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脑利钠肽预测心原性猝死和室性心律失常的meta 分析。

Brain natriuretic peptide for the prediction of sudden cardiac death and ventricular arrhythmias: a meta-analysis.

机构信息

Wessex Cardiothoracic Unit, Southampton University Hospitals NHS Trust, Tremona Road, Southampton SO16 6YD, UK.

出版信息

Eur J Heart Fail. 2009 Oct;11(10):958-66. doi: 10.1093/eurjhf/hfp123.

Abstract

AIMS

The risk stratification of patients for sudden cardiac death (SCD) remains a challenge. Brain natriuretic peptide (BNP) predicts overall mortality in heart disease but it is unclear how well it predicts SCD. We therefore performed a meta-analysis of studies evaluating the accuracy of BNP to predict SCD and ventricular arrhythmias (VA).

METHODS AND RESULTS

Electronic databases and published bibliographies were systematically searched (1984-2008). We found 14 studies that met our inclusion criteria. Six studies (3543 patients) evaluated BNP to predict SCD in patients without implantable cardioverter defibrillators (ICDs) across a wide range of populations. A raised BNP predicted SCD with a relative risk of 3.68 [95% confidence interval (CI) 1.90, 7.14]. Eight studies (1047 patients) evaluated BNP to predict the occurrence of VA in patients with ICDs. A raised BNP predicted the occurrence of VA with a relative risk of 2.54 (95% CI 1.87, 3.44).

CONCLUSION

The measurement of BNP has significant value in predicting SCD and VA. However, the benefit of BNP testing in addition to other risk stratification tests is unclear and BNP needs to be evaluated prospectively in combination with other complementary risk stratification tools.

摘要

目的

心脏性猝死(SCD)患者的危险分层仍然是一个挑战。脑钠肽(BNP)预测心脏疾病的总死亡率,但它如何预测 SCD 尚不清楚。因此,我们对评估 BNP 预测 SCD 和室性心律失常(VA)准确性的研究进行了荟萃分析。

方法和结果

电子数据库和已发表的文献进行了系统搜索(1984-2008 年)。我们找到了符合我们纳入标准的 14 项研究。其中 6 项研究(3543 例患者)评估了 BNP 在广泛人群中预测无植入式心脏复律除颤器(ICD)患者 SCD 的能力。升高的 BNP 预测 SCD 的相对风险为 3.68 [95%置信区间(CI)1.90,7.14]。8 项研究(1047 例患者)评估了 BNP 预测 ICD 患者 VA 发生的能力。升高的 BNP 预测 VA 的相对风险为 2.54(95% CI 1.87,3.44)。

结论

BNP 的测量对预测 SCD 和 VA 具有重要价值。然而,BNP 检测除其他危险分层检测外的益处尚不清楚,需要前瞻性评估 BNP 与其他互补危险分层工具相结合的效果。

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