Severe obstructive sleep apnea phenotypes by cluster analysis based on multiple organs function

基于多器官功能的聚类分析对重度阻塞性睡眠呼吸暂停表型进行分类

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Abstract

Obstructive sleep apnea (OSA) is a heterogeneous disorder and the severe OSA could lead to cardiovascular and metabolic comorbidities. However, the OSA diagnosis focuses on the respiratory system according to guidelines. In this study, we aim to explore the clinical phenotypes of severe OSA based on comprehensive assessment of multiple organs function using cluster analysis. Patients with severe OSA were studied with data of age, sex, anthropometric examination, blood pressure, liver and renal function, lipid levels, fasting blood glucose, apnea index (AI), hyponea index (HI), apnea-hyponea index (AHI), lowest Sao2 during sleep-monitor, and disorders of nonalcoholic fatty liver disease (NAFLD) and carotid atherosclerosis (CAS). Cluster analysis was performed using k-medoids algorithm. A total of 503 subjects were clustered into two clusters: Cluster 1 (n = 136), middle-aged women; Cluster 2 (n = 367), middle-aged men. When compared with cluster 1, the cluster 2 showed an increased AI, AHI, BMI, neck and waist circumferences, fasting blood glucose, NAFLD and CAS prevalence, decreased liver and renal function, and decreased HI. The results suggest the phenotypes of severe OSA were identified especially based on multiple organ functions, creating the need to rethink these patients' comprehensive assessment. The findings from our study suggest that for severe OSA patients, middle-aged men are more likely accompanied worse systematic condition than women, which should be taken into account by physicians.

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