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Use of consensus clustering to identify distinct subtypes of chronic kidney disease and associated mortality risk.
- Source :
-
Scientific reports [Sci Rep] 2024 Dec 02; Vol. 14 (1), pp. 29893. Date of Electronic Publication: 2024 Dec 02. - Publication Year :
- 2024
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Abstract
- Background: Chronic kidney disease (CKD) is a complex condition with diverse etiology and outcomes. Utilizing a data-driven clustering approach holds promise in identifying distinct CKD subgroups associated with specific risk profiles for death.<br />Methods: Unsupervised consensus clustering was utilized to classify chronic kidney disease (CKD) into subtypes based on 45 baseline characteristics in a cohort of 6,526 participants from the US National Health and Nutrition Examination Survey (NHANES) spanning the years 1999-2000 to 2017-2018.We examined the associations between CKD subgroups and clinical endpoints related to mortality, including all-cause mortality, cardiovascular disease mortality, cancer mortality, and mortality due to other causes.<br />Results: A total of 6,526 individuals with CKD were classified into four clusters at baseline. Cluster 1 (n = 508) comprised patients with relatively favorable levels of cardiac and kidney function markers, lower prevalence of cancer and higher prevalence of obesity, lower medication usage, and younger age. Cluster 4 (n = 2,029) comprised patients with the worst cardiac and kidney function markers. The characteristics of cluster 2 (n = 1,439) and 3 (n = 2,550) fell in between these two clusters. From cluster 1 to cluster 4, we observed a gradual increase in the hazard ratios of all-cause mortality, cardiovascular disease mortality, and mortality due to other causes. Additionally, further sensitivity analysis revealed patient heterogeneity among predefined subgroups with similar baseline kidney function and mortality risks.<br />Conclusions: Consensus clustering integrated baseline clinical and laboratory measures, revealing distinct CKD subgroups with markedly different risks of death, suggesting that further examination of patient subgroups could advance precision medicine.<br />Competing Interests: Declarations. Ethics approval and consent to participate: The NHANES is a public-use dataset available through the website. The NHANES protocol was approved by the institutional review board of the Centers for Disease Control and Prevention ( https://www.cdc.gov/nchs/nhanes/ irba98. htm). NHANES has obtained written informed consent from all participants. Competing interests: The authors declare no competing interests. Compliance with ethics guidelines: All authors declare that they have no conflict of interest.<br /> (© 2024. The Author(s).)
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 14
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 39623025
- Full Text :
- https://doi.org/10.1038/s41598-024-81208-1