International journal of chronic obstructive pulmonary disease
Cytokine- and Airflow-Based Clustering Identifies COPD Phenotypes with Differing Quantitative CT Features
By Wang Q, Yao Y, Xia M and 4 others.
Abstract
Introduction
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with distinct inflammatory profiles that may be associated with key pathological features, including emphysema and airway wall remodeling. This study aimed to identify COPD subgroups based on circulating pro- and anti-inflammatory cytokine activity and airflow limitation and to examine their clinical, physiological, and quantitative CT characteristics.
Methods
Demographic characteristics, symptom scores, pulmonary function parameters, and quantitative CT indices were collected from patients with stable COPD. Serum levels of pro- and anti-inflammatory cytokines were measured using enzyme-linked immunosorbent assay (ELISA). Cluster analysis was performed using a Gaussian mixture model (GMM).