AHI (r=0.945). For AHI≥5/h, ≥15/h and ≥30/h respectively according PSG, sensitivity was 93%, 88%, 92%, specificity was 79%, 93%, 95%, PPV was 95%, 97%, 96%, NPV 75%, 76%, 91% for PPG. The corresponding areas under the receiver operator characteristic curves were 0.981, 0.996 and 0.995 respectively.

Conclusion: PPG-derived data is consistent with simultaneous in-lab PSG in the diagnosis of obstructive sleep apnea syndrome.

MeSH terms

  • Adult
  • China
  • Female
  • Humans
  • Male
  • Middle Aged
  • Oximetry / methods*
  • Oxygen
  • Photoplethysmography / methods*
  • Polysomnography*
  • ROC Curve
  • Sensitivity and Specificity
  • Sleep
  • Sleep Apnea, Obstructive / diagnosis*
  • Sleep Apnea, Obstructive / physiopathology
  • Snoring / etiology*

Substances

  • Oxygen