Prediction of Incident Heart Failure in CKD: The CRIC Study

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 m(2). 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.

Automated summary

This study evaluated the prognostic value of cardiac biomarkers and echocardiographic variables in predicting heart failure (HF) in patients with chronic kidney disease (CKD). The results showed that NT-proBNP and hsTnT had better discrimination than the current HF prediction model. HF clinical prediction models tailored to CKD patients are needed.