医学
睡眠(系统调用)
数据库
计算机科学
操作系统
作者
Sébastien Bailly,Ludger Grote,Jan Hedner,Sofia Schiza,Walter T. McNicholas,Özen K. Başoğlu,Carolina Lombardi,Zoran Đogaš,G. Roisman,Athanasia Pataka,Maria R. Bonsignore,Jean‐Louis Pépin
出处
期刊:Respirology
[Wiley]
日期:2020-11-02
卷期号:26 (4): 378-387
被引量:57
摘要
ABSTRACT Background and objective To personalize OSA management, several studies have attempted to better capture disease heterogeneity by clustering methods. The aim of this study was to conduct a cluster analysis of 23 000 OSA patients at diagnosis using the multinational ESADA. Methods Data from 34 centres contributing to ESADA were used. An LCA was applied to identify OSA phenotypes in this European population representing broad geographical variations. Many variables, including symptoms, comorbidities and polysomnographic data, were included. Prescribed medications were classified according to the ATC classification and this information was used for comorbidity confirmation. Results Eight clusters were identified. Four clusters were gender‐based corresponding to 54% of patients, with two clusters consisting only of men and two clusters only of women. The remaining four clusters were mainly men with various combinations of age range, BMI, AHI and comorbidities. The preferred type of OSA treatment (PAP or mandibular advancement) varied between clusters. Conclusion Eight distinct clinical OSA phenotypes were identified in a large pan‐European database highlighting the importance of gender‐based phenotypes and the impact of these subtypes on treatment prescription. The impact of cluster on long‐term treatment adherence and prognosis remains to be studied using the ESADA follow‐up data set.
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