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Project

LUNG VOLUME REDUCTION TO TREAT SEVERE CHRONIC OBSTRUCTIVE PULMONARY DISEASE: A MULTIDISCIPLINARY DIAGNOSTIC AND INTERVENTIONAL APPROACH FROM REFERRAL TO FOLLOW- UP.

Chronic obstructive lung disease (COPD) kills more than 3 million people worldwide every year. It is characterized by progressive dyspnea, poor quality of life, frequent exacerbations, and results in early death. Medical treatment of COPD may slow progression but cannot reverse the true nature of the disease. Lung volume reduction (LVR) surgery and endoscopic lung volume reduction are two valid treatment options that intend to restore function and relieve symptoms. Yet, the actual number of patients eligible for LVR is unknown. Therefore, we aim to analyze the severe emphysema population to assess the proportion of potential candidates for LVR. To achieve good outcomes after LVR, careful patient selection with involvement of a multidisciplinary team is essential. Hence, more specific guidance for appropriate patient selection and the determination of the optimal intervention is needed. Aided by state-of-the-art machine learning algorithms, we aim to develop algorithms that support clinicians for optimal referral and treatment decisions. Remote telemedicine offers the opportunity to improve patient self-management and facilitate care for patients with limited access to health facilities during follow-up. Because of the ability to detect clinical improvement or sudden deterioration, we aim to explore the potential of remote monitoring during coaching interventions in detecting deterioration and triggering early intervention.
Date:1 Oct 2022 →  Today
Keywords:Emphysema, Lung Volume Reduction, Chronic obstructive pulmonary disease, Multidisciplinary approach
Disciplines:Respiratory medicine, Thoracic surgery
Project type:PhD project