The Predictive Value of N-Terminal Probrain Natriuretic Peptide for Infection in Patients With Acute Myocardial Infarction.

Abstract

Background: Infections increase the risk of poor outcomes in patients with ST-elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI). However, predicting patients at a high risk of developing infection remains unclear. Moreover, the value of N-terminal probrain natriuretic peptide (NT-proBNP) for predicting infection is still unknown. Thus, we aimed to assess the relationship between NT-proBNP and the following development of infection, and clinical adverse outcomes in patients with STEMI undergoing PCI. Methods: STEMI patients undergoing PCI were consecutively enrolled from January 2010 to July 2016 and divided into groups according to baseline NT-proBNP levels: tertiles T1 (<988 pg/mL), T2 (988-3520 pg/mL), and T3 (≥3520 pg/mL). The primary endpoint was infection during hospitalization. Results: A total of 182 (27%) patients developed in-hospital infection. The incidence of infection increased from T1 to T3 (10.5, 17.7, and 54.5%, P < 0.001). NT-proBNP was an independent risk factor (adjusted odds ratio = 1.39, 95% confidence interval (CI) = 1.12-1.73, P = 0.003) and presented accurately predicting infection (area under curve = 0.774). Multivariate cox analysis showed that NT-proBNP was a significant risk factor for major adverse clinical events (MACE) at follow-up (adjusted HR = 1.92, 95% CI = 1.61-2.29, P < 0.001). Conclusion: The baseline NT-proBNP level has a good predictive value for infection and MACE in STEMI patients undergoing PCI.

• Authors: YiNing Dai, XiaoLiang Wan, Can Liu, ChongYang Duan, Shuai Shao, HongHuan Chen, Litao Wang, JiJin Lin, Ling Xue, JiYan Chen, PengCheng He, YuanHui Liu, Ning Tan
• Journal: Frontiers in cardiovascular medicine (Front Cardiovasc Med) Vol. 8 Pg. 626724 ( 2021) ISSN: 2297-055X [Print] Switzerland
• PMID: 34513938 (Publication Type: Journal Article)
• Copyright: Copyright © 2021 Dai, Wan, Liu, Duan, Shao, Chen, Wang, Lin, Xue, Chen, He, Liu and Tan.