STUDY OBJECTIVES: This study aims to investigate the unique characteristics and clinical significance of the nocturnal sleep onset rapid eye movement period (nSOREMP) in the Chinese population with narcolepsy, enhancing our understanding and management of the disorder globally. METHODS: This retrospective analysis investigated narcolepsy in Chinese patients from six hospitals, using International Classification of Sleep Disorders. A parallel retrospective analysis of the Chinese Clinical Sleep Database (CCSD) focused on polysomnography (PSG) records was conducted to evaluate nSOREMP prevalence in other sleep disorders. RESULTS: The study found a 2.51% nSOREMP prevalence in other sleep disorders of CCSD. Significant differences in age, N2 and rapid eye movement (REM) percentages, REM latency, and various indexes were noted among narcolepsy with/without nSOREMP, and other sleep disorders with nSOREMP of CCSD. nSOREMP prevalence in NT1 was 33.33% and in NT2, 28.30%. Noteworthy disparities in NT1 included N2 percentages, REM latency, and SOREMPs in Multiple Sleep Latency Test (MSLT). In NT2, differences were significant in age, sleep latency, N2 and REM latencies, arousal index, mean sleep latency in MSLT, and MSLT SOREMPs. CONCLUSIONS: This study highlights the distinct characteristics of nSOREMP in the Chinese population. Patients exhibiting symptoms suggestive of the onset of narcolepsy are advised to undergo an MSLT, irrespective of the occurrence of SOREMP during nocturnal PSG.
Purpose: In this study, we established the Chinese Clinical Sleep Database (CCSD), aiming to provide a safe, scalable, and user-friendly database that includes high-quality clinical data from Chinese population to facilitate sleep research. Material and Methods: We collect individual's demographic data, scales, anthropometric measurements, clinical diagnosis, and polysomnography (PSG) recordings from the routine medical process of sleep medicine centers using standardized procedures. The distributed cluster storage technology are utilized to store these data. The structured data are stored in a high-performance MySQL database, while the unstructured data are stored in an object storage service. And we have developed an online data platform to share and manage our data. Results: The data collection has been conducted in three hospitals. In the preliminary stage of data collection (from October 18, 2022 to September 4, 2023), our database included a total of 1183 patients. Among them, 56.8% were male and their ages ranged from 3 to 88 years. These patients were diagnosed with various types of sleep disorders. Conclusion: Since the CCSD's inception, it has demonstrated good stability, security, and scalability. As an public database, the CCSD also exhibits user-friendliness. The CCSD contains comprehensive clinical data, which can contribute to the advancement of the diagnosis and treatment strategies for sleep disorders, ultimately promoting sleep health.
