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- W3188317409 abstract "Background: Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology and outcomes; but staging AKI is predominantly by serum creatinine. We sought to identify AKI sub-groups (sub-phenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes.Methods: We independently applied latent class analysis (LCA) and k-Means clustering, to 29 clinical, plasma and urinary biomarker parameters measured during hospitalization to identify AKI sub-phenotypes in the ASSESS-AKI Study. AKI sub-phenotype associations were examined with the composite of major adverse kidney events (MAKE), defined as incident or progressive chronic kidney disease, long-term dialysis, or all-cause death during study follow-up.Findings: Among 769 AKI patients both LCA and k-Means clustering identified two AKI sub-phenotypes. Class 1 was characterized by a higher prevalence of prior congestive heart failure and favorable blood inflammatory and urinary tubular injury biomarkers, while class 2 was characterized by higher rates of prior chronic kidney disease and less favorable biomarkers. After a median follow-up of 4.7 years, the risk for MAKE was higher with class 2 (adjusted hazard ratio 1.41; 95% CI, 1.08 to 1.84; p=0.01) compared with class 1, adjusting for demographics, hospital level factors and KDIGO Stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of chronic kidney disease progression and dialysis. The top five variables that were different between class 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury, while serum creatinine ranked 20th out of the 29 variables for differentiating class 1 and 2.Interpretation: In this analysis, we identify two molecularly distinct AKI sub-phenotypes with differing risk of long-term outcomes, independent of current criteria to risk stratify AKI. Future identification of AKI sub-phenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI.Funding: National Institute of Diabetes, Digestive and Kidney DiseasesDeclaration of Interest: None to declare. Ethical Approval: The study was approved by the Yale University, Vanderbilt University, Kaiser Permanente, and University of Washington Institutional Review Boards. Written informed consent was obtained from participants." @default.
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- W3188317409 date "2021-01-01" @default.
- W3188317409 modified "2023-10-07" @default.
- W3188317409 title "Data Driven Analysis of Molecular Data Classifies AKI Patient and Predicts Clinical Outcomes" @default.
- W3188317409 doi "https://doi.org/10.2139/ssrn.3881735" @default.
- W3188317409 hasPublicationYear "2021" @default.
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