Analysis of the characteristics of excessive daytime sleepiness in adult patients with obstructive sleep apnea-hypopnea syndrome
- CHEN Jinhui, HUANG Ting, DONG Jie, XU Yong, HAN Jibo, LUO Zhihong, TAO Zezhang
Journal of Otolaryngology and Ophthalmology of Shandong University. 2021, 35(4):
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Objective Clinical and polysomnography(PSG)data of obstructive sleep apnea(OSA)patients with and without excessive daytime sleepiness(EDS)were analyzed to investigate correlation factors for the Epworth Sleepiness Scale(ESS)and to explore the effect of surgical intervention for OSA on patients' level of EDS. Methods In total, 565 adult patients diagnosed with OSAHS using PSG in the otorhinolaryngology clinic of our hospital between June 2018 and June 2019 were analyzed retrospectively. The patients were divided into the non-EDS group(ESS≤10 points)and the EDS group(ESS>10 points)according to their ESS scores, of which 400 were assigned to the non-EDS group and 165 to the EDS group. General clinical data of all patients(such as sex, age, body mass index(BMI), neck and chest circumference, waist-to-hip ratio, etc.), PSG parameters(including indexes of sleep respiratory events such as the apnea-hypopnea index(AHI), nocturnal blood oxygen parameters such as LSaO2 and TS90%, indexes of sleep structure such as the proportion of each sleep period, etc.), and subjective ESS scores were observed; the incidence of EDS and the distribution of the EDS degree were investigated statistically, and the differences in clinical characteristics between the non-EDS and EDS groups were compared. The influencing factors for EDS were explored. Results (1) EDS incidence in adult patients with OSAHS was 29.2%. There were significant differences in sex, age(P=0.001), BMI(P<0.001), level of AHI(P=0.001), and hypoxemia(P<0.001)(P<0.05)between the groups, all of which influenced the incidence of EDS. (2) The distribution of age was similar between the EDS and non-EDS groups(P>0.05). Patients' height(P=0.016), weight(P<0.001), BMI(P<0.001), neck circumference(P<0.001), chest circumference(P=0.002), waist circumference(P<0.001), abdominal circumference(P<0.001), and hip circumference(P=0.002)measurements in the EDS group were all higher than those of patients in the non-EDS group, and all the differences were statistically significant(P<0.05). There were statistically significant differences in total sleep time(P<0.001), sleep efficiency (P=0.003), overall AHI(P<0.001), REM AHI(P=0.001), non-REM AHI(P<0.001), LSaO2(P<0.001), ASaO2(P<0.001), TS90%(P<0.001), oxygen reduction index(P<0.001), microarousal index(P<0.001), maximum apnea time(P<0.001), and other sleep respiratory parameters between the EDS and non-EDS groups(P<0.05). (3) The mean age of daytime sleepiness patients with different degrees of sleepiness was similar, and there were statistical differences in body weight(P=0.002), BMI(P<0.001), neck circumference(P=0.010), chest circumference(P=0.028), waist circumference(P=0.006)and abdominal circumference(P=0.003)(P<0.05). The higher the degree of sleepiness, the longer the sleep duration(P=0.047), The higher sleep efficiency(P=0.019), AHI(P<0.001), REM AHI(P<0.001), and NREM The higher the indexes of AHI(P<0.001), TS90%(P<0.001), oxygen deactivation index(P<0.001), microarousal index(P=0.004), maximum apnea time(P=0.030), morning systolic blood pressure(P=0.047)and diastolic blood pressure(P=0.024),LSaO2(P<0.001)and AsaO2(P<0.001)were gradually decreased, and the differences were statistically significant(P<0.05).(4) The subjective ESS score was significantly correlated with AHI(r=0.263, P<0.001), non-REM AHI(r=0.267, P<0.001), LSaO2(r=-0.266, P<0.001), ASaO2(r=-0.236, P<0.001), TS90%(r=0.240, P<0.001), oxygen reduction index(r=0.275, P<0.001), microarousal index(r=0.253, P<0.001), and maximum apnea duration(r=0.219, P<0.001)(P<0.05). (5) Binary logistic regression analysis showed that TS90%(P=0.001)and oxygen decrease(P=0.029)index were risk factors for EDS(P<0.05). The oxygen decrease index(P<0.001)may determine the degree of daytime sleepiness. Conclusion The incidence of EDS can be affected by sex, age, BMI, AHI, and severity of hypoxemia. The severity of EDS can be influenced by BMI, severity of OSAHS, and hypoxemia level. Compared with the non-EDS group, the EDS group had a longer sleep time, higher sleep efficiency, and a higher index of PSG parameters. TS90% and oxygen decrease index were risk factors for EDS. The oxygen decrease index may determine the degree of daytime sleepiness.