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目的:探讨Framingham卒中风险评分(FSP)结合血浆炎症因子(Hs-CRP、IL-6、TNF-α和LpPLA2)水平构建预测首发脑卒中的新模型的预测价值。方法:选择2014年8月至2015年6月于东莞市厚街医院住院的首发脑卒中患者101例为,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。利用多因素Logistic回归分析FSP及炎症因子水平在预测脑卒中发生的价值,通过ROC曲线及Z检验比较分析各预测模型的诊断价值及差异。结果:随着FSP定义的脑卒中危险度的增加,炎症因子表达水平显著升高;回归分析显示卒中独立危险因素包括:FSP(OR=2.85,95%CI:1.05-7.23)、IL-6(OR=6.53,95%CI:1.76-21.71)和Lp-PLA2(OR=7.75,95%CI:2.15-53.45)。单纯FSP、单纯炎症因子、FSP+炎症因子预测模型的受试者工作曲线下面积分别为0.588、0.850和0.861。结论:FSP、IL-6和Lp-PLA2是脑卒中发生的独立危险因素,将IL-6和Lp-PLA2纳入预测模型可有效提高首发脑卒中的预测效率。
Objective: To investigate the predictive value of Framingham Stroke Risk Score (FSP) combined with plasma levels of inflammatory cytokines (Hs-CRP, IL-6, TNF-α and LpPLA2) Methods: A total of 101 stroke patients admitted to Houjie Hospital of Dongguan City from August 2014 to June 2015 were selected as the control group. 156 non-stroke community residents were randomly matched by age and sex. Multivariate logistic regression analysis was used to analyze the value of FSP and inflammatory cytokines in the prediction of stroke. The diagnostic value and differences of each prediction model were analyzed by ROC curve and Z test. Results: The expression of inflammatory cytokines was significantly increased with the increase of stroke risk as defined by FSP. Regression analysis showed that the independent risk factors of stroke included FSP (OR = 2.85, 95% CI: 1.05-7.23), IL-6 OR = 6.53, 95% CI: 1.76-21.71) and Lp-PLA2 (OR = 7.75, 95% CI: 2.15-53.45). The area under the working curve of subjects with simple FSP, simple inflammation factor and FSP + inflammatory factor prediction model were 0.588,0.850 and 0.861 respectively. Conclusion: FSP, IL-6 and Lp-PLA2 are independent risk factors for stroke. The inclusion of IL-6 and Lp-PLA2 in the prediction model can effectively improve the prediction efficiency of the first stroke.