Admission, Discharge, or Change in B-Type Natriuretic Peptide and Long-Term Outcomes

Abstract

Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P <0.0001; IDI, 0.023, P <0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P <0.0001; IDI, 0.010, P <0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.