About this trial
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
Eligibility criteria
Qualifiers
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
Disqualifiers
acute exacerbation of COPD within 8 weeks of start of the study
comorbidities affecting speech or breathing coordination (neuromuscular disease, CVA< BMI > 40)
comorbidities affecting speech characteristics of dyspnea (severe heart failure, interstitial lung disease)
comorbidities affecting respiratory system including but not exclusive to asthma or cystic fibrosis
Trial design
Treatments tested in this trial
- voice sampling
- capnometry
Treatment groups
Sponsors and collaborators
Maastricht University
Lead sponsor
Roche Pharma AG
Collaborator