Abstract
Identification of novel risk factors for chronic kidney disease (CKD) progression may inform mechanistic investigations and improve identification of high-risk subgroups. The current study aimed to characterize CKD progression across levels of numerous risk factors and identify independent risk factors for CKD progression among those with and without diabetes. The Chronic Renal Insufficiency Cohort (CRIC) Study is a prospective cohort study of adults with CKD conducted at 7 US clinical centers. Participants (N=3,379) had up to 12.3 years of follow-up; 47% had diabetes. 30 risk factors for CKD progression across sociodemographic, behavioral, clinical, and biochemical domains at baseline. Study outcomes were estimated glomerular filtration rate (eGFR) slope and the composite of halving of eGFR or initiation of kidney replacement therapy. Stepwise selection of independent risk factors was performed stratified by diabetes status using linear mixed-effects and Cox proportional hazards models. Among those without and with diabetes, respectively, mean eGFR slope was-1.4±3.3 and-2.7±4.7mL/min/1.73m2 per year. Among participants with diabetes, multivariable-adjusted hazard of the composite outcome was approximately 2-fold or greater with higher levels of the inflammatory chemokine CXCL12, the cardiac marker N-terminal pro-B-type natriuretic peptide (NT-proBNP), and the kidney injury marker urinary neutrophil gelatinase-associated lipocalin (NGAL). Among those without diabetes, low serum bicarbonate and higher high-sensitivity troponin T, NT-proBNP, and urinary NGAL levels were all significantly associated with a 1.5-fold or greater rate of the composite outcome. The observational study design precludes causal inference. Strong associations for cardiac markers, plasma CXCL12, and urinary NGAL are comparable to that of systolic blood pressure≥140mm Hg, a well-established risk factor for CKD progression. This warrants further investigation into the potential mechanisms that these markers indicate and opportunities to use them to improve risk stratification.
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