Development and external validation of a machine learning model for predicting in-hospital mortality in ICU patients with diabetic kidney disease: a study utilizing the MIMIC database and a Chinese cohort

The developed XGBoost model demonstrates good predictive performance for in-hospital mortality in ICU-DKD patients, exhibiting satisfactory generalizability and interpretability. This tool supports early risk stratification and facilitates personalized treatment strategies in critical care settings.