Generalizability of symptom-based subtypes of moderate to severe OSA patients within and between ethnic groups

Abstract Objectives Multiple studies have shown that symptom-based subtypes of obstructive sleep apnea (OSA) exist and are generalizable to clinical and population-based samples of different race/ethnic and regional backgrounds. However, there have not been studies evaluating the generalizability within a clinical sample of Chinese ancestry. Thus, the aim of the current study was to investigate the generalizability of symptom-based subtypes within clinical patients from China. Methods This is a cross-sectional, multi-center study of patients with OSA from international sleep centers participating in the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Two Chinese cohorts were collected: 666 patients from Peking University People’s Hospital (PKUPH) and 503 patients from other China sites (Peking University International Hospital, Taiwan, and Shanghai). In addition, 694 White patients were included from 7 sites across 5 countries (Iceland, Germany Berlin, Australia Sydney, Perth, Brazil, and the United States Ohio State University and University of Pennsylvania). Symptom-based subtypes were determined using a latent class analysis (LCA) of 18 self-reported symptom variables and 3 comorbidities. Results A total of 1,863 patients were included in the LCA. The previously described 5 symptom subtype (disturbed sleep, minimal symptoms, excessively sleepy, moderately sleepy, and upper airway symptoms dominant) were optimal in the PKUPH site, other China sites, and White patients from SAGIC. Chinese patients had higher prevalence of the minimal symptoms subtype (P .001) compared to White patients. Among the five subtypes, the excessively sleepy subtype exhibited the highest AHI, and ODI. Conclusions : Based on the included symptoms and comorbidities, five subtypes provided the optimal groupings across both Chinese and White patients in SAGIC. Chinese patients were more likely to present with fewer symptoms. These data further enhance understanding of the generalizability of OSA symptom subtypes across ethnically diverse backgrounds, and pave the way for precision management of OSA in the future.