Exploring expiratory flow dynamics to understand chronic obstructive pulmonary disease

Abstract

Chronic obstructive pulmonary disease (COPD) is one of the most common respiratory diseases and a leading cause of morbidity and mortality. It is characterized by irreversible airflow limitations. We aimed to explore whether the dynamics of expiration could serve as a descriptor of airflow limitations. Additionally, we explored the relationship between dynamic components and the presence of COPD. A data-based model was developed using data from 474 subjects. Significant difference (p < 0.0001) was found comparing a group of diseased patients with healthy for each dynamic component (namely the two poles, the steady state gain (SSG) and the time constant). Moreover difference was observed for each severity stage of disease. When ranking all components, SSG and pole1 are highlighted as the best COPD descriptors. We concluded that more detailed analysis of the forced expiration can be used to expand the understanding of COPD. Furthermore, the obtained parameters may improve current COPD assessment.