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Clusters of sleep apnoea phenotypes: A large pan‐European study from the European Sleep Apnoea Database (ESADA)
Author(s) -
Bailly Sébastien,
Grote Ludger,
Hedner Jan,
Schiza Sofia,
McNicholas Walter T.,
Basoglu Ozen K.,
Lombardi Carolina,
Dogas Zoran,
Roisman Gabriel,
Pataka Athanasia,
Bonsignore Maria R,
Pepin JeanLouis
Publication year - 2021
Publication title -
respirology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.857
H-Index - 85
eISSN - 1440-1843
pISSN - 1323-7799
DOI - 10.1111/resp.13969
Subject(s) - medicine , comorbidity , cluster (spacecraft) , medical prescription , disease , population , database , environmental health , computer science , pharmacology , programming language
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.