@article{73caa4181ebf4dca88b6f720e0d29994,
title = "Prediction of Incident Heart Failure in CKD: The CRIC Study",
abstract = "Introduction: Heart failure (HF) is common in chronic kidney disease (CKD); identifying patients with CKD at high risk for HF may guide clinical care. We assessed the prognostic value of cardiac biomarkers and echocardiographic variables for 10-year HF prediction compared with a published clinical HF prediction equation in a cohort of participants with CKD. Methods: We studied 2147 Chronic Renal Insufficiency Cohort (CRIC) participants without prior HF with complete clinical, cardiac biomarker (N-terminal brain natriuretic peptide [NT-proBNP] and high sensitivity troponin-T [hsTnT]), and echocardiographic data (left ventricular mass [LVM] and left ventricular ejection fraction [LVEF] data). We compared the discrimination of the 11-variable Atherosclerosis Risk in Communities (ARIC) HF prediction equation with LVM, LVEF, hsTnT, and NT-proBNP to predict 10-year risk of hospitalization for HF using a Fine and Gray modeling approach. We separately evaluated prediction of HF with preserved and reduced LVEF (LVEF ≥50% and <50%, respectively). We assessed discrimination with internally valid C-indices using 10-fold cross-validation. Results: Participants{\textquoteright} mean (SD) age was 59 (11) years, 53% were men, 43% were Black, and mean (SD) estimated glomerular filtration rate (eGFR) was 44 (16) ml/min per 1.73 m2. A total of 324 incident HF hospitalizations occurred during median (interquartile range) 10.0 (5.7–10.0) years of follow-up. The ARIC HF model with clinical variables had a C-index of 0.68. Echocardiographic variables predicted HF (C-index 0.70) comparably to the published ARIC HF model, while NT-proBNP and hsTnT together (C-index 0.73) had significantly better discrimination (P = 0.004). A model including cardiac biomarkers, echocardiographic variables, and clinical variables had a C-index of 0.77. Discrimination of HF with preserved LVEF was lower than for HF with reduced LVEF for most models. Conclusion: The ARIC HF prediction model for 10-year HF risk had modest discrimination among adults with CKD. NT-proBNP and hsTnT discriminated better than the ARIC HF model and at least as well as a model with echocardiographic variables. HF clinical prediction models tailored to adults with CKD are needed. Until then, measurement of NT-proBNP and hsTnT may be a low-burden approach to predicting HF in this population, as they offer moderate discrimination.",
keywords = "biomarkers, cardiovascular disease, chronic kidney disease, echocardiogram, heart failure",
author = "{CRIC Study Investigators} and Zelnick, {Leila R.} and Shlipak, {Michael G.} and Soliman, {Elsayed Z.} and Amanda Anderson and Robert Christenson and Mayank Kansal and Rajat Deo and Jiang He and Jaar, {Bernard G.} and Weir, {Matthew R.} and Panduranga Rao and Cohen, {Debbie L.} and Cohen, {Jordana B.} and Feldman, {Harold I.} and Alan Go and Nisha Bansal and Appel, {Lawrence J.} and Jing Chen and Debbie Cohen and Go, {Alan S.} and Lash, {James P.} and Nelson, {Robert G.} and Mahboob Rahman and Rao, {Panduranga S.} and Shah, {Vallabh O.} and Unruh, {Mark L.}",
note = "Funding Information: Funding for the CRIC Study was obtained under a cooperative agreement from National Institute of Diabetes and Digestive and Kidney Diseases ( U01DK060990 , U01DK060984 , U01DK061022 , U01DK061021 , U01DK061028 , U01DK060980 , U01DK060963 , U01DK060902 and U24DK060990 ). In addition, this work was supported in part by the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award NIH / NCATS UL1TR000003 , Johns Hopkins University UL1 TR-000424 , University of Maryland GCRC M01 RR-16500 , Clinical and Translational Science Collaborative of Cleveland , UL1TR000439 from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research (MICHR) UL1TR000433 , University of Illinois at Chicago CTSA UL1RR029879 , Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases P20 GM109036 , Kaiser Permanente NIH / NCRR UCSF-CTSI UL1 RR-024131 , and Department of Internal Medicine , University of New Mexico School of Medicine Albuquerque, NM R01DK119199 . Funding Information: This study was supported by R01 DK103612 (Bansal). This research was supported in part by an unrestricted gift from the Northwest Kidney Centers to the Kidney Research Institute. Roche Diagnostics provided partial funding for the NT-proBNP and hsTnT assays. Funding for the CRIC Study was obtained under a cooperative agreement from National Institute of Diabetes and Digestive and Kidney Diseases (U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902 and U24DK060990). In addition, this work was supported in part by the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award NIH / NCATS UL1TR000003, Johns Hopkins University UL1 TR-000424, University of Maryland GCRC M01 RR-16500, Clinical and Translational Science Collaborative of Cleveland, UL1TR000439 from the National Center for Advancing Translational Sciences (NCATS) component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research (MICHR) UL1TR000433, University of Illinois at Chicago CTSA UL1RR029879, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases P20 GM109036, Kaiser Permanente NIH / NCRR UCSF-CTSI UL1 RR-024131, and Department of Internal Medicine, University of New Mexico School of Medicine Albuquerque, NM R01DK119199. Publisher Copyright: {\textcopyright} 2022 International Society of Nephrology",
year = "2022",
month = apr,
doi = "10.1016/j.ekir.2022.01.1067",
language = "English (US)",
volume = "7",
pages = "708--719",
journal = "Kidney International Reports",
issn = "2468-0249",
publisher = "Elsevier Inc.",
number = "4",
}