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纤维蛋白原与白蛋白比值在急性冠状动脉综合征中的预测价值。

Predictive value of fibrinogen-to-albumin ratio in acute coronary syndrome.

作者信息

Çetin M, Erdoğan T, Kırış T, Özer S, Yılmaz A S, Durak H, Aykan A Ç, Şatıroğlu Ö

机构信息

Faculty of Medicine, Department of Cardiology, Recep Tayyip Erdogan University, Rize, Turkey.

Ataturk Training and Research Hospital, Department of Cardiology, Izmir Katip Celebi University, Izmir, Turkey.

出版信息

Herz. 2020 Dec;45(Suppl 1):145-151. doi: 10.1007/s00059-019-4840-5. Epub 2019 Aug 6.

DOI:10.1007/s00059-019-4840-5
PMID:31388710
Abstract

BACKGROUND

We aimed to investigate the predictive value of the fibrinogen-to-albumin ratio (FAR) regarding the development of major cardiovascular events (MACE) in patients treated with percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS).

METHODS

This was a prospective, observational cohort study that included 261 consecutive patients who were treated with PCI. The patients were grouped according to the occurrence of MACE during the follow-up period.

RESULTS

During follow-up, MACE occurred in 68 (26%) patients. The FAR was independently predictive of MACE (HR: 1.017, 95% CI: 1.010-1.024, p < 0.001). In addition, left ventricular ejection fraction (LVEF) and a diagnosis of ST-segment elevation myocardial infarction (STEMI) were independent predictors of MACE. The area under the curve (AUC) of the multivariable model, including LVEF and diagnosis of STEMI, was 0.707 (95% CI: 0.631-0.782, p < 0.001). When the FAR was added to the multivariable model, the AUC was 0.770 (95% CI: 0.702-0.838, z = 2.820, difference p = 0.0048).

CONCLUSION

The FAR could be used for the prediction of MACE in patients with ACS who have undergone PCI.

摘要

背景

我们旨在研究纤维蛋白原与白蛋白比值(FAR)对接受经皮冠状动脉介入治疗(PCI)的急性冠状动脉综合征(ACS)患者发生主要心血管事件(MACE)的预测价值。

方法

这是一项前瞻性观察队列研究,纳入了261例连续接受PCI治疗的患者。根据随访期间MACE的发生情况对患者进行分组。

结果

随访期间,68例(26%)患者发生了MACE。FAR是MACE的独立预测指标(HR:1.017,95%CI:1.010-1.024,p<0.001)。此外,左心室射血分数(LVEF)和ST段抬高型心肌梗死(STEMI)诊断是MACE的独立预测因素。包含LVEF和STEMI诊断的多变量模型的曲线下面积(AUC)为0.707(95%CI:0.631-0.782,p<0.001)。当将FAR添加到多变量模型中时,AUC为0.770(95%CI:0.702-0.838,z = 2.820,差异p = 0.0048)。

结论

FAR可用于预测接受PCI的ACS患者发生MACE的情况。

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