Investigation of time profile of FEV across the onset of potential COPD: a retrospective cohort study using medical checkup data in Japan.

This study compared the time profile of FEV after COPD diagnosis among rapid decliners, slow decliners, and sustainers in the year of COPD diagnosis. COPD subjects were identified from the annual medical checkup records of Hitachi, Ltd., employees in Japan (April 1998-March 2019).

Machine Learning Methods for the Diagnosis of Chronic Obstructive Pulmonary Disease in Healthy Subjects: Retrospective Observational Cohort Study.

Background: Airflow limitation is a critical physiological feature in chronic obstructive pulmonary disease (COPD), for which long-term exposure to noxious substances, including tobacco smoke, is an established risk. However, not all long-term smokers develop COPD, meaning that other risk factors exist.

Objective: This study aimed to predict the risk factors for COPD diagnosis using machine learning in an annual medical check-up database.