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

Rheumatology (Oxford, England) - 6 Apr 2026

Hu Shuhui, Cui Lingling, Chen Ying, Li Xinde, Wang Can, Zhao Yulei, Zhang Yiru, Terkeltaub Robert, Li Changgui, Lu Jie

Abstract excerpt

OBJECTIVE: To systematically evaluate the contribution of clinical heterogeneity to chronic kidney disease (CKD) progression in gout patients using data-driven phenotyping, and to assess whether incorporating genetic risk improves prediction of renal outcomes. METHODS: In this prospective cohort study, 1497 Chinese gout patients were enrolled and followed for CKD progression. K-means clustering was applied to...

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Clustering Algorithms
East Asian People
Genetic Risk Score
Gout
Hyperuricemia

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Machine Learning

Renal Insufficiency, Chronic

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PMID: 41934097
DOI: 10.1093/rheumatology/keag158

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

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