Background and objective: The definition of chronic obstructive pulmonary disease (COPD) based on a fixed forced expiratory volume in 1 s (FEV1 )/forced vital capacity (FVC) ratio or on the lower limits of FEV1 /FVC of a healthy reference population is the subject of continuous debate. We explored whether dynamics of forced expiratory flow decline on spirometry can identify subjects with and without COPD when the two key diagnostic criteria are discordant.
Methods: Four hundred twenty-three individuals with a history of ≥15 pack-years smoking had pulmonary function measurements conducted. A second-order input-output model was used to describe the dynamics of the forced expiration. The capability of the model parameters to predict presence of disease was explored with a support vector machine classifier. In the discordant individuals, newly classified subjects were validated by other pulmonary function tests.
Results: In the non-discordant subjects (n = 370), the second-order model was able to confirm a diagnosis of COPD in 95% of subjects (n = 351). In the discordant individuals (n = 53), the classification by dynamic flow analysis found 28 patients to be healthy whereas 25 patients were still classified as COPD. Hyperinflation, increased airways resistance and reduced dynamic volumes were observed in the newly identified COPD group of discordant subjects. When using non-spirometry-based pulmonary function criteria as a standard for correct diagnoses in the individual discordant subjects, the model allocated 68% (n = 36) of the discordant to a correct diagnosis.
Conclusions: Expiratory flow dynamics can detect airflow limitation and indicate the presence of COPD. In discordant subjects, our methodology allows a better identification of subjects with or without characteristics of COPD.
Keywords: Global Initiative for Chronic Obstructive Lung Disease; airway obstruction; chronic obstructive pulmonary disease diagnosis; lower limit of normal; spirometry.
© 2015 Asian Pacific Society of Respirology.