Predictors of Excessive Daytime Sleepiness in Korean Snoring Patients.
- Author:
Kyong Jin SHIN
1
;
Sung Eun KIM
;
Sam Yeol HA
;
Jin Se PARK
;
Bong Soo PARK
;
Jung Hyeob SOHN
;
Kang Min PARK
Author Information
1. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea. smilepkm@hanmail.net
- Publication Type:Original Article
- Keywords:
Age;
Snoring;
Daytime Sleepiness;
Epworth Sleepiness Scale
- MeSH:
Diagnosis;
Humans;
Linear Models;
Sleep Apnea, Obstructive;
Snoring*
- From:Journal of Rhinology
2014;21(2):103-107
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: Excessive daytime sleepiness is one of the most common symptoms in snoring patients. However, the reason why some individuals complain of daytime sleepiness and others do not is unclear. In this study, we evaluated snoring individuals and examined several demographic and polysomnographic profiles in an attempt to identify predictors of excessive daytime sleepiness. METHODS: The inclusion criteria for patients were the following: 1) patients who underwent an overnight polysomnograph, 2) patients with the chief complaint of snoring, and 3) patients who completed the Korean version of the Epworth sleepiness scale. We used the Epworth sleepiness scale to estimate excessive daytime sleepiness. We quantified correlations between the Epworth sleepiness scale and the demographic/polysomnographic parameters. We also analyzed the parameters affecting excessive daytime sleepiness using multiple linear regression analysis. RESULTS: One hundred nineteen patients met the inclusion criteria for this study. Multiple regression analysis showed that young age was the only independent variable showing statistical significance for predicting excessive daytime sleepiness, and was well-correlated with the Epworth sleepiness scale. However, there were no polysomnographic parameters that were predictive. CONCLUSIONS: Clinicians need to be cautious when using the Epworth sleepiness scale for the diagnosis of obstructive sleep apnea and determining the response to treatment.
