Background-Heart failure (HF) is responsible for a huge burden in hospital care. Our goal was to evaluate the value of N-terminal-pro-brain natriuretic peptide (NT-proBNP) in predicting death or hospital readmission after discharge of HF patients. Methods and Results-We included 182 patients consecutively admitted to hospital because of decompensated HF.Patients were followed up for 6 months. The primary end point was death or readmission. Twenty-six patients died in hospital. The median admission NT-proBNP level was 6778.5 pg/mL, and the median level at discharge was 4137.0 pg/mL (PϽ0.001). Patients were classified into 3 groups: (1) decreasing NT-proBNP levels by at least 30% (nϭ82), (2) no significant modifications on NT-proBNP levels (nϭ49), and (3) increasing NT-proBNP levels by at least 30% (nϭ25). The primary end point was observed in 42.9% patients. Variables associated with an increased hazard of death and/or hospital readmission in univariate analysis were length of hospitalization, heart rate, signs of volume overload, no use of ACE inhibitors, higher NYHA class at discharge, admission and discharge NT-proBNP, and the change in NT-proBNP levels. The variation in NT-proBNP was the strongest predictor of an adverse outcome. Independent variables associated with an increased risk of readmission or death were signs of volume overload and the change in NT-proBNP levels. Conclusions-Variations in NT-proBNP levels are related to hospital readmission and death within 6 months. NT-proBNP levels are potentially useful in the evaluation of treatment efficacy and might help clinicians in planning discharge of HF patients. Whether therapeutic strategies aimed to lower NT-proBNP levels modify prognosis warrants future investigation.

Patients with cirrhosis have systolic and diastolic cardiac dysfunction at rest. Newer echocardiographic techniques may identify patients with functional impairment more accurately than conventional methods, which are more influenced by flow conditions.

In patients hospitalised for ADHF, the addition of the discharge NT-proBNP values as well as the change in NT-proBNP to known risk markers, generates a relatively simple yet robust discharge risk score that importantly improves the prediction of adverse events.