Defining the Heterogeneity of Sleep Apnea Syndrome: a Cluster Analysis with Implications for Patient Management

Introduction: Obstructive sleep apnea (OSA) is a complex pathology with heterogeneity that has not been fully characterized to date. Our objective is to identify groups of patients with common clinical characteristics through cluster analysis that could predict patient prognosis, the impact of comorbidities and/or the response to a common treatment. Methods: Cluster analysis was performed using the hierarchical cluster method in 2025 patients in the apnea-HUGU cohort. The variables used for building the clusters included general data, comorbidity, sleep symptoms, anthropometric data, physical exam and sleep study results. Results: Four clusters were identified: (1) young male without comorbidity with moderate apnea and otorhinolaryngological malformations; (2) middle-aged male with very severe OSA with comorbidity without cardiovascular disease; (3) female with mood disorder; and (4) symptomatic male with established cardiovascular disease and severe OSA. Conclusions: The characterization of these four clusters in OSA can be decisive when identifying groups of patients who share a special risk or common therapeutic strategies, orienting us toward personalized medicine and facilitating the design of future clinical trials. (C) 2021 SEPAR. Published by Elsevier Espana, S.L.U. All rights reserved.