ISSN 2149-3987 | E-ISSN 2149-553X
Original Article
Predicting Severe Sleep Apnea in Patients with Complaints: Pulse Oximetry and Body Mass Index
1 Department of Otorhinolaryngology, Ankara Numune Training and Research Hospital, Ankara, Turkey  
2 Department of Otorhinolaryngology, Kahramankazan State Hospital, Ankara, Turkey  
3 Department of Otorhinolaryngology, Hitit University School of Medicine, Çorum, Turkey  
Turk Arch Otorhinolaryngol 2018; 56: 149-154
DOI: 10.5152/tao.2018.2928
Key Words: Sleep apnea, diagnosis, polysomnography, body mass index, pulse oximetry
Abstract

 

Objective: An adequate evaluation combined with an easily accessible test would be a useful way to direct the appropriate patients to sleep centers in circumstances with a limited opportunity for polysomnography (PSG). For this reason, it is necessary to use a screening method prior to PSG evaluation. The aim of the present study was to investigate whether the use of body mass index (BMI) and pulse oximetry is sufficient to predict the severity of obstructive sleep apnea syndrome (OSAS) without PSG.

 

Methods: A total of 956 patients who were admitted to a tertiary referral center with complaints of witnessed apnea, excessive daytime sleepiness, and previously performed PSG were included in the study. Data of PSG (included pulse oximetry) and BMI were investigated for the determination of cut-off points for parameters in the patients.

 

Results: Based on the presence of severe OSAS, the cut-off points were ≥31.7 kg/m2 for BMI, <81% for minimum oxygen saturation (Min O2), and ≥14.1 min for sleep time with oxygen saturation <90% (ST90). Severe OSAS risk was found to be higher in patients with BMI ≥31.7 kg/m2, ST90 ≥14.1 min, and Min O2 ≤81% than in those without (OR: 37.173; 95% CI: 22.465–61.510, p=0.001). Specificity and accuracy were 94.85% and 72.49%, respectively, when all three cut-off scores were provided.

 

Conclusion: The appropriate cut-off values obtained from combining BMI and pulse oximetry data can provide accurate results for predicting the severity of OSAS.

 

Cite this article as: Kum RO, Sazak Kundi FC, Baklacı D, Yurtsever Kum N, Güler İ, Yılmaz YF, et al. Predicting Severe Sleep Apnea in Patients with Complaints: Pulse Oximetry and Body Mass Index. Turk Arch Otorhinolaryngol 2018; 56(3): 149-54.

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