中国临床实用医学
中國臨床實用醫學
중국림상실용의학
CHINA CLINICAL PRACTICAL MEDICINE
2010年
6期
97-100
,共4页
代谢综合征%尿微量白蛋白%胰岛素抵抗指数%回归分析
代謝綜閤徵%尿微量白蛋白%胰島素牴抗指數%迴歸分析
대사종합정%뇨미량백단백%이도소저항지수%회귀분석
Metabolic syndrome%Microalbuminuria%Insulin resistance index%Regression analysis
目的 探讨尿微量白蛋白(Microalbuminuria,mAlb)与代谢综合征(Metabolic Syndrome,MS)胰岛素抵抗组成成分的相互关系.方法 随机选取147个的代谢综合征患者,统计患者一般信息,测定其尿微量白蛋白(mAlb)、血糖和C肽等代谢综合征组分相关指标.根据尿微量白蛋白量将研究对象分组,比较代谢综合征胰岛素抵抗组分相关指标的差异,并进行相关、回归分析;进行尿微量白蛋白为因变量与代谢综合征胰岛素抵抗组分为自变量的多重回归分析和Logistic回归分析.结果 尿微量白蛋白正常组的代谢综合胰岛素抵抗征组分的指标较增高组差异有统计学意义(P＜0.001),尿微量白蛋白与代谢综合征胰岛素抵抗组分的指标呈正相关(R=0.282,P=0.024).成功建立了以尿微量白蛋白为因变量,年龄和胰岛素抵抗指数[CP]为自变量的多重回归方程(P=0.001);以尿微量白蛋白为因变量,胰岛素抵抗指数为自变量的Logistic回归模型(P=0.031).结论 代谢综合征患者的胰岛素抵抗可能是尿微量白蛋白的重要危险因素.
目的 探討尿微量白蛋白(Microalbuminuria,mAlb)與代謝綜閤徵(Metabolic Syndrome,MS)胰島素牴抗組成成分的相互關繫.方法 隨機選取147箇的代謝綜閤徵患者,統計患者一般信息,測定其尿微量白蛋白(mAlb)、血糖和C肽等代謝綜閤徵組分相關指標.根據尿微量白蛋白量將研究對象分組,比較代謝綜閤徵胰島素牴抗組分相關指標的差異,併進行相關、迴歸分析;進行尿微量白蛋白為因變量與代謝綜閤徵胰島素牴抗組分為自變量的多重迴歸分析和Logistic迴歸分析.結果 尿微量白蛋白正常組的代謝綜閤胰島素牴抗徵組分的指標較增高組差異有統計學意義(P＜0.001),尿微量白蛋白與代謝綜閤徵胰島素牴抗組分的指標呈正相關(R=0.282,P=0.024).成功建立瞭以尿微量白蛋白為因變量,年齡和胰島素牴抗指數[CP]為自變量的多重迴歸方程(P=0.001);以尿微量白蛋白為因變量,胰島素牴抗指數為自變量的Logistic迴歸模型(P=0.031).結論 代謝綜閤徵患者的胰島素牴抗可能是尿微量白蛋白的重要危險因素.
목적 탐토뇨미량백단백(Microalbuminuria,mAlb)여대사종합정(Metabolic Syndrome,MS)이도소저항조성성분적상호관계.방법 수궤선취147개적대사종합정환자,통계환자일반신식,측정기뇨미량백단백(mAlb)、혈당화C태등대사종합정조분상관지표.근거뇨미량백단백량장연구대상분조,비교대사종합정이도소저항조분상관지표적차이,병진행상관、회귀분석;진행뇨미량백단백위인변량여대사종합정이도소저항조분위자변량적다중회귀분석화Logistic회귀분석.결과 뇨미량백단백정상조적대사종합이도소저항정조분적지표교증고조차이유통계학의의(P＜0.001),뇨미량백단백여대사종합정이도소저항조분적지표정정상관(R=0.282,P=0.024).성공건립료이뇨미량백단백위인변량,년령화이도소저항지수[CP]위자변량적다중회귀방정(P=0.001);이뇨미량백단백위인변량,이도소저항지수위자변량적Logistic회귀모형(P=0.031).결론 대사종합정환자적이도소저항가능시뇨미량백단백적중요위험인소.
Objective To explore relationships of microalbuminuria(mAlb) and Insulin resistance in patients with metabolic syndrome(MS). Methods We randomly assigned 147 patients with MS from YongZhou Vocational Technique College affiliated hospital. We collected general information, mAlb, blood glucose, C peptide from individuals. We performed the compare means analysis for components of metabolic syndrome in patients with different mAlb. In addition, we also performed correlation and regression analysis for them. Further,we performed multiple regressions and logistic regression analysis to detect potential predicts and risk factors.Results We could find that HomaIR[CP] component of MS were significantly difference between in normal mAlb group and another group(P＜0.001), mAlb were position correlate with HomaIR[CP] components of MS ( R = 0.282, P=0.024); We successfully generate multiple regression function involving mAlb and Age and HomaIR [CP], and a logistic regression function including mAlb and HomaIR [ CP] ( P = 0. 031 ). Conclusion The results provide evidence that HomaIR should be an impotent risk factor for mAlb in patients with metabolic syndrome.
