Belgian Lung Function Study

Currently, it remains unclear how to manage serial lung function measurements in a clinical setting. The investigators aimed to tackle this problem by developing a machine learning (ML) model that can accurately predict population and individual lung function trajectories. These predictions would enable the investigators to identify positive or negative deviations, thereby revealing unexpected disease patterns. A prospective validation is needed that includes data on mortality, hospitalisations, emergency-room visits and patient-reported outcomes. Within this study, the goal is to validate the ML model with the data collected from this observational study.

NCT Number	NCT07419555
Lead Sponsor	KU Leuven Collaborators: AZ Delta, University Hospital, Antwerp, Ziekenhuis Oost-Limburg
Conditions	Chronic Respiratory Diseases
Enrollment	4,000 participants
Start Date	2026-03-25
Primary Completion	2029-03-01 (estimated)
Study Completion	2029-03-01 (estimated)
Updated on ClinicalTrials.gov	2026-03-30