Cluster-defined gout subtypes exhibit divergent chronic kidney disease trajectories: a machine learning approach in a Chinese prospective cohort

This study proposes a novel K-means clustering-based classification of gout, identifying subgroups with distinct CKD trajectories. Integration of clinical phenotyping and genetic profiling may enhance individualized risk stratification and guide targeted prevention strategies in gout-associated CKD.