Aaron M Hein1, Julia J Scialla2, Jie-Lena Sun3, Stephen J Greene4, Linda K Shaw3, Karen Chiswell3, Patrick H Pun4, Robert J Mentz5. 1. Department of Medicine, Duke University School of Medicine, Durham, North Carolina. 2. Department of Medicine, Duke University School of Medicine, Durham, North Carolina; Departments of Medicine and Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia; Duke Clinical Research Institute, Durham, North Carolina. 3. Duke Clinical Research Institute, Durham, North Carolina. 4. Department of Medicine, Duke University School of Medicine, Durham, North Carolina; Duke Clinical Research Institute, Durham, North Carolina. 5. Department of Medicine, Duke University School of Medicine, Durham, North Carolina; Duke Clinical Research Institute, Durham, North Carolina. Electronic address: robert.mentz@duke.edu.
Abstract
BACKGROUND: Greater variability in the estimated glomerular filtration rate (eGFR) is associated with higher mortality in patients with chronic kidney disease (CKD). Heart failure (HF) is common in CKD and may increase variability through changes in hemodynamic and volume regulation. We sought to determine if patients with vs without HF have higher kidney function variability in CKD, and to define the association with mortality. METHODS AND RESULTS: Patients undergoing coronary angiography from 2003 to 2013 with an eGFR of less than 60 mL/min/1.73 m2 were evaluated from the Duke Databank for Cardiovascular Disease. Variability in the eGFR, measured as the coefficient of variation (CV) of residuals from the regression of eGFR vs time, was calculated spanning 3 months to 2 years after catheterization. Mortality was assessed 2 to 7 years after catheterization. Patients were grouped into 3 HF phenotypes: HF with reduced ejection fraction, HF with preserved ejection, and no HF. Regression was used to evaluate associations between HF phenotypes and variability in the eGFR and between variability in the eGFR and mortality rate with stratification by HF phenotype. Among 3767 participants, the median eGFR at baseline was 45 mL/min/1.73 m2 (interquartile range 33-53 mL/min/1.73 m2), and longitudinal measures of eGFR over 21 months had within-patient residual variability (CV) of 14% (9%-20%). In adjusted analyses, variability in the eGFR was greater in those with HF with preserved ejection (n = 695, CV difference 0.98%, 95% confidence interval 0.14%-1.81%) or HF with reduced ejection fraction (n = 800, CV difference 2.51%, 95% confidence interval 1.66%-3.37%) relative to no HF (n = 2272). In 3068 participants eligible for mortality analysis, the presence of HF and greater variability in the eGFR were each associated independently with higher mortality, but there was no evidence of interaction between variability in the eGFR and any HF phenotype (all P for interaction ≥.49). CONCLUSIONS: Variability in the eGFR is greater in patients with HF and associated with mortality. Prediction algorithms and classification schemes should consider not only static, but also dynamic eGFR variability in HF and CKD prognostication.
BACKGROUND: Greater variability in the estimated glomerular filtration rate (eGFR) is associated with higher mortality in patients with chronic kidney disease (CKD). Heart failure (HF) is common in CKD and may increase variability through changes in hemodynamic and volume regulation. We sought to determine if patients with vs without HF have higher kidney function variability in CKD, and to define the association with mortality. METHODS AND RESULTS: Patients undergoing coronary angiography from 2003 to 2013 with an eGFR of less than 60 mL/min/1.73 m2 were evaluated from the Duke Databank for Cardiovascular Disease. Variability in the eGFR, measured as the coefficient of variation (CV) of residuals from the regression of eGFR vs time, was calculated spanning 3 months to 2 years after catheterization. Mortality was assessed 2 to 7 years after catheterization. Patients were grouped into 3 HF phenotypes: HF with reduced ejection fraction, HF with preserved ejection, and no HF. Regression was used to evaluate associations between HF phenotypes and variability in the eGFR and between variability in the eGFR and mortality rate with stratification by HF phenotype. Among 3767 participants, the median eGFR at baseline was 45 mL/min/1.73 m2 (interquartile range 33-53 mL/min/1.73 m2), and longitudinal measures of eGFR over 21 months had within-patient residual variability (CV) of 14% (9%-20%). In adjusted analyses, variability in the eGFR was greater in those with HF with preserved ejection (n = 695, CV difference 0.98%, 95% confidence interval 0.14%-1.81%) or HF with reduced ejection fraction (n = 800, CV difference 2.51%, 95% confidence interval 1.66%-3.37%) relative to no HF (n = 2272). In 3068 participants eligible for mortality analysis, the presence of HF and greater variability in the eGFR were each associated independently with higher mortality, but there was no evidence of interaction between variability in the eGFR and any HF phenotype (all P for interaction ≥.49). CONCLUSIONS: Variability in the eGFR is greater in patients with HF and associated with mortality. Prediction algorithms and classification schemes should consider not only static, but also dynamic eGFR variability in HF and CKD prognostication.
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