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急性冠状动脉综合征患者的炎症与抗炎可变簇及风险预测:一种因子分析方法

Inflammatory and anti-inflammatory variable clusters and risk prediction in acute coronary syndrome patients: a factor analysis approach.

作者信息

Tziakas Dimitrios N, Chalikias Georgios K, Kaski Juan Carlos, Kekes Angelos, Hatzinikolaou Eleni I, Stakos Dimitrios A, Tentes Ioannis K, Kortsaris Alexandros X, Hatseras Dimitrios I

机构信息

University Cardiology Department, Democritus University of Thrace, Voulgaroktonou 23, 68100 Alexandroupolis, Greece.

出版信息

Atherosclerosis. 2007 Jul;193(1):196-203. doi: 10.1016/j.atherosclerosis.2006.06.016. Epub 2006 Jul 20.

Abstract

BACKGROUND

Numerous inflammatory mediators such as C-reactive protein (CRP), fibrinogen, interleukin-18 (IL-18), and inter-cellular adhesion molecule-1 (ICAM-1) have been proposed for risk stratification in acute coronary syndrome (ACS) patients. However, interactions between these markers have made it difficult to assess their true role in risk prediction. Factor analysis is a multivariable statistical technique that reduces a large number of intercorrelated variables to a smaller set of independent clusters, underlining physiological relationships. The aim of this study was to investigate, using factor analysis, a clustering of pro-inflammatory markers, anti-inflammatory cytokines such as interleukin-10 (IL-10) and HDL cholesterol, and to determine their role in prediction of risk of recurrent coronary events in ACS patients.

METHODS

We assessed 320 consecutive patients (236 men; 67 years; IQ 58-74 years) admitted with ACS. The composite of cardiac death and re-hospitalization with non-fatal myocardial infarction, or unstable angina, was the pre-specified study end-point. Serum CRP, fibrinogen, HDL cholesterol, IL-10, IL-18 and ICAM-1 levels were measured at study entry. We assessed independent predictors of the combined end-point during a 1-year follow-up using multiple logistic regression analysis.

RESULTS

Factor analysis identified three clusters which were arbitrarily interpreted as (1) a "systemic inflammation" cluster with positive loadings of CRP and fibrinogen, (2) a "local inflammation-endothelial dysfunction" cluster with positive loadings of IL-18 and ICAM-1 and (3) an "anti-inflammation" cluster comprising IL-10 and HDL cholesterol. Only the "anti-inflammation" cluster was a significant predictor (OR 0.66, 95% CI: 0.49-0.89) of adverse cardiac events during a 1-year follow-up and remained significant (OR 0.65, 95% CI: 0.48-0.88) in a multivariate model that included all three factors.

CONCLUSIONS

Although inflammatory markers such as CRP predict future cardiovascular events in ACS patients, when all inflammatory mediators are taken into account in a prospective analysis of risk, markers reflecting anti-inflammatory mechanisms are better prognostic markers.

摘要

背景

许多炎症介质,如C反应蛋白(CRP)、纤维蛋白原、白细胞介素-18(IL-18)和细胞间黏附分子-1(ICAM-1),已被用于急性冠状动脉综合征(ACS)患者的风险分层。然而,这些标志物之间的相互作用使得难以评估它们在风险预测中的真正作用。因子分析是一种多变量统计技术,它将大量相互关联的变量减少为一组较小的独立聚类,突出生理关系。本研究的目的是使用因子分析来研究促炎标志物、抗炎细胞因子如白细胞介素-10(IL-10)和高密度脂蛋白胆固醇的聚类情况,并确定它们在预测ACS患者复发性冠状动脉事件风险中的作用。

方法

我们评估了320例连续入院的ACS患者(236例男性;年龄67岁;四分位间距58 - 74岁)。心脏死亡以及因非致命性心肌梗死或不稳定型心绞痛再次住院的复合情况是预先设定的研究终点。在研究开始时测量血清CRP、纤维蛋白原、高密度脂蛋白胆固醇、IL-10、IL-18和ICAM-1水平。我们使用多因素逻辑回归分析评估了1年随访期间联合终点的独立预测因素。

结果

因子分析确定了三个聚类,分别被任意解释为:(1)一个“全身炎症”聚类,CRP和纤维蛋白原呈正负荷;(2)一个“局部炎症 - 内皮功能障碍”聚类,IL-18和ICAM-1呈正负荷;(3)一个“抗炎”聚类,包括IL-10和高密度脂蛋白胆固醇。在1年随访期间,只有“抗炎”聚类是不良心脏事件的显著预测因素(比值比0.66,95%置信区间:0.49 - 0.89),并且在包含所有三个因素的多变量模型中仍然显著(比值比0.65,95%置信区间:0.48 - 0.88)。

结论

尽管诸如CRP等炎症标志物可预测ACS患者未来的心血管事件,但在对风险进行前瞻性分析时,如果将所有炎症介质都考虑在内,反映抗炎机制的标志物是更好的预后标志物。

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