Dries Testelmans1,2, M A Spruit3,4,5, B Vrijsen6,7, M Sastry8, C Belge6,7, A Kalkanis6,7, S Gaffron9, E F M Wouters3,4,10, B Buyse6,7. 1. Department of Pulmonology, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium. dries.testelmans@uzleuven.be. 2. Department of Chronic Diseases, Metabolism and Ageing, KU Leuven, Leuven, Belgium. dries.testelmans@uzleuven.be. 3. Department of Research and Education, CIRO, Centre of Expertise for Chronic Organ Failure, Horn, The Netherlands. 4. Department of Respiratory Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands. 5. NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht, The Netherlands. 6. Department of Pulmonology, University Hospitals Leuven, Herestraat 49, 3000, Leuven, Belgium. 7. Department of Chronic Diseases, Metabolism and Ageing, KU Leuven, Leuven, Belgium. 8. Academic Sleep Centre, CIRO, Horn, The Netherlands. 9. Analytics, Viscovery Software GmbH, Vienna, Austria. 10. Ludwig Boltzmann Institute for Lung Health, Vienna, Austria.
Abstract
PURPOSE: Obstructive sleep apnea (OSA) is a prevalent and multifaceted disease. To date, the presence and severity of objectively identified comorbidities and their association with specific OSA phenotypes, CPAP adherence, and survival remain to be elucidated. The aim of this study is to cluster patients with OSA based on 10 clinically important objectively identified comorbidities, and to characterize the comorbidity clusters in terms of clinical and polysomnographic characteristics, CPAP adherence, and survival. STUDY DESIGN AND METHODS: Seven hundred ten consecutive patients starting CPAP for moderate-to-severe OSA were included. Comorbidities were based on generally accepted cutoffs identified in the peer-reviewed literature. Self-organizing maps were used to order patients based on presence and severity of their comorbidities and to generate clusters. RESULTS: The majority of patients were men (80%). They were generally middle-aged (52 years) and obese (BMI: 31.5 kg/m2). Mean apnea-hypopnea index (AHI) was 41 ± 20 per h of sleep. More than 94% of the patients had one or more comorbidities with arterial hypertension, dyslipidemia, and obesity being the most prevalent. Nine comorbidity clusters were identified. The clinical relevance of these comorbidity clusters was highlighted by the difference in symptoms, PSG parameters, and cardiovascular risk. Also, differences in CPAP adherence, improvements in ESS, and long-term survival were present between the clusters. CONCLUSION: Comorbidity prevalence in patients with OSA is high, and different comorbidity clusters, demonstrating differences in cardiovascular risk, CPAP adherence, and survival, can be identified. These results further substantiate the need for a comprehensive assessment of patients with OSA beyond the AHI.
PURPOSE: Obstructive sleep apnea (OSA) is a prevalent and multifaceted disease. To date, the presence and severity of objectively identified comorbidities and their association with specific OSA phenotypes, CPAP adherence, and survival remain to be elucidated. The aim of this study is to cluster patients with OSA based on 10 clinically important objectively identified comorbidities, and to characterize the comorbidity clusters in terms of clinical and polysomnographic characteristics, CPAP adherence, and survival. STUDY DESIGN AND METHODS: Seven hundred ten consecutive patients starting CPAP for moderate-to-severe OSA were included. Comorbidities were based on generally accepted cutoffs identified in the peer-reviewed literature. Self-organizing maps were used to order patients based on presence and severity of their comorbidities and to generate clusters. RESULTS: The majority of patients were men (80%). They were generally middle-aged (52 years) and obese (BMI: 31.5 kg/m2). Mean apnea-hypopnea index (AHI) was 41 ± 20 per h of sleep. More than 94% of the patients had one or more comorbidities with arterial hypertension, dyslipidemia, and obesity being the most prevalent. Nine comorbidity clusters were identified. The clinical relevance of these comorbidity clusters was highlighted by the difference in symptoms, PSG parameters, and cardiovascular risk. Also, differences in CPAP adherence, improvements in ESS, and long-term survival were present between the clusters. CONCLUSION: Comorbidity prevalence in patients with OSA is high, and different comorbidity clusters, demonstrating differences in cardiovascular risk, CPAP adherence, and survival, can be identified. These results further substantiate the need for a comprehensive assessment of patients with OSA beyond the AHI.
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