Related Experiment Video
Updated: Sep 25, 2025

Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Prediction of Incident Heart Failure in CKD: The CRIC Study
Leila R Zelnick1, Michael G Shlipak2, Elsayed Z Soliman3
1Kidney Research Institute, Department of Medicine (Nephrology), University of Washington, Seattle, Washington, USA.
Insights
Identifying heart failure (HF) risk in chronic kidney disease (CKD) patients is crucial. Cardiac biomarkers N-terminal brain natriuretic peptide (NT-proBNP) and high-sensitivity troponin-T (hsTnT) show moderate discrimination for predicting HF in CKD.
Area of Science:
- Nephrology
- Cardiology
- Biomarkers
Background:
- Heart failure (HF) is a common complication in patients with chronic kidney disease (CKD).
- Accurate prediction of HF risk in CKD patients is essential for timely clinical intervention.
- Existing prediction models may not fully capture HF risk in this specific population.
Purpose of the Study:
- To assess the prognostic value of cardiac biomarkers and echocardiographic variables for predicting 10-year HF risk in individuals with CKD.
- To compare the predictive performance of these variables against a published clinical HF prediction equation.
Main Methods:
- Utilized data from 2147 Chronic Renal Insufficiency Cohort (CRIC) participants without prior HF.
- Collected clinical, cardiac biomarker (NT-proBNP, hsTnT), and echocardiographic (LVM, LVEF) data.
- Employed Fine and Gray modeling and 10-fold cross-validation to compare prediction models, including the ARIC HF equation.
Main Results:
- The Atherosclerosis Risk in Communities (ARIC) HF model showed modest discrimination (C-index 0.68).
- Cardiac biomarkers NT-proBNP and hsTnT together demonstrated significantly better discrimination (C-index 0.73) than the ARIC model.
- A comprehensive model including clinical, biomarker, and echocardiographic data achieved the highest discrimination (C-index 0.77).
Conclusions:
- The ARIC HF prediction model has limited discrimination in adults with CKD.
- NT-proBNP and hsTnT offer a low-burden, moderately effective approach for HF risk prediction in CKD patients.
- Development of HF prediction models specifically tailored for CKD populations is warranted.
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' 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.
More Related Videos
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
06:38Early Detection of Drug-Induced Renal Hemodynamic Dysfunction Using Sonographic Technology in Rats
Published on: March 11, 2016
Related Concept Videos
Chronic Kidney Disease I: Introduction
Chronic Kidney Disease IV: Nursing Management
Chronic Kidney Disease III: Interprofessional Care
Acute Kidney Injury IV: Diagnostic Studies and Prevention
Chronic Kidney Disease II: Clinical Manifestations
Acute Kidney Injury I: Introduction