循环内皮细胞对冠心病心血管事件的预测价值

目的 探讨循环内皮细胞(CEC)计数成为急性冠脉综合征(ACS)患者心血管风险预测的重要生物标志的有效性.方法 研究分析了110例ACS患者和30例健康人群作对照(HC组);根据其病史、症状、心电图、各种生化结果,利用两种不同的冠心病风险评分系统评估ACS患者的心血管事件风险:心肌梗死溶栓治疗临床试验(TIMI)评分评价非ST段抬高型心肌梗死(NSTEMI)/不稳定型心绞痛(UA)以及ST段抬高型心肌梗死(STEMI);全球急性冠状动脉事件注册(GRACE)评分评价所有冠心病;利用流式细胞仪检测静脉血CEC数.结果 与HC组比较,ACS患者组的CEC计数明显升高,并随疾病的严重程度进行性升高;CEC计数和心血管事件风险的高低明显相关,TIMI UA/NSTEMI、TIMI/STEMI、GRACE评分相关系数分别为0.47、0.64、0.61(P<0.05);CEC诊断急性心肌梗死中度可靠,受试者工作特征曲线下面积(AUC)=0.90(95% CI:0.84~0.94, P<0.01);CEC计数诊断ACS中度可信,AUC=0.89(95% CI:0.82~0.93,P<0.01) .结论 CEC计数的升高和ACS患者心血管事件的高风险密切相关,CEC可能成为心血管事件的有效预测因子.

The role of circulating endothelial cells in predicting the riskof cardiovascular events in patients with coronary artery disase

Objective To investigate the role of the circulating endothelial cells(CEC)-a direct biomarker of endothelial injury, in evaluating the cardiovascular risk in patients presenting with the acute coronary syndrome(ACS).Methods We studied 110 admitted patients diagnosed as acute coronary artery and 30 healthy controls(HC group).Cardiovascular risk scores were calculated in all ACS patients using two kinds of risk score systems: the thrombolysis in myocardial infarction scoring systems(TIMI) for non-ST-elevation myocardial infarction(NSTEMI)/unstable angina(UA) pectoris, ST-elevation myocardial infarction(STEMI) and the global registry of acute coronary events(GRACE) risk score for all ACS based on patients′ clinical history, symptom, electrocardiogramcharacteristic changes, biochemical outcomes;CEC counting was executed by flow cytometry.Results Compared with HC group, the CEC count of ACS patients was significantly increased, and increased with the severity of disease.There were significant correlation between CEC counts and risk scores(TIMI UA/NSTEMI r=0.47;TIMI STEMI r=0.64;GRACE r=0.61,P<0.05).The area under the receiver-operating characteristic curve(AUC) for the diagnosis of MI(NSTEMI/STEMI) was 0.90(95% CI:0.84~0.94,P<0.01), for the all ACS was 0.89(95% CI:0.82~0.93,P<0.01).Conclusion CEC counts go up with the increasing cardiovascular risk, which is possibly an effective predictive biomarker for clinical cardiovascular events.