多中心维持性血液透析患者干体重与蛋白质能量消耗关系的临床研究

A multi-center clinical study on the relationship between dry weight and protein energy wasting in patients with maintenance hemodialysis

目的明确贵州省多中心血透患者干体重设置情况与蛋白质能量消耗(PEW)相关指标的关系,为更准确地设置患者干体重提供依据。方法收集 2018年5-8月贵州省11家维持性血液透析患者资料,问卷收集人口学特征资料;采用人体成分测量仪测量干体重、细胞外液、细胞内液、脂肪量、瘦体重等指标;采用卷尺及皮褶厚度测量仪等工具测量患者腰围、臀围、上臂中点周径、皮褶厚度、小腿围等指标。根据干体重设置情况分为3组。A组,干体重设置稍低组;B组,干体重设置正常组;C组,干体重设置稍高组。分析3组PEW患病情况,比较不同干体重设置组别间PEW相关指标是否存在差异,分析各测量指标及干体重控制情况与PEW患病程度的相关性及各因素对PEW的影响。结果干体重设置稍高组PEW重度患者发生率高于前两组(P<0.05),PEW相关指标上臂中点周径、三头肌皮褶厚度、臀围、脂肪量、BMI、血红蛋白、白蛋白、前白蛋白等指标均低于前两组(P<0.05)。相关性分析结果显示,各因素与PEW相关程度依次为BMI[(r=-0.677 ,P<0.05)、干体重(r=0.636,P<0.05)、上臂中点周径(r=-0.589 ,P<0.05)、白蛋白(r=-0.562,P<0.05)、臀围(r=-0.475,P<0.05)。影响PEW的因素有白蛋白(OR=0.883, 95%CI :0.782~0.997,P<0.05)、BMI(OR=0.671 ,95%CI :0.509~0.884,P<0.05)、上臂中点周径(OR=0.457 , 95%CI :0.318~0.655 ,P<0.05)、干体重(OR=1.191,95%CI :1.041~1.363,P<0.05)。结论干体重设置过高,脱水量不足,透析不充分增加了维持性血液透析患者PEW的发生风险。

Objective To explore the relationship between dry weight setting and the related parameters of PEW of multicenter hemodialysis patients in Guizhou. in order to provide the basis for setting dry weight in patients. Methods We conducted the research in patients of 11 hemodialysis center in Guizhou province. We collected demographic data(age, gender, nationality, marital status, education level, income status and so on) by questionnaire;are collected dry weight, ECW, ICW, fat mass,lean body mass and so on by bioelectrical impedance analysis, and then we also collected physical measurement indexes, such as waist circumference, hip circumference, medium arm circumference(MAC), tricep fold thickness(TSF)and crus diameter. The data is divided into three groups according to the dry weight setings. Group 1: dry weight setting was slightly lower(dry weight setted by doctors was slightly lower than bioelectrical impedance analysis results,withen 1 kg);group 2: dry weight setting was normal;group 3: dry weight setting slightly higher group(dry weight setted by doctors was slightly higher than bioelectrical impedance analysis results,withen 1 kg). We used Chi-square analysis to analyze PEW prevalence, compared differences of the PEW indications by variance analysis, and then we used Spearman correlation analysis to analyze the correlation between PEW and the indications. Influence of various factors on the PEW was analyzed by logistic regression analysis. Results The PEW morbidity of group 3 was higher than the other two groups. PEW indicators such as upper arm midpoint diameter, tricep fold thickness, hip circumference, fat mass, BMI, Hb, Alb and prealbumin were lower than the other two groups, the difference being statistically significant(P<0.05). Correlation analysis results show that the degree of the factors associated with the PEW was as follows in turn BMI(r=-0.677, P<0.05), dry weight(r=0.636, P<0.05), upper arm midpoint diameter(r=-0.589, P<0.05), albumin(r=-0.562, P<0.05) and hip circumference(r=-0.475, P<0.05). Logistic regression showed that the factors affecting PEW were albumin(OR = 0.883, 95%CI: 0.782-0.997, P<0.05), BMI(OR = 0.671, 95%CI: 0.509-0.884, P<0.05), upper arm midpoint diameter(OR = 0.457, 95% CI: 0.318-0.655, P<0.05) and dry weight(OR = 1.191, 95%CI: 1.041-1.363, P<0.05). Conclusion The dry weight setting too high, insufficient amount of ultrafiltration and inadequate dialysis can increase the occurrence of PEW.