踝臂指数与动脉硬化及其危险因素的关系

Relationship of Ankle Brachial Index,Atherosclerosis and Conventional Risk Factors

目的了解踝臂指数与动脉硬化及其危险因素的关系。方法对174例住院患者行选择性冠状动脉造影,用冠状动脉病变血管的数量和Gensini积分系统评价冠状动脉病变的严重程度。并进行踝臂指数测定、眼底动脉检查及动脉硬化的危险因素分析。结果冠状动脉正常组与冠状动脉病变组踝臂指数差异显著(P<0.001),冠状动脉造影积分和踝臂指数的Pearson积距相关系数为-0.768(P<0.001),冠状动脉造影积分越高,踝臂指数越低。眼底动脉正常组与眼底动脉病变组踝臂指数差异显著(P<0.001),眼底动脉病变越严重踝臂指数越小。眼底动脉正常组与眼底动脉病变组冠状动脉造影积分差异显著(P<0.001),眼底动脉病变越严重冠状动脉造影积分越高。以踝臂指数<0.9为二分类变量做Logistic回归分析,发现踝臂指数与年龄、性别、甘油三酯、低密度脂蛋白、吸烟量、糖尿病和遗传因素相关。结论踝臂指数是动脉硬化的一个简便可靠的预测因素,低踝臂指数与传统的动脉硬化危险因素如年龄、性别、甘油三酯、低密度脂蛋白、吸烟量、糖尿病和遗传因素有相关性。

Aim To study the relationship of ankle braehial index （ABI）, atherosclerosis and conventional risk factors. Methods 174 inpatients were performed coronary angiography, Gensini＇s coronary angiography score was calculated to quantify the extent of coronary artery atherosclerosis. ABI of all subjects were measured, retinal artery was inspected and risk factors of atherosclearosis were investigated. Results ABI between normal coronary angiography group and anormal coronary angiography group had statistically significant difference （ P 〈 0. 001 ）. There was an inverse linear trend between ABI and Gensini＇scoronary angiography score （ r= - 0.768, P 〈 0.001 ）, the more Gensini＇ s coronary angiography score the lower ABI. ABI between normal retinal artery group and anormal retinal artery group had statistically significant difference （ P 〈 0. 001 ）, the more severity of retinal artery the lower ABI. Gensini＇s coronary angiography score between normal retinal artery group and anormal retinal artery group had statistically significant difference （ P 〈 0.001 ）, the more severity of retinal artery the more Gensini＇s coronary angiography score. Logistic regression model analysis showed that risk factors including ages, sex, triglyceride, low density lipoprotein, quantity of smoking, diabetes and genetic factor were all associated with ABI significantly sions ABI is a handy and dependable predictor of atherosclerosis. ABI are all associated with conventional risk factors including ages, sex, triglyceride, low density lipoprotein, quantity of smoking, diabetes and genetic factor.