BACKGROUND: The urinary proteomic classifier chronic kidney disease 273 (CKD273) is predictive for the development and progression of chronic kidney disease (CKD) and/or albuminuria in type 2 diabetes. This study evaluates its role in the prediction of cardiovascular (CV) events in patients with CKD Stages G1-G5. METHODS: We applied the CKD273 classifier in a cohort of 451 patients with CKD Stages G1-G5 followed prospectively for a median of 5.5 years. Primary endpoints were all-cause mortality, CV mortality and the composite of non-fatal and fatal CV events (CVEs). RESULTS: In multivariate Cox regression models adjusting for age, sex, prevalent diabetes and CV history, the CKD273 classifier at baseline was significantly associated with total mortality and time to fatal or non-fatal CVE, but not CV mortality. Because of a significant interaction between CKD273 and CV history (P = 0.018) and CKD stages (P = 0.002), a stratified analysis was performed. In the fully adjusted models, CKD273 classifier was a strong and independent predictor of fatal or non-fatal CVE only in the subgroup of patients with CKD Stages G1-G3b and without a history of CV disease. In those patients, the highest tertile of CKD273 was associated with a >10-fold increased risk as compared with the lowest tertile. CONCLUSIONS: The urinary CKD273 classifier provides additional independent information regarding the CV risk in patients with early CKD stage and a blank CV history. Determination of CKD273 scores on a random urine sample may improve the efficacy of intensified surveillance and preventive strategies by selecting patients who potentially will benefit most from early risk management.
BACKGROUND: The urinary proteomic classifier chronic kidney disease 273 (CKD273) is predictive for the development and progression of chronic kidney disease (CKD) and/or albuminuria in type 2 diabetes. This study evaluates its role in the prediction of cardiovascular (CV) events in patients with CKD Stages G1-G5. METHODS: We applied the CKD273 classifier in a cohort of 451 patients with CKD Stages G1-G5 followed prospectively for a median of 5.5 years. Primary endpoints were all-cause mortality, CV mortality and the composite of non-fatal and fatal CV events (CVEs). RESULTS: In multivariate Cox regression models adjusting for age, sex, prevalent diabetes and CV history, the CKD273 classifier at baseline was significantly associated with total mortality and time to fatal or non-fatal CVE, but not CV mortality. Because of a significant interaction between CKD273 and CV history (P = 0.018) and CKD stages (P = 0.002), a stratified analysis was performed. In the fully adjusted models, CKD273 classifier was a strong and independent predictor of fatal or non-fatal CVE only in the subgroup of patients with CKD Stages G1-G3b and without a history of CV disease. In those patients, the highest tertile of CKD273 was associated with a >10-fold increased risk as compared with the lowest tertile. CONCLUSIONS: The urinary CKD273 classifier provides additional independent information regarding the CV risk in patients with early CKD stage and a blank CV history. Determination of CKD273 scores on a random urine sample may improve the efficacy of intensified surveillance and preventive strategies by selecting patients who potentially will benefit most from early risk management.
Authors: Morgan E Grams; Aditya Surapaneni; Jingsha Chen; Linda Zhou; Zhi Yu; Diptavo Dutta; Paul A Welling; Nilanjan Chatterjee; Jingning Zhang; Dan E Arking; Teresa K Chen; Casey M Rebholz; Bing Yu; Pascal Schlosser; Eugene P Rhee; Christie M Ballantyne; Eric Boerwinkle; Pamela L Lutsey; Thomas Mosley; Harold I Feldman; Ruth F Dubin; Peter Ganz; Hongzhe Lee; Zihe Zheng; Josef Coresh Journal: J Am Soc Nephrol Date: 2021-09 Impact factor: 14.978
Authors: Michael Rudnicki; Justyna Siwy; Ralph Wendt; Mark Lipphardt; Michael J Koziolek; Dita Maixnerova; Björn Peters; Julia Kerschbaum; Johannes Leierer; Michaela Neprasova; Miroslaw Banasik; Ana Belen Sanz; Maria Vanessa Perez-Gomez; Alberto Ortiz; Bernd Stegmayr; Vladimir Tesar; Harald Mischak; Joachim Beige; Heather N Reich Journal: Nephrol Dial Transplant Date: 2021-12-31 Impact factor: 5.992