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作 者:沈国飞
机构地区:[1]苏州市吴江区中医医院内分泌科,江苏苏州215221
出 处:《南昌大学学报(医学版)》2014年第10期18-21,24,共5页Journal of Nanchang University:Medical Sciences
摘 要:目的研究大型血小板比率(P-LCR)、尿微白蛋白(MA)与2型糖尿病(T2DM)患者并发缺血性脑血管病(ICVD)的关系。方法选择83例T2DM并发缺血性脑血管病患者为观察组、94例单纯T2DM患者为对照组,对2组患者的年龄、性别、血压、血脂、尿酸、血糖、糖化血红蛋白、血小板参数及MA等相关因素进行分析比较,对影响T2DM患者并发ICVD相关因素采用逐步多因素Logistic回归分析,建立Logistic回归模型。用ROC曲线评价Logistic回归预测模型P1、P-LCR联合MA预测模型P2、P-LCR的预测能力。结果 2组MPV、PDW及P-LCR值与MA阳性率比较差异均有统计学意义(P=0.00)。多因素Logistic回归分析显示年龄、P-LCR、MA、收缩压、糖化血红蛋白是T2DM患者并发ICVD的独立危险因子。Logistic回归预测模型P1、P-LCR联合MA预测模型P2、P-LCR各自ROC曲线下面积分别为0.868、0.779、0.704(P=0.00)。结论 P-LCR、MA与T2DM并发ICVD有关,对P-LCR、MA联合监测及动态监测有助于T2DM并发ICVD的早期预测。Objective To investigate the relationships of platelet larger cell ratio(P-LCR)and urine microalbumin(MA)to type 2 diabetes mellitus(T2DM)complicated by ischemic cerebrovas-cular disease(ICVD).Methods The age,gender,blood pressure,blood lipid,uric acid,blood glu-cose,glycated hemoglobin,platelet parameters and MA were compared between patients with T2DM and ICVD(observation group,n=83)and patients with diabetes mellitus(control group, n=94).Multivariate stepwise logistic regression was performed to analyze ICVD-related factors in patients with T2DM.The predictive ability of ROC of logistic regression prediction model P1, P-LCR combined with MA prediction model P2,and P-LCR was evaluated by ROC curve.Results There were significant differences in MPV,PDW,P-LCR and MA between the two groups(P =0.00).Multivariate logistic regression analysis showed that the age,P-LCR,MA,systolic pressure and glycosylated hemoglobin were the independent risk factors for T2DM complicated by ICVD. The area under ROC curve was 0.868 for logistic regression prediction model P1,0.779 for P-LCR combined with MA prediction model P2,and 0.704 for P-LCR(P =0.00).Conclusion The P-LCR and MA are associated with T2DM complicated by ICVD.The dynamic monitoring of combined P-LCR and MA contributes to the early prediction of T2DM complicated by ICVD.
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