慢性肾脏病患者腹高与Framingham风险评分、内皮特异性分子1相关性探讨
发布时间：2018-10-21 14:33
【摘要】：目的:1、分析在慢性肾脏病(chronic kidney disease CKD)患者中腹高(Sagittal Abdominal Diameter,SAD)与 CKD 并发心血管疾病(cardiovascular disease CVD)危险因素的相关性及SAD与Framingham风险评分相关性探讨;2、分析 SAD 与内皮特异性分子 1(endothelial specific molecule-1,ESM-1)的相关性以及内脏脂肪组织(visceral adipose tissue VAT)与炎症、内皮细胞功能紊乱的机制探讨。方法:1.收集2011年11月至2016年7月在我院肾脏内科住院CKD患者307例。测量身高及体重,计算体重指数(body mass index BMI);测量SAD;收集患者病史、临床指标计算Framingham风险评分。采用SPSS15.0进行统计学分析:Kolmogorov Smirnov检验所有计量资料是否为正态分布。符合正态分布以均数±标准差(x±s)表示,非正态分布以中位数和四分位数表示。分组间变量比较计数资料采用卡方检验(X2),计量资料采用方差分析(ANOVA)。各变量之间采用Spearman相关性分析。多重线性回归分析用于明确变量间依存关系,P0.05可认为差异有统计学意义。2.收集2015年至2016年昆明医科大学第一附属医院肾内科非透析CKD5期患者共69例,测量患者SAD、收集一般资料、病史,各项检查指标;血清ESM-1水平采用酶联免疫吸附法(ELISA)测定。采用SPSS15.0进行统计学分析:Kolmogorov Smirnov检验所有计量资料是否为正态分布。符合正态分布以均数±标准差(x±s)表示。分组间变量比较计数资料采用卡方检验(X2),计量资料采用T检验。各变量之间采用Spearman相关性分析。多重线性回归分析用于明确变量间依存关系,P0.05可认为差异有统计学意义。结果:1、Framingham 风险评分与年龄(P0.01)、BMI(P0.01)和SAD(P0.01)成显著正相关,与GFR呈负相关(P=0.068);采用多重线性回归模型对变量进行调整(校正R2=0.178)后SAD与Framingham仍呈现显著正相关(P0.01)。SAD 与年龄(P0.05)、GFR(P=0.068)、BMI(P0.05)、UA(P=0.055)呈正相关;采用多重线性回归模型对变量进行调整分析后(校正R2=0.409)显示,SAD 与 BMI(P0.01)、糖尿病病史(P0.01)、GFR(P0.01)和年龄(P0.01)呈显著正相关。2、在 69 例 CKD5 患者中 SAD(P0.05)与 LgESM-1 正相关,HGB(P0.05)与LgESM-1负相关。采用多重线性回归模型对年龄、吸烟等变量进行调整(校正R2为0.121),SAD(P0.05)与LgESM-1正相关,HGB(P0.05)与LgESM-1负相关。结论:1、在CKD患者中,CKD并发CVD的危险因素年龄、GFR、CRP与SAD呈正相关,Framingham风险评分与SAD正相关,SAD可作为未透析CKD患者Framingham风险评分潜在的预测因子。2、在非透析CKD5期患者中,SAD与血管内皮损伤标志物ESM-1正相关,可作为非透析CKD5期患者血管内皮损伤潜在的预测因子。
[Abstract]:Objective: 1 to analyze the correlation between high abdominal (Sagittal Abdominal Diameter,SAD and (cardiovascular disease CVD) risk factors in patients with chronic kidney disease (chronic kidney disease CKD) complicated with cardiovascular disease and the correlation between SAD and Framingham risk score; 2, to analyze the relationship between SAD and endothelium-specific molecules. (1) correlation of (endothelial specific molecule-1,ESM-1), (visceral adipose tissue VAT) of visceral adipose tissue and inflammation, Mechanism of endothelial cell dysfunction. Methods: 1. From November 2011 to July 2016, 307 patients with CKD were hospitalized in the Department of Renal Medicine in our hospital. Height and weight were measured, body mass index (body mass index BMI);) was calculated, SAD; was collected and Framingham risk score was calculated. SPSS15.0 was used to analyze the statistics and: Kolmogorov Smirnov was used to test whether all the metrological data were normal distribution. The normal distribution is expressed as mean 卤standard deviation (x 卤s), and the non-normal distribution is expressed as median and quartile. The counting data between groups were compared by chi-square test (X2), and the data were measured by analysis of variance (ANOVA). Spearman correlation analysis was used among the variables. Multiple linear regression analysis was used to clarify the relationship between variables, P0.05 can be considered the difference is statistically significant. 2. A total of 69 non-dialysis CKD5 patients were collected from 2015 to 2016 in the Department of Renal Medicine of the first affiliated Hospital of Kunming Medical University. The general data, medical history and various examination indexes of SAD, were measured. The serum ESM-1 level was determined by Elisa (ELISA). SPSS15.0 was used to analyze the statistics and: Kolmogorov Smirnov was used to test whether all the metrological data were normal distribution. The normal distribution is expressed as mean 卤standard deviation (x 卤s). The counting data were compared by chi-square test (X 2) and T test was used. Spearman correlation analysis was used among the variables. Multiple linear regression analysis was used to clarify the relationship between variables, P0.05 can be considered the difference is statistically significant. Results: (1) there was a significant positive correlation between SAD risk score and age (P0.01), BMI (P0.01) and SAD (P0.01), and a negative correlation between SAD and GFR (P0.068), and a significant positive correlation between SAD and Framingham (P0.01). SAD and age (P0.05), GFR (P0.068), BMI (P0.05), UA (P0.055) after adjusting variables with multiple linear regression model (R2C0.178). The multiple linear regression model was used to analyze the variables (adjusted R2P 0.409). SAD was positively correlated with BMI (P0.01), history of diabetes (P0.01), GFR (P0.01) and age (P0.01). In 69 cases of CKD5, SAD (P0.05) was negatively correlated with LgESM-1 (P 0.05) and LgESM-1 was negatively correlated with LgESM-1 (P 0.05). The multiple linear regression model was used to adjust the age, smoking and other variables (adjusted R2 was 0.121), SAD (P0.05) and LgESM-1 was positively correlated with, HGB (P0.05 and negatively correlated with LgESM-1. Conclusion: 1. In CKD patients, the age of risk factors of CKD complicated with CVD, GFR,CRP and SAD were positively correlated, and Framingham risk score was positively correlated with SAD. SAD could be used as a potential predictor of Framingham risk score in non-dialysis CKD patients. In non-dialysis CKD5 patients, SAD was associated with Framingham risk score. The vascular endothelial injury marker ESM-1 was positively correlated. It can be used as a potential predictor of vascular endothelial injury in non-dialysis CKD5 patients.
