Abstract 13478: Increased Changes in Calculated Plasma Volume Predict Poor Prognosis in Heart Failure

Abstract

Introduction: Plasma volume (PV) is contracted in stable patients with heart failure (HF) due to the effects of therapy aimed at reducing congestion, while increased PV can complicate the progression of HF. We sought to determine the prognostic implications of calculated PV in patients with HF. Hypothesis: Increased changes in PV predict mortality after hospital discharge in HF patients. Methods: We used data from the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial for our analysis. The outcome in our study was all-cause mortality after hospital discharge. We used the hemoglobin and 1-hematocrit method to calculate the percentage change in PV (%ΔPV) between baseline and hospital discharge. We used Kaplan-Meier curves to compare 180-day (6-month) survival for patients that had increased %ΔPV to patients that had reduced or no %ΔPV. We used Cox proportional hazard regression analysis to adjust for age and gender, and obtained adjusted hazard ratios (AHR) and 95% confidence intervals (CI) of the association between mortality and %ΔPV. Results: There were 315 patients with complete data on PV that were included, of which 231 (73.3%) were men. The mean age was 56 years (range: 22-88 years). Of these 315 patients, 59 (18.7%) died after discharge during 4365.3 person days (PDs) of observation from baseline; mortality incidence rate was 1.4 deaths/100 PDs. Patients with reduced or no %ΔPV were more likely to survive than those with increased %ΔPV at the end of follow-up (Log rank test p=0.0042). Patients with increased %ΔPV had a statistically significant increased risk of mortality compared to patients with reduced or no %ΔPV (AHR 1.9, 95% CI: 1.1-3.2). Conclusions: Increased changes in calculated plasma volume predicted 6-month mortality in HF patients enrolled in the ESCAPE trial. Plasma volume changes during hospitalization for acute decompensated HF could guide risk stratification and prognosis in HF patients.