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Use of Oximetry As a Screening Tool for Obstructive Sleep Apnea: a Case Study in Taiwan

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Journal J Med Syst
Date 2015 Feb 14
PMID 25677955
Citations 3
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Abstract

Obstructive sleep apnea (OSA) is a relatively common disease in the general population. Patients with OSA have a high risk of various comorbid medical diseases. Polysomnography (PSG) is the current gold standard for diagnosing OSA but is time consuming and expensive. This study aims to identify a sensitive screening parameter that can be used by clinicians to determine the time of referral for PSG examination in Taiwan. Eighty-seven patients, including 67 males and 20 females, were included in this study. We divided the patients into two groups: training data (n = 58) and testing group (n = 29). Pearson χ(2) test was used to perform bivariate analysis, and a decision tree was used to build a model. The decision model selected the frequency of desaturation > 4% per hour (DI4) as the indicator of OSA influence. The testing data accuracy of the C4.5 decision tree was 82.80%. External data were also used to validate the model reliability. The accuracy of the external data was 95.96%. Approximately one-third of patients with DI4 between 11 and 33 suffered from OSA. This population requires further diagnosis. Oximetry is an important and widely available screening method in Taiwan. This study proposes the need for PSG referral if DI4 is between 11 and 33.

Citing Articles

Fusion of Whole Night Features and Desaturation Segments Combined with Feature Extraction for Event-Level Screening of Sleep-Disordered Breathing.

Liu R, Li C, Xu H, Wu K, Li X, Liu Y Nat Sci Sleep. 2022; 14:927-940.

PMID: 35607445 PMC: 9123935. DOI: 10.2147/NSS.S355369.


A novel, simple, and accurate pulse oximetry indicator for screening adult obstructive sleep apnea.

Nigro C, Castano G, Bledel I, Colombi A, Zicari M Sleep Breath. 2021; 26(3):1125-1134.

PMID: 34554375 DOI: 10.1007/s11325-021-02439-4.


A Prognosis Tool Based on Fuzzy Anthropometric and Questionnaire Data for Obstructive Sleep Apnea Severity.

Wang K, Chen K, Huang S, Teng N J Med Syst. 2016; 40(4):110.

PMID: 26932370 DOI: 10.1007/s10916-016-0464-y.

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