The Chinese Clinical Sleep Database: An Innovative Database System Includes Large-Scale Clinical Data of Chinese Population.
collaboration tool
data collection
database
methodology
sleep medicine
Journal
Nature and science of sleep
ISSN: 1179-1608
Titre abrégé: Nat Sci Sleep
Pays: New Zealand
ID NLM: 101537767
Informations de publication
Date de publication:
2024
2024
Historique:
received:
19
11
2023
accepted:
12
03
2024
medline:
27
3
2024
pubmed:
27
3
2024
entrez:
27
3
2024
Statut:
epublish
Résumé
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. 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. 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. 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.
Identifiants
pubmed: 38533251
doi: 10.2147/NSS.S450578
pii: 450578
pmc: PMC10964089
doi:
Types de publication
Journal Article
Langues
eng
Pagination
305-313Informations de copyright
© 2024 Fang et al.
Déclaration de conflit d'intérêts
Yuanhui Li, Xiang Liu, and Simin Guo are affiliated with Adai Technology (Beijing) Co., Ltd. The authors report no other conflicts of interest in this work.