Classification of facial phenotypes in Asian patients with obstructive sleep apnea

Abstract

Backgroud The facial phenotypes of Asian obstructive sleep apnea (OSA) patients remain unclear. Objectives (1) To describe the facial features of OSA patients. (2) To develop a model based on facial contour indicators to predict OSA. (3) To classify the facial phenotypes of Asian OSA patients. Materials and methods 110 patients with OSA (apnea-hypopnea index [AHI] ≥ 10/h) and 50 controls (AHI< 10/h) were selected to measure facial contour indicators. Indicators were compared between OSA patients and the control group. We used multivariable linear regression analysis to predict OSA severity and K-means cluster analysis to classify OSA patients into different phenotypes. Results We built a model to predict OSA which explained 49.1% of its variance and classified OSA patients into four categories. Cluster 1 (Skeletal type) had the narrowest facial width indicators with narrowing of the retroglossal airway. Cluster 2 (Obese type) had the widest face, and narrowest hard palate, retropalatal, and hypopharyngeal airways. Cluster 3 (Nose type) had the narrowest nasal cavity. Cluster 4 (Long type) had the longest airway length. Conclusions and significance Patients with OSA were classified into four categories, each of which identified different anatomic risk factors that can be used to select the treatment.