불면증 정도가 폐쇄성 수면무호흡 증후군에서의 주간졸림 정도에 끼치는 영향
The Effect of Insomnia Severity on Daytime Sleepiness in Obstructive Sleep Apnea Syndrome
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목 적:폐쇄성 수면무호흡 증후군(obstructive sleep apnea syndrome, 이하 OSAS)의 특징적 임상양상으로 주간졸림이 있다. 주간졸림과 수면무호흡의 심각도가 비례하는지에 대해서는 이론이 있다. 이러한 이론에는 불면증 정도가 두변수의 상관관계에 영향을 줄 수 있다는 가정하에 본 연구자들은 피츠버그수면질지수(Pittsburgh Sleep Quality Index, 이하 PSQI) 정도가 주간졸림과 수면무호흡의 심각도의 연관관계에 어떠한 영향을 주는 지에 관해 연구하고자 하였다. 방 법:임상병력 및 야간수면다원검사(nocturnal polysomnography, 이하 NPSG)를 실시하여 OSAS로 진단된 235 명의 남자 환자를 선정하였다. 전체 대상군의 수면 및 기분관련 자가보고척도, 수면다원검사지수, 인구학적 척도를 조사하고 이들 사이의 단순상관분석을 시행하였다. 이후 전체대상군을 PSQI가 5 이하인 A군(n = 75)과 5 초과인 B군(n = 160)으로 나누었다. 각 군에서 제어변수로 벡우울척도(Beck depression inventory, 이하 BDI) 및 벡불안척도(Beck anxiety inventory, 이하 BAI)를 설정하고 엡워스졸림척도(Epworth sleepiness scale, 이하 ESS)와 다른 척도들 간의편상관관계분석을 시행하였다. 마지막으로 A군에서 주간졸림에 영향을 주는 요소를 알아보기 위해 ESS에 대해 다중회귀분석을 시행하였다. 결 과:전체 대상군에서 단순상관분석에서는 ESS와 수면무호흡 심각도 지수들인 무호흡-저호흡 지수(apnea-hypopnea index, 이하 AHI ) (r = 0.148, p = 0.023), 무호흡 지수(ap-nea index, 이하 AI) (r = 0.137, p = 0.036), 저호흡 지수(hy-popnea index, 이하 HI) (r = 0.058, p = 0.377), 산소탈포화도 지수(oxygen desaturation index, 이하 ODI)(r = 0.149, p = 0.022), 각성 총지수(arousal total index, 이하 ATI) (r = 0.129, p = 0.048) 간에 미약한 상관관계를 보이거나 상관관계가 없었다. A군에서 ESS와 AHI (rp = 0.313, p = 0.008), AI (rp = 0.339, p = 0.004), ODI (rp = 0.289, p = 0.015), ATI (rp = 0.256, p = 0.031) 간에 양의 유의한 상관관계를 보였다. B군에서는 ESS와 수면무호흡의 심각도 척도 간에 유의한 상관관계를 보이지 않았다. A군에서 다중회귀분석 결과 ESS에 통계적으로 유의한 영향을 끼치는 요인으로 AI (t = 2.996, p = 0.004), BAI (t = 2.721, p = 0.008)가 있었다. 결 론:주간졸림 정도와 수면무호흡 중증도 간의 유의한 연관성은 A군에서만 관찰되었다. 이 결과는 OSAS 환자가 호소하는 주간졸음을 평가할 때 불면 증상에 대해 고려해야 한다는 것을 시사한다.
Abstract
Objectives: Whether daytime sleepiness is proportional to the severity of sleep apnea in obstructive sleep apnea syndrome (OSAS) is controversial. In this study we investigated how insomnia severity affects the association between daytime sleepiness and sleep apnea severity in OSAS. Methods: The present study included 235 male subjects who were diagnosed with OSAS based on clinical history and nocturnal polysomnography. Pearson’s correlation analysis was conducted among sleep and mood-related self-reported data, polysomnographic data and demographic data of all subjects. Based on Pittsburgh Sleep Quality Index (PSQI), the subjects were divided into 2 groups; group A (n = 75; PSQI ≤5) and group B (n = 160; PSQI > 5). Partial correlation analysis was performed between the Epworth Sleepiness Scale (ESS) and other data in both groups. Multiple linear regression analysis was conducted to investigate the factors which affected the ESS in group A. Results: Pearson’s correlation analysis showed weak or non-existent correlations between ESS and apnea severity data such as apnea-hypopnea index (AHI) (r = 0.148, p = 0.023), apnea index (AI) (r = 0.137, p = 0.036), hypopnea index (HI) (r = 0.058, p = 0.377), oxygen desaturation index (ODI) (r = 0.149, p = 0.022) and arousal total index (ATI) (r = 0.129, p = 0.048). Positive correlations between ESS and apnea severity data such as AHI (rp = 0.313, p = 0.008), AI (rp = 0.339, p = 0.004), ODI (rp = 0.289, p = 0.015) and ATI (rp = 0.256, p = 0.031) were observed only in group A. Multiple regression analysis showed that AI (t = 2.996, p = 0.004) and BAI (t = 2.721, p = 0.008) were associated with ESS in group A. Conclusion: The correlation between daytime sleepiness and sleep apnea severity was shown only in group A. This result suggests that associations between daytime sleepiness in OSAS and sleep apnea severity will become prominent when controlling for insomnia-related variables.
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