The prognostic value of the serum inflammatory biomarkers in patients with carotid atherosclerosis
20 % of ischemic stroke appear to originate from carotid artery atherosclerotic disease. Serum biomarkers reflecting the activity of atherosclerotic process and may help for estimate risk of acute cerebrovascular events. Several serum inflammatory markers have been proposed for risk assessment, but their prognostic role less known.
The aim of this study is to clarify the prognostic value of biomarkers of atherosclerosis lipoprotein-associated phospholipase A2 (Lp-PLA2) and E-selectin in patients with symptomatic and asymptomatic carotid stenosis.
Materials and methods. The study involved 106 patients with atherosclerotic carotid stenosis >50 % (74 men and 32 women, mean age 62.6±0.9) from which 76 symptomatic (35 with acute ipsilateral atherothrombotic stroke and 41 after carotid endarterectomy) and 30 asymptomatic patients. The control group consisted of age- and sex-matched 20 healthy subjects. The level of serum Lp-PLA2 and E-selectin was determined using a commercially available enzyme-linked immunosorbent assay kit.
Results. The level of Lp-PLA 2 was in general significantly higher (p<0.05) in patients groups than in the control group and most high Lp-PLA2 concentration was in groups of symptomatic patients who underwent carotid endarterectomy. The level of E-selectin in the study patients was significantly higher than in the control group (p<0.05). The correlation of Lp-PLA 2 with E-selectin was significant for total patients (R=0.365664, p=0.00085) and group after carotid endarterectomy (R=0.429143, p=0.01796), but not for asymptomatic group (p>0.05). Receiver Operating Characteristics curves of logistic regression models which takes into joint both indicators was specificity and sensitive for predicting the occurrence of ischemic stroke.
Conclusion. Conducted study show that the levels of Lp-PLA 2 and E-selectin have a significant impact on the development of stroke in patients with atherosclerotic carotid stenosis and can be used to predict it. A multidimensional model of the dependence of the probability of stroke on a linear combination of Lp-PLA 2 and E-selectin allows to obtaining significantly higher characteristics of the accuracy of stroke prediction than models with each factor alone.
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