Amino-Terminal Pro-B-Type Natriuretic Peptide for Risk Prediction in Acute Decompensated Heart Failure

Domenico Scrutinio MD, Pietro Guida PhD, Andrea Passantino MD, Rocco Lagioia MD, Silvana Pepe BSc, Raffaella Catanzaro MD, Daniela Santoro MD
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引用次数: 3

Abstract

©2012 Wiley Periodicals Inc.

Amino-terminal pro-B-type natriuretic peptide (NT-proBNP) has been associated with prognosis in heart failure. The aim of this study was to assess whether NT-proBNP enhances risk prediction in acute decompensated heart failure (ADHF). The authors enrolled 453 patients hospitalized for ADHF. The primary outcome was 12-month mortality. Two separate multivariable predictive models were built by using standard variables–only and NT-proBNP concentrations. The models were internally validated using the bootstrapping method. Twelve-month mortality was 28.3%. There was no statistical evidence of overfit. Compared with the standard variables–only model, the NT-proBNP model had a better predictive performance as judged by the Nagelkerke R2 (0.410 vs 0.374) and the Brier score (0.136 vs 0.141), which are measures of overall performance; the Akaike Information Criterion (399.2 vs 415.0), which is a tool for model selection; and the C index (0.844 vs 0.831), which is a measure of the discriminative ability. Both models were well calibrated, as judged by the Hosmer-Lemeshow chi-square test. Both models predicted 12-month mortality significantly better than the Enhanced Feedback for Effective Cardiology Treatment risk score. In conclusion, the NT-proBNP model improved risk prediction compared with the standard variables–only model.

Abstract Image

氨基末端前b型利钠肽用于急性失代偿性心力衰竭的风险预测
氨基末端前b型利钠肽(NT-proBNP)与心力衰竭的预后相关。本研究的目的是评估NT-proBNP是否能增强急性失代偿性心力衰竭(ADHF)的风险预测。作者招募了453名ADHF住院患者。主要终点为12个月死亡率。分别使用标准变量和NT-proBNP浓度建立了两个独立的多变量预测模型。采用自举法对模型进行内部验证。12个月死亡率为28.3%。没有统计学上的过拟合证据。通过Nagelkerke R2 (0.410 vs 0.374)和Brier评分(0.136 vs 0.141)来判断,NT-proBNP模型与标准变量模型相比具有更好的预测性能;赤池信息标准(399.2 vs 415.0),这是模型选择的工具;C指数(0.844 vs 0.831),是衡量辨别能力的指标。根据Hosmer-Lemeshow卡方检验,两个模型都经过了很好的校准。两种模型对12个月死亡率的预测都明显优于有效心脏病治疗的增强反馈风险评分。综上所述,NT-proBNP模型比标准变量模型提高了风险预测。
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