Exploring Novel Biomarkers for Emphysema Detection: the ENBED Study
The goal of this clinical trial is to evaluate whether voice or capnometry, alone or in combination with other (non invasive) biomarkers can be used to detect emphysema on chest CT-scan in people with chronic obstructive pulmonary disease (COPD). The main question it aims to answer is: • Can a machine-learning based algorithm be developed that can classify the extent of emphysema on chest CT scan from patients with COPD, based on voice and/or capnometry. Participants will: * perform different voice-related tasks * perform capnometry twice (before/after exercise) * perform a light exercise task between tasks ( 5-sit-to-stand test) * undergo one venipuncture
• Adults aged over 18 years
• current respiratory smptoms (any dyspnea, cough or sputum)
• spirometry confirmed diagnosis of a non-fully reversible airflow obstruction, defined as a post bronchodilator Forced Expiratory Volume at one second/Forced Vital Capacity (FEV1/FVC ratio) \< 0.7 and/or emphysemateus abnormalities on CT imaging.
• presence of risk factors or causes associated with COPD
• chest CT scan performed in the past 12 months prior to inclusion to the study
• able to understand, read and write Dutch language