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01.12.2015 | Research article | Ausgabe 1/2015 Open Access

BMC Pulmonary Medicine 1/2015

Validation of overnight oximetry to diagnose patients with moderate to severe obstructive sleep apnea

BMC Pulmonary Medicine > Ausgabe 1/2015
Liang-Wen Hang, Hsiang-Ling Wang, Jen-Ho Chen, Jiin-Chyr Hsu, Hsuan-Hung Lin, Wei-Sheng Chung, Yung-Fu Chen
Wichtige Hinweise

Competing interests

The authors declare that they do not have competing interests.

Authors’ contributions

These authors’ individual contributions were as follows. Conception and design: LWH, JHC, WSC, and YFC. Administrative support: LWH, HLW, and HHL. Collection and assembly of data: All authors. Data analysis and interpretation: WSC and YFC. Manuscript writing: All authors. Final approval of manuscript: All authors.



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.


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.


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.


Overnight pulse oximetry provides satisfactory diagnostic performance in detecting severe OSA patients. Home-styled oximetry may be a tool for severe OSA diagnosis.
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