脑白质疏松的危险因素及其与红细胞分布宽度相关性的探究

发布时间：2018-06-30 19:24

本文选题：脑白质疏松 + 红细胞分布宽度　；参考：《广西医科大学》2017年硕士论文

【摘要】：目的:研究脑白质疏松(white matter hypertensities,WMH)的危险因素及其与红细胞分布宽度(red blood cell distribution width,RDW)的相关性。方法:选取2015年1月至2016年10月在广西医科大学第一附属医院住院完善头颅MRI的患者,根据纳入及排除标准最终纳入研究的患者共146例,其中MRI正常的为共58例(非WMH组),MRI上仅表现为脑白质疏松的88例(WMH组),收集数据包括:(1)一般资料:性别、年龄、身高及体重并计算体重指数BMI;(2)既往史:高血压、糖尿病、脑卒中、冠心病、吸烟、饮酒史;(3)实验室数据:红细胞分布宽度、血红蛋白、平均红细胞体积、白细胞、中性粒细胞比例、总胆固醇、低密度脂蛋白胆固醇、高密度脂蛋白胆固醇、甘油三酯、同型半胱氨酸。(4)根据Fazekas评分标准对脑白质疏松严重程度进行评分。计量资料采用独立样本T检验,计数资料采用卡方c2检验,以单因素分析中有统计学意义(P0.05)的因素为自变量,以是否脑白质疏松为因变量应用二分类logistic回归分析探讨脑白质疏松的独立危险因素;以脑白质疏松严重程度为因变量,应用有序多分类logistic回归分析研究脑白质疏松及严重程度的独立危险因素。应用Spearman相关性检验分析脑白质疏松严重程度与红细胞分布宽度的相关性。应用Pearson相关性检验及Spearman相关性检验分析红细胞分布宽度与其他危险因素的相关性。结果:(1)与非WMH组相比,WMH组的年龄(37-86岁,64.40±10.15 vs.30-81岁,51.50±14.22)、高血压病史比例(52.8%vs.29.3%)、同型半胱氨酸(13.45±5.41 vs.11.69±4.82)、RDW水平(13.7%±1.29%vs.13.29%±0.83%)升高,而血红蛋白水平(125.89±13.64 vs.131.13±11.11)降低,差异有统计学意义(P㩳0.05)。进一步进行二分类Logistic回归分析提示年龄是脑白质疏松的独立危险因素(OR 1.080,95%CI 1.039~1.123,P㩳0.05)。(2)非WMH组、轻度WMH组、中-重度WMH组高血压病史比例(分别为29.3%、48.5%、70%,P=0.004),年龄(分别为51.50±14.22、62.25±9.99、71.70±6.84,P=0.000),RDW(分别为13.29±0.84、13.60±1.34、14.05±1.05,P=0.031)呈递增趋势,Hb(131.13±11.11、126.63±13.90、123.41±12.70,P=0.034)呈递减趋势,差异有统计学意义。进一步进行有序多分类Logistic回归分析,结果显示脑白质疏松严重程度的独立危险因素(OR 1.095,95%CI 1.057~1.135,P=0.000)。(3)Spearman相关性分析显示脑白质疏松严重程度与RDW(r=0.207,P=0.012)呈正相关。(4)Pearson相关性分析显示RDW与血红蛋白、MCV呈负相关(r分别为-0.390,-0.458,P0.05)。结论:(1)年龄是脑白质疏松发生和严重程度的独立危险因素。(2)红细胞分布宽度在脑白质疏松患者中升高,并与脑白质疏松严重程度呈正相关,红细胞分布宽度与脑白质疏松相关的机制还需要更大规模的、设计良好的实验进一步探究。
[Abstract]:Objective: To study the risk factors of white matter hypertensities (WMH) and its correlation with the distribution width of red blood cells (red blood cell distribution width, RDW). Methods: to select the head MRI patients at the First Affiliated Hospital of Guangxi Medical University from January 2015 to October 2016, according to the inclusion and exclusion criteria. A total of 146 patients were enrolled in the study, of which 58 cases (non WMH) were normal MRI and 88 cases of leukoaraiosis (group WMH) on MRI. The data included: (1) general data: sex, age, height and weight and calculate body mass index BMI; (2) history of hypertension, diabetes, stroke, coronary heart disease, smoking, drinking history; (3) laboratory number According to the distribution of red blood cells, hemoglobin, average red blood cell volume, white blood cell, neutrophils ratio, total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, triglyceride, homocysteine. (4) the severity of leukoaraiosis was evaluated according to the Fazekas score. The measurement data were measured by independent sample T The counting data were determined by chi square C2 test. The independent variables were statistically significant (P0.05) in the single factor analysis. The independent risk factors of leukoaraiosis were investigated by two classified logistic regression analysis on whether the leukoaraiosis was used as a dependent variable. With the severity of leukoaraiosis as the dependent variable, an orderly multi classification logistic regression was used. Analysis and study of independent risk factors of leukoaraiosis and severity. Spearman correlation test was used to analyze the correlation between the severity of leukoaraiosis and the distribution width of red blood cells. The correlation between Pearson correlation test and Spearman correlation test was used to analyze the correlation between red blood cell distribution width and other risk factors. (1) and non WMH The age of group WMH (37-86 years, 64.40 + 10.15 vs.30-81 years, 51.50 + 14.22), the history of hypertension (52.8%vs.29.3%), homocysteine (13.45 + 5.41 vs.11.69 + 4.82), RDW level (13.7% + 1.29%vs.13.29% + 0.83%), and the level of hemoglobin (125.89 + 13.64 vs.131.13 + 11.11) decreased, the difference was statistically significant (P? 0.05). Further two classification Logistic regression analysis showed that age was an independent risk factor for leukoaraiosis (OR 1.080,95%CI 1.039~1.123, P? 0.05). (2) non WMH group, mild WMH group, moderate to severe WMH group (29.3%, 48.5%, 70%, P=0.004), age (respectively 51.50 + 14.22,62.25 + 9.99,71.70 + 6.84 respectively, P=0.000). Do not be 13.29 + 0.84,13.60 + 1.34,14.05 + 1.05, P=0.031) increasing trend, Hb (131.13 + 11.11126.63 + 13.90123.41 + 12.70, P=0.034) showed a decreasing trend, and the difference was statistically significant. Further analysis of sequential multiple classification Logistic regression showed the independent risk factor of the severity of leukoaraiosis (OR 1.095,95%CI 1.057~1.135,) (3) (3) Spearman correlation analysis showed that the severity of leukoaraiosis was positively correlated with RDW (r=0.207, P=0.012). (4) Pearson correlation analysis showed that RDW was negatively correlated with hemoglobin and MCV (R is -0.390, -0.458, P0.05). (1) age is an independent risk factor for the occurrence and severity of leukoaraiosis. (2) the wide distribution of red blood cells The degree of leukoaraiosis is higher in patients with leukoaraiosis and is positively correlated with the severity of leukoaraiosis. The mechanism of red cell distribution and leukoaraiosis needs to be more large-scale, and well designed experiments are further explored.
【学位授予单位】：广西医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R743

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