Lukas Otero Sanchez, Clara-Yongxiang Zhan, Carolina Gomes da Silveira Cauduro, Laurent Crenier, Hassane Njimi, Gael Englebert, Antonella Putignano, Antonia Lepida, Delphine Degré, Nathalie Boon, Thierry Gustot, Pierre Deltenre, Astrid Marot, Jacques Devière, Christophe Moreno, Miriam Cnop, Eric Trépo
BACKGROUND & AIMS: Diabetes mellitus is a major risk factor for fatty liver disease development and progression. A novel machine learning method identified five clusters of patients with diabetes, with different characteristics and risk of diabetic complications using six clinical and biological variables. We evaluated whether this new classification could identify individuals with an increased risk of liver-related complications. METHODS: We used a prospective cohort of patients with a diagnosis of type 1 or type 2 diabetes without evidence of advanced fibrosis at baseline recruited between 2000 and 2020...
August 2023: JHEP reports: innovation in hepatology