Cluster analysis of clinical phenotypic heterogeneity in obstructive sleep apnea assessed using photoplethysmography

Abstract

BackgroundWe evaluated heterogeneity in clinical phenotypes among patients with obstructive sleep apnea syndrome (OSAHS) using photoplethysmography (PPG) in cluster analysis. MethodsAll enrolled patients underwent polysomnography (PSG) monitoring while wearing a PPG device. Pulse wave signals were recorded with a modified pulse oximetry probe in the PPG device. The pulse wave-derived cardiac risk composite parameter (CRI) and eight derived signal parameters were used to assess OSAHS phenotype. We defined a high cardiovascular risk OSAHS group (CRI ≥0.5) and low cardiovascular risk OSAHS group (CRI <0.5). K-means clustering was performed for analysis of clinical phenotype heterogeneity in OSAHS by combining the CRI and its derived signals. ResultsThe OSAHS group had high cardiovascular risk for sex, age, body mass index, systolic and diastolic blood pressure, apnea hypopnea index, and obstructive arousal index and higher risk of developing hypertension, diabetes, and cerebrovascular comorbidities. The low cardiovascular risk OSAHS group had higher blood oxygen levels. Three clinical phenotypes were identified in CRI clustering: 1) typical OSAHS with high risk of hypertension (characterized by middle age, obesity, hypertension with severe OSAHS); 2) older women and mild OSAHS; 3) older men and mild OSAHS. Three subtypes were obtained based on the eight cardiac risk-derived parameters: 1) hypoxia combined with decreased pulse wave amplitude variation; 2) decreased vascular pulse wave amplitude combined with decreased pulse frequency; 3) arrhythmia combined with hypoxia. ConclusionsEstablishing OSAHS clinical phenotypes with the CRI and derived parameters using PPG may help in establishing multi-dimensional assessment of cardiovascular risk in OSAHS.