中文摘要：

目的研究动脉粥样硬化高危人群中尿酸和脂蛋白a[Lp（a）1预测动脉粥样硬化性肾动脉狭窄（ARAS）的价值。方法回顾性分析2008年10月至2011年4月在北京协和医院怀疑为ARAS，并接受肾动脉造影的190例患者的临床资料，其中89例诊为ARAS；部分患者同时接受了冠脉造影。对照组为年龄、性别匹配的180例同期本院常规体检人群。收集一般临床资料、血尿酸（UA）、Lp（a）、胆固醇（TC）、三酰甘油（TG）、高密度脂蛋白（HDL）、低密度脂蛋白（LDL）、Scr和c反应蛋白（CRP）等。分析ARAS患者的临床特点和相关危险因素，并利用二元Logistic回归分析尝试建立在高危人群中预测ARAS的临床决策工具。结果ARAS患者的Scr、UA、Lp（a）和CRP水平显著地高于健康体检人群。高度怀疑ARAS或同时伴有冠状动脉病变而行肾动脉造影患者中，确诊ARAS组与非ARAS组生化指标、血脂、UA和肾功能差异均无统计学意义。二元Logistic回归分析显示，UA〉344μmol／L是ARAS发病的独立相关因素；且当UA〉344μmol／L和Lp（a）〉242mg／L时，预测ARAS的特异性达96％，阳性似然比为5．45，P=0．001，OR值为6．78，95％C1（1．90～24．2），P=0．001。结论ARAS的高危人群中，UA升高是ARAS的独立危险因素；UA联合Lp（a）对于预测ARAS有一定的临床意义。

英文摘要：

Objective To explore the value of uric acid （UA） combined with lipoprotein a [Lp（a）] in prediction of atherosclerotic renal artery stenosis （ARAS） in high risk population with atherosclerosis. Methods A total of 190 patients who were highly suspected for ARAS and received renal artery angiography in Peking Union Medical College Hospital from October 2008 to April 2011 were enrolled in the study. Among these patients, 120 were diagnosed as coronary arterial disease （CAD） by coronary artery angiography and 89 were diagnosed as ARAS. The control group included 180 people undergoing routine healthy examination in our hospital. The basic information and lab results such as UA, Lp （a）, total cholesterol （TC）, triacylglycerol （TG）, HDL, LDL, Scr and C-reactive protein （CRP） were collected. Logistic regression analysis was used to identify possible risk factors of ARAS and to establish a new tool to predict ARAS in the high risk population. Results The levels of Scr, UA, Lp （a） and CRP in ARAS cases were significantly elevated compared to control people. For high risk population, there were no significant differences in Scr, lipids, UA and CRP between ARAS cases and non-ARAS cases. Logistic regression analysis showed that UA level〉344 μmol/L was correlated to ARAS independently. Using UA level〉344 μmol/L and Lp （a） level〉242 mg/L as a predicting marker for ARAS in high risk population, the specificity was 96.0%, the positive likelihood ratio was 5.45 （P=0.001）, and the odds ratio was 6.78, 95%CI （1.90-24.2） （P=0.001）. Conclusions In high risk population, the UA may be an independent correlating factor of ARAS. Combining UA with Lp（a） can predict the ARAS.