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Antineutrophil cytoplasmic antibody-associated vasculitis classification by cluster analysis based on clinical phenotypes: a single-center retrospective cohort study.

Lucy Eunju LeeJung Yoon PyoSung Soo AhnJason Jungsik SongYong-Beom ParkSang-Won Lee
Published in: Clinical rheumatology (2023)
Because the clusters were naturally derived from their distinguished phenotypes and have different clinical courses, our clustering method may be a more clinically relevant classification system for AAV, revealing its phenotypic diversity. We also proposed a simple and intuitive distance-based assignment algorithm, which can be easily modified according to specific clinical needs. Key Points • In this study with a single-center AAV cohort, we showed that AAV can be divided into five distinct subclasses with different disease courses based on the clinical and laboratory features of the patients. • Our study revealed ethnic differences in AAV manifestation and suggests that physicians may need to analyze their own AAV patients to assess the disease status of AAV patients. • We proposed a distance-based cluster membership assignment method that can be clinically modified to fit the specific purpose of grouping patients.
Keyphrases
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • prognostic factors
  • peritoneal dialysis
  • machine learning
  • deep learning
  • patient reported outcomes