The aim of the study is to develop a standardized, risk-adapted screening protocol for detecting pleuropulmonary manifestations in patients with rheumatoid arthritis. To assess the risk of these manifestations, a comprehensive range of functional and clinical evaluations will be performed and correlated with structural lung assessments using computed tomography (CT).
The objective of the study is the establishment of a standardized risk-adapted screening protocol for detecting pleuropulmonary manifestations in patients with rheumatoid arthritis. To determine the risk of pleuropulmonary manifestation in RA, clinical (pulmonological and rheumatological specialist examination including standardized disease activity and symptom scores), laboratory (e.g. RF, ACPA, CRP, CEA), lung function (incl. body plethysmography, TLCO, FeNO, SMWT), sonographic (thoracic ultrasound, joint ultrasound), and demographic (e.g., age, gender) factors will be considered. A machine learning (ML) based risk-modeling approach will be utilized to create the screening tool. For further external validation and clinical application, a freely accessible online tool and a mobile app will be developed based on the existing model.
Study Type
OBSERVATIONAL
Enrollment
800
Medical University Innsbruck
Innsbruck, Austria, Austria
RECRUITINGNumber of RA patients with pleuropulmonary involvement according to an AI-supported multiparametric risk profile analysis
AI-supported risk factor-based analysis of pleuropulmonary involvement in RA patients assessed at a single time-point (baseline assessment). A multiparametric AI-supported evaluation based on clinical, sonographic, pulmonary function, laboratory, and exercise performance tests defines an RA population at high risk for the presence of pleuropulmonary involvement.
Time frame: single point (baseline)
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