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Abstract: TH-OR42

Prediction of Incident Heart Failure in CKD

Session Information

Category: Hypertension and CVD

  • 1401 Hypertension and CVD: Epidemiology, Risk Factors, and Prevention

Authors

  • Zelnick, Leila R., University of Washington, Seattle, Washington, United States
  • Shlipak, Michael, University of California San Francisco, San Francisco, California, United States
  • Soliman, Elsayed Z., Wake Forest University, Winston-Salem, North Carolina, United States
  • Anderson, Amanda Hyre, Tulane University, New Orleans, Louisiana, United States
  • Christenson, Robert, University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Kansal, Mayank, University of Illinois at Chicago, Chicago, Illinois, United States
  • Deo, Rajat, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • He, Jiang, Tulane University, New Orleans, Louisiana, United States
  • Jaar, Bernard G., Johns Hopkins University, Baltimore, Maryland, United States
  • Weir, Matthew R., University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Rao, Panduranga S., University of Michigan, Ann Arbor, Michigan, United States
  • Cohen, Debbie L., University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Cohen, Jordana B., University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Feldman, Harold I., University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Go, Alan S., Kaiser Permanente Northern California, Oakland, California, United States
  • Bansal, Nisha, University of Washington, Seattle, Washington, United States
Background

Heart failure (HF) is common in patients with chronic kidney disease (CKD); identifying high risk patients would guide clinical care. We assessed prognostic value of cardiac biomarkers and echocardiographic (echo) variables for HF prediction compared to a published clinical equation in the Chronic Renal Insufficiency Cohort (CRIC).

Methods

Among 2,146 CRIC participants without prior HF and with complete clinical, cardiac biomarker and echo data, we compared the discrimination of the 11-variable Atherosclerosis Risk in Communities (ARIC) HF prediction equation to cardiac biomarkers (N terminal brain natriuretic peptide, NT-proBNP, and high sensitivity troponin T, hsTnT) and echo measures (left ventricular mass, LVM, and ejection fraction, LVEF) to predict 10-year risk of HF hospitalization using Cox regression. We separately evaluated prediction of HF with preserved and reduced LVEF (LVEF ≥50% and <50%, respectively). We assessed discrimination with internally valid, 10-fold cross-validated C-indices.

Results

Participants had mean (SD) age 59 (11), eGFR 44 (16) mL/min/1.73m2, 53% men, and 43% Black; 268 incident HF hospitalizations occurred during 6.7 (SD 2.5) years of follow-up. The ARIC HF model with clinical variables had a C-index of 0.68 (Table). hsTnT alone (C-index 0.69) and LVM+LVEF (C-index 0.71) were comparable to the ARIC model, while NT-proBNP alone had better discrimination (C-index 0.72, p=0.04). A model including cardiac biomarkers, echo, and clinical variables had a C-index of 0.78. Discrimination of HF with preserved LVEF was lower than for HF with reduced LVEF for most models (Table).

Conclusion

The ARIC HF prediction model for 10-year HF risk had modest discrimination among adults with CKD. NT-proBNP alone discriminated better than the ARIC model, and was comparable to models with echo variables. HF clinical prediction models specifically in adults with CKD are needed. Until then, use of NT-proBNP may be a low burden approach to predict HF in this population, and offers moderate discrimination.

Funding

  • NIDDK Support