ArticleKidney diseases (Basel, Switzerland)
Unsupervised Clustering Identifies High-Risk Phenotypic Subgroup in Crescentic Glomerulonephritis Patients.
Article in Kidney diseases (Basel, Switzerland). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: The current classification of crescentic glomerulonephritis (cGN) primarily focuses on renal outcomes; its ability to predict overall patient survival remains controversial. This study aims to develop a risk stratification system for overall survival and validate a renal risk score for predicting end-stage renal disease (ESRD) in cGN. Methods: We retrospectively analyzed 224 cGN patients from the First Affiliated Hospital of Sun-Yat Sen University, with a median follow-up of 87.10 (interquartile range: 32.35, 153.97) months. The primary outcome was all-cause mortality, and the secondary outcome was ESRD. K-means clustering, principal component analysis, and decision tree analysis were used to identify patient groups. Results: Traditional classification showed that type III cGN patients had the poorest overall survival rates, whereas type I had the poorest renal survival. K-means clustering stratified patients into high-risk ( Conclusions: We identified two survival risk groups and developed a renal risk score in cGN patients, providing an informative and comprehensive risk stratification to facilitate the clinical management.
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