【学位授予单位】：昆明医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R692
本文编号：2285388
[Abstract]:Objective: 1 to analyze the correlation between high abdominal (Sagittal Abdominal Diameter,SAD and (cardiovascular disease CVD) risk factors in patients with chronic kidney disease (chronic kidney disease CKD) complicated with cardiovascular disease and the correlation between SAD and Framingham risk score; 2, to analyze the relationship between SAD and endothelium-specific molecules. (1) correlation of (endothelial specific molecule-1,ESM-1), (visceral adipose tissue VAT) of visceral adipose tissue and inflammation, Mechanism of endothelial cell dysfunction. Methods: 1. From November 2011 to July 2016, 307 patients with CKD were hospitalized in the Department of Renal Medicine in our hospital. Height and weight were measured, body mass index (body mass index BMI);) was calculated, SAD; was collected and Framingham risk score was calculated. SPSS15.0 was used to analyze the statistics and: Kolmogorov Smirnov was used to test whether all the metrological data were normal distribution. The normal distribution is expressed as mean 卤standard deviation (x 卤s), and the non-normal distribution is expressed as median and quartile. The counting data between groups were compared by chi-square test (X2), and the data were measured by analysis of variance (ANOVA). Spearman correlation analysis was used among the variables. Multiple linear regression analysis was used to clarify the relationship between variables, P0.05 can be considered the difference is statistically significant. 2. A total of 69 non-dialysis CKD5 patients were collected from 2015 to 2016 in the Department of Renal Medicine of the first affiliated Hospital of Kunming Medical University. The general data, medical history and various examination indexes of SAD, were measured. The serum ESM-1 level was determined by Elisa (ELISA). SPSS15.0 was used to analyze the statistics and: Kolmogorov Smirnov was used to test whether all the metrological data were normal distribution. The normal distribution is expressed as mean 卤standard deviation (x 卤s). The counting data were compared by chi-square test (X 2) and T test was used. Spearman correlation analysis was used among the variables. Multiple linear regression analysis was used to clarify the relationship between variables, P0.05 can be considered the difference is statistically significant. Results: (1) there was a significant positive correlation between SAD risk score and age (P0.01), BMI (P0.01) and SAD (P0.01), and a negative correlation between SAD and GFR (P0.068), and a significant positive correlation between SAD and Framingham (P0.01). SAD and age (P0.05), GFR (P0.068), BMI (P0.05), UA (P0.055) after adjusting variables with multiple linear regression model (R2C0.178). The multiple linear regression model was used to analyze the variables (adjusted R2P 0.409). SAD was positively correlated with BMI (P0.01), history of diabetes (P0.01), GFR (P0.01) and age (P0.01). In 69 cases of CKD5, SAD (P0.05) was negatively correlated with LgESM-1 (P 0.05) and LgESM-1 was negatively correlated with LgESM-1 (P 0.05). The multiple linear regression model was used to adjust the age, smoking and other variables (adjusted R2 was 0.121), SAD (P0.05) and LgESM-1 was positively correlated with, HGB (P0.05 and negatively correlated with LgESM-1. Conclusion: 1. In CKD patients, the age of risk factors of CKD complicated with CVD, GFR,CRP and SAD were positively correlated, and Framingham risk score was positively correlated with SAD. SAD could be used as a potential predictor of Framingham risk score in non-dialysis CKD patients. In non-dialysis CKD5 patients, SAD was associated with Framingham risk score. The vascular endothelial injury marker ESM-1 was positively correlated. It can be used as a potential predictor of vascular endothelial injury in non-dialysis CKD5 patients.
【学位授予单位】：昆明医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R692
【参考文献】
中国期刊全文数据库 前1条
1 严艳;汪年松;严海东;简桂花;张晓光;王晓霞;薛勤;高许萍;;双能X线评价慢性肾脏病患者营养状况的研究[J];中国中西医结合肾病杂志;2009年02期
，本文编号：2285388
本文链接：https://www.wllwen.com/yixuelunwen/mjlw/2285388.html
最近更新
教材专著
