Clinical Research Directory

Development of a Prediction Score for the Occurrence of Death or Lung Transplantation in Patients With Emphysema Secondary to Alpha-1-anti-tripsin Deficiency

Emphysema linked to alpha-1-antitrypsin deficiency (DAAT): towards a better prediction of risks Emphysema caused by alpha-1-antitrypsin deficiency (DAAT) is a rare genetic disorder that can lead to serious complications, such as the need for a lung transplant or death, affecting up to 15% of patients. The only specific treatment available is a weekly infusion of alpha-1-antitrypsin (IV-AAT), an expensive and burdensome therapy. Currently, there is no reliable model to predict the course of the disease in these patients. Our study, conducted in several French hospitals, aims to develop a prediction tool combining clinical, biological, functional data and advanced medical image analysis (lung CT). This model will make it possible to identify the most at-risk patients, in order to better adapt their care, anticipate transplant needs and avoid unnecessary treatments for low-risk patients. Ultimately, this approach could also improve access to care for patients who need it most, while optimizing health system resources.

Machine Learning Model for Predicting Recovery After Critical Illness

This study aims to develop and test an artificial intelligence (AI) model to predict long-term functional status and return to work after critical illness. The main question is: Can we develop and validate a machine learning model to predict long-term functional status and return to work after critical illness?