Incremental prognostic value of a novel metabolite-based biomarker score in congestive heart failure patients

新型代谢物生物标志物评分在充血性心力衰竭患者中的增量预后价值

阅读:1

Abstract

AIMS: The Cardiac Lipid Panel (CLP) is a newly discovered panel of metabolite-based biomarkers that has shown to improve the diagnostic value of N terminal pro B type natriuretic peptide (NT-proBNP). However, little is known about its usefulness in predicting outcomes. In this study, we developed a risk score for 4-year cardiovascular death in elderly chronic heart failure (CHF) patients using the CLP. METHODS AND RESULTS: From the Cardiac Insufficiency Bisoprolol Study in Elderly trial, we included 280 patients with CHF aged >65 years. A targeted metabolomic analysis of the CLP biomarkers was performed on baseline serum samples. Cox regression was used to determine the association of the biomarkers with the outcome after accounting for established risk factors. A risk score ranging from 0 to 4 was calculated by counting the number of biomarkers above the cut-offs, using Youden index. During the mean (standard deviation) follow-up period of 50 (8) months, 35 (18%) subjects met the primary endpoint of cardiovascular death. The area under the receiver operating curve for the model based on clinical variables was 0.84, the second model with NT-proBNP was 0.86, and the final model with the CLP was 0.90. The categorical net reclassification index was 0.25 using three risk categories: 0-60% (low), 60-85% (intermediate), and >85% (high). The continuous net reclassification index was 0.772, and the integrated discrimination index was 0.104. CONCLUSIONS: In patients with CHF, incorporating a panel of three metabolite-based biomarkers into a risk score improved the prognostic utility of NT-proBNP by predicting long-term cardiovascular death more precisely. This novel approach holds promise to improve clinical risk assessment in CHF patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。