Clinical Features and Correlates of Excessive Daytime Sleepiness in Parkinson's Disease - Xiang, Ya-qin; Xu, Qian; Sun, Qi-ying; Wang, Zhi-qin; Tian, Yun; Fang, Liang-juan; Yang, Yang; Tan, Jie-qiong; Yan, Xin-xiang; Tang, Bei-sha; Guo, Ji-feng (Frontiers in Neurology, 2019)
Objective: To explore clinical features and correlates of Parkinson's disease (PD) patients with excessive daytime sleepiness (EDS) in Chinese population. Methods: Clinically established or probable PD patients were recruited. Demographic data, basic medical history, lifestyle and environmental factors were collected, participants were evaluated using standardized assessment protocols. Patients were divided into PD with EDS group or without EDS group based on the Epworth Sleepiness Scale (ESS) score, with a cutoff of 10. Clinical manifestations were compared between patients with or without EDS, and correlates of EDS were also studied. In addition, the relationship between EDS and poor nighttime sleep quality was analyzed. Results：A total of 1221 PD patients were recruited into our study. Mean ESS (min, max) score was 7.6 (0, 24), 34.1% patients had ESS≧10. No difference was seen in lifestyle (except for alcohol drinking), environmental factors, motor subtype, BMI, initial presentation of motor symptoms, wearing off and levodopa equivalent dose (LED). Patients with EDS had an older average age and a lower education degree. Moreover, older age at PD onset, higher proportion of male and longer disease duration were found in EDS group. The patients with EDS had higher Hoehn-Yahr scales, higher Unified Parkinson’s Disease Rating Scale (UPDRS) partⅠ, partⅡ, partⅢ score, more severer non-motor symptom, poorer quality of sleep and life. Logistic regression analyses demonstrated that EDS was associated with male sex, age, probable rapid eye movement sleep behavior disorder (pRBD), PD-related sleep problems, cognitive impairment, and worse quality of life (QoL). Conclusion: EDS is a general clinical manifestation in PD. Our study proved that many factors were associated with EDS. Understanding the clinical characteristics of EDS in PD patients are helpful to identify the EDS early, improve QoL and reduce the occurrence of accidents.