Radiomics-enhanced modelling approach for predicting the need for ECMO in ARDS patients: a retrospective cohort study.

ABSTRACT: Decisions regarding veno-venous extracorporeal membrane oxygenation (vv-ECMO) in patients with acute respiratory distress syndrome (ARDS) are often based solely on clinical and physiological parameters, which may insufficiently reflect severity and heterogeneity of lung injury. This study aimed to develop a predictive model integrating machine learning-derived quantitative features from admission chest computed tomography (CT) with selected clinical variables to support early individualized decision-making regarding vv-ECMO therapy. In this retrospective single-center cohort study, 375 consecutive patients with COVID-19-associated ARDS admitted to the ICU between March 2020 and April 2022 were included. Lung segmentation from initial CTs was performed using a convolutional neural network (

SUBMITTER: Mirus M 

PROVIDER: S-EPMC12485099 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature