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血浆炎症因子在首发脑卒中患者中的改变及其意义 被引量:5

The Change and Significance of Plasma Inflammatory Factors in Patients with Initial Stroke
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摘要 目的:探讨血浆炎症因子(hs-CRP、IL-6、TNF-α和Lp-PLA2)水平在首发脑卒中患者中的变化,并评价其预测脑卒中的意义。方法:选择2014年8月-2015年6月于东莞市厚街医院住院的首发脑卒中患者101例,同期按年龄、性别随机匹配的156例社区非卒中人群为对照组。检测血糖、血脂及血浆炎症因子水平,并通过ROC曲线评价炎症细胞因子在预测脑卒中发生的价值。结果:病例组血糖高于对照组,差异有统计学意义(P=0.000);两组的总胆固醇和高密度脂蛋白的含量比较,差异均有统计学意义(P=0.000);两组的炎症因子hs-CRP、IL-6、TNF-α和Lp-PLA2的水平比较,差异均有统计学意义(P=0.000)。单纯炎症细胞因子模型预测发生脑卒中的ROC下面积为0.850[95%CI(0.796,0.893)],灵敏度为80.5%,特异度为83.7%。结论:首发脑卒中患者的血浆炎症因子显著改变,炎症因子预测模型可有效预测首发脑卒中的发生。 Objective:To investigate the changes of plasma inflammatory factors (hs-CRP,IL-6, TNF-α and Lp-PLA2) levels in patients with first stroke,and to evaluate the significance of the prediction of stroke.Method:101 patients with stroke in Dongguan Houjie Hospital from August 2014 to June 2015 were selected,and the same time,156 community-dwelling healthy controls were recruited as the control group.Blood glucose,blood lipids and plasma levels of inflammatory factors were detected,and the value of inflammatory cytokines in predicting the occurrence of stroke was evaluated by ROC curve.Result:The blood glucose in the case group was higher than that in the control group,the difference was statistically significant (P=0.000).The total cholesterol and high density lipoprotein levels of the two groups were compared,the differences were statistically significant(P=0.000).The levels of inflammatory factors,IL-6,TNF-α, Lp-PLA2 and hs-CRP in the two groups were compared,the differences were statistically significant(P=0.000). The area of ROC in the prediction of cerebral stroke was 0.850[95%CI(0.796,0.893)],the sensitivity was 80.5%,the specificity was 83.7%.Conclusion:The levels of plasma inflammatory cytokines in patients with first episode of stroke are significantly changed,the prediction model of inflammatory factors can effectively predict the occurrence of stroke.
出处 《中国医学创新》 CAS 2016年第33期1-4,共4页 Medical Innovation of China
基金 东莞市社会科技发展基金资助(2013108101023)
关键词 脑卒中 IL-6 TNF-Α LP-PLA2 风险预测模型 Stroke hs-CRP IL-6 TNF- α Lp-PLA2 Risk prediction model
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