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      Direct comparison of serial B-type natriuretic peptide and NT-proBNP levels for prediction of short- and long-term outcome in acute decompensated heart failure

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          Abstract

          Introduction

          Monitoring treatment efficacy and assessing outcome by serial measurements of natriuretic peptides in acute decompensated heart failure (ADHF) patients may help to improve outcome.

          Methods

          This was a prospective multi-center study of 171 consecutive patients (mean age 80 73-85 years) presenting to the emergency department with ADHF. Measurement of BNP and NT-proBNP was performed at presentation, 24 hours, 48 hours and at discharge. The primary endpoint was one-year all-cause mortality; secondary endpoints were 30-days all-cause mortality and one-year heart failure (HF) readmission.

          Results

          During one-year follow-up, a total of 60 (35%) patients died. BNP and NT-proBNP levels were higher in non-survivors at all time points (all P < 0.001). In survivors, treatment reduced BNP and NT-proBNP levels by more than 50% ( P < 0.001), while in non-survivors treatment did not lower BNP and NT-proBNP levels. The area under the ROC curve (AUC) for the prediction of one-year mortality increased during the course of hospitalization for BNP (AUC presentation: 0.67; AUC 24 h: 0.77; AUC 48 h: 0.78; AUC discharge: 0.78) and NT-proBNP (AUC presentation: 0.67; AUC 24 h: 0.73; AUC 48 h: 0.75; AUC discharge: 0.77). In multivariate analysis, BNP at 24 h (1.02 [1.01-1.04], P = 0.003), 48 h (1.04 [1.02-1.06], P < 0.001) and discharge (1.02 [1.01-1.03], P < 0.001) independently predicted one-year mortality, while only pre-discharge NT-proBNP was predictive (1.07 [1.01-1.13], P = 0.016). Comparable results could be obtained for the secondary endpoint 30-days mortality but not for one-year HF readmissions.

          Conclusions

          BNP and NT-proBNP reliably predict one-year mortality in patients with ADHF. Prognostic accuracy of both biomarker increases during the course of hospitalization. In survivors BNP levels decline more rapidly than NT-proBNP levels and thus seem to allow earlier assessment of treatment efficacy. Ability to predict one-year HF readmission was poor for BNP and NT-proBNP.

          Trial registration

          ClinicalTrials.gov identifier: NCT00514384.

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          Most cited references53

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          Prediction of Creatinine Clearance from Serum Creatinine

          A formula has been developed to predict creatinine clearance (C cr ) from serum creatinine (S cr ) in adult males: Ccr = (140 – age) (wt kg)/72 × S cr (mg/100ml) (15% less in females). Derivation included the relationship found between age and 24-hour creatinine excretion/kg in 249 patients aged 18–92. Values for C cr were predicted by this formula and four other methods and the results compared with the means of two 24-hour C cr’s measured in 236 patients. The above formula gave a correlation coefficient between predicted and mean measured Ccr·s of 0.83; on average, the difference between predicted and mean measured values was no greater than that between paired clearances. Factors for age and body weight must be included for reasonable prediction.
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            Prediction of creatinine clearance from serum creatinine.

            A formula has been developed to predict creatinine clearance (Ccr) from serum creatinine (Scr) in adult males: (see article)(15% less in females). Derivation included the relationship found between age and 24-hour creatinine excretion/kg in 249 patients aged 18-92. Values for Ccr were predicted by this formula and four other methods and the results compared with the means of two 24-hour Ccr's measured in 236 patients. The above formula gave a correlation coefficient between predicted and mean measured Ccr's of 0.83; on average, the difference predicted and mean measured values was no greater than that between paired clearances. Factors for age and body weight must be included for reasonable prediction.
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              Cardiorenal syndrome.

              The term cardiorenal syndrome (CRS) increasingly has been used without a consistent or well-accepted definition. To include the vast array of interrelated derangements, and to stress the bidirectional nature of heart-kidney interactions, we present a new classification of the CRS with 5 subtypes that reflect the pathophysiology, the time-frame, and the nature of concomitant cardiac and renal dysfunction. CRS can be generally defined as a pathophysiologic disorder of the heart and kidneys whereby acute or chronic dysfunction of 1 organ may induce acute or chronic dysfunction of the other. Type 1 CRS reflects an abrupt worsening of cardiac function (e.g., acute cardiogenic shock or decompensated congestive heart failure) leading to acute kidney injury. Type 2 CRS comprises chronic abnormalities in cardiac function (e.g., chronic congestive heart failure) causing progressive chronic kidney disease. Type 3 CRS consists of an abrupt worsening of renal function (e.g., acute kidney ischemia or glomerulonephritis) causing acute cardiac dysfunction (e.g., heart failure, arrhythmia, ischemia). Type 4 CRS describes a state of chronic kidney disease (e.g., chronic glomerular disease) contributing to decreased cardiac function, cardiac hypertrophy, and/or increased risk of adverse cardiovascular events. Type 5 CRS reflects a systemic condition (e.g., sepsis) causing both cardiac and renal dysfunction. Biomarkers can contribute to an early diagnosis of CRS and to a timely therapeutic intervention. The use of this classification can help physicians characterize groups of patients, provides the rationale for specific management strategies, and allows the design of future clinical trials with more accurate selection and stratification of the population under investigation.
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                Author and article information

                Journal
                Crit Care
                Critical Care
                BioMed Central
                1364-8535
                1466-609X
                2011
                5 January 2011
                : 15
                : 1
                : R1
                Affiliations
                [1 ]Department of Internal Medicine, University Hospital Basel, Petersgraben 4, 4053 Basel, Switzerland
                [2 ]Department of Cardiology, University Hospital Basel, Petersgraben 4, 4053 Basel, Switzerland
                Article
                cc9398
                10.1186/cc9398
                3222028
                21208408
                1b769e2d-511d-4285-a75a-1400d7d72d95
                Copyright ©2011 Noveanu et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 19 July 2010
                : 9 September 2010
                : 5 January 2011
                Categories
                Research

                Emergency medicine & Trauma
                Emergency medicine & Trauma

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