Variability in estimated glomerular filtration rate and patients' outcomes in a real‐world heart failure population

Abstract

Abstract Aims The prognostic significance of renal function variability has not been fully elucidated in heart failure (HF). This multicentre, prospective cohort study aimed to evaluate the usefulness of visit‐to‐visit variability in estimated glomerular filtration rate (eGFR) for predicting patients' outcomes in a real‐world HF population. Methods A total of 564 patients who had survived HF hospitalization were randomly assigned with a 2:1 ratio to derivation and validation cohorts, and they were then followed after discharge. Using the data for 6 months after discharge, each patient's visit‐to‐visit eGFR variability (EGV) was estimated. In the derivation cohort, Cox regression analyses were performed to assess the association of EGV with a subsequent composite event (death and HF hospitalization). In the validation cohort, the predictive performance was compared among Cox regression models with EGV, those with B‐type natriuretic peptide (BNP) and those with eGFR. Results In the derivation cohort (376 patients), median age, left ventricular ejection fraction (LVEF), BNP and eGFR at discharge were 72 years, 53.3%, 134.8 pg/mL and 58.7 mL/min/1.73 m2, respectively. During a median follow‐up of 2.2 years, higher EGV was associated with an increased risk of the composite event (adjusted hazard ratio [per standard deviation increase in log‐transformed EGV], 1.5; 95% confidence interval, 1.1–2.0). A similar finding was observed in a stratified analysis by LVEF. In the validation cohort (188 patients), better model fit, discrimination, reclassification and calibration were observed for EGV than for 6‐month averaged BNP or eGFR for predicting the composite event when added to HF risk prediction models. Adding EGV to models with BNP or eGFR improved model discrimination and reclassification. Conclusions EGV predicts HF outcomes regardless of LVEF. Risk prediction models with EGV have good performance in real‐world HF patients. The study findings highlight the clinical importance of observing visit‐to‐visit fluctuations in renal function in this population.

Keywords

• Heart failure (HF); Risk prediction; eGFR variability; B‐type natriuretic peptide (BNP); Estimated glomerular filtration rate (eGFR)