Development and Validation of Risk Stratification for Heart Failure After Acute Coronary Syndrome Based on Dynamic S100A8/A9 Levels

基于动态S100A8/A9水平的急性冠脉综合征后心力衰竭风险分层的建立与验证

阅读:2

Abstract

BACKGROUND: The early assessment of heart failure (HF) risk in patients with acute coronary syndrome (ACS) can help reduce mortality. S100A8/A9 is not only rapidly released after myocardial ischemia, but is also involved in reperfusion injury, which is an important predictor of HF after ACS. We attempted to construct a reliable HF risk stratification tool for evaluating patients with ACS after reperfusion therapy based on S100A8/A9 dynamic changes. METHODS AND RESULTS: This prospective study included 3 independent cohorts of patients with ACS who received reperfusion therapy. The discovery cohort was divided into 2 subgroups: the longitudinal subgroup (n=264) with serum S100A8/A9 levels measured at admission and on days 1, 2, 3, and 4 postadmission, respectively, and the 2-point subgroup (n=798) with S100A8/A9 levels measured at admission and on day 1 postadmission, respectively. Validation cohorts 1 (n=1399) and 2 (n=1183) both had S100A8/A9 levels measured on day 1 postadmission. HF events included in-hospital HF events after the initial presentation and long-term HF events after discharge. The median follow-up for the discovery cohort, validation cohort 1, and validation cohort 2 was 4.2, 2.6, and 1.8 years, respectively. In the discovery cohort, S100A8/A9's predictive ability at day 1 surpassed other time points. Through the S100A8/A9-guided risk stratification, patients deemed high risk (>7900 ng/mL) exhibited a higher 1-year HF event rate (46% versus 2%, 38% versus 5%) than patients at low risk (<2100 ng/mL) in both validation cohorts. Among patients without left ventricular dysfunction after ACS, β-blocker therapy correlated with reduced 1-year HF events in intermediate-to- high-risk patients but not in low-risk patients. CONCLUSIONS: S100A8/A9 levels on day 1 accurately classified patients at varying risks of HF, serving as a robust tool for HF risk prediction and treatment guidance. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03752515.

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。