Chen H, Peng C H
Department of Clinical Laboratory, the Third Xiangya Hospital of Central South University, Changsha 410013, China.
Zhonghua Yu Fang Yi Xue Za Zhi. 2022 Aug 6;56(8):1112-1117. doi: 10.3760/cma.j.cn112150-20211203-01118.
To investigate the application of bromocresol green Colorimetry (BCG) method in measuring serum albumin (ALB) and to evaluate its influencing factors in different diseases. This study was a cross-sectional study that included 128 people admitted to the department of nephrology, department of general surgery, department of infectious diseases and other departments of the Third Xiangya Hospital of Central South University in July 2021. They were divided into groups according to disease types, including chronic kidney disease group (47 cases), liver disease group (40 cases), other diseases group (41 cases), serum ALB was detected by BCG method and immunoturbidimetry at the same time, and the results were expressed as ALB and ALB respectively, each group was subdivided into three subgroups according to ALB results: relatively high-value subgroup, relatively intermediate-value subgroup and relatively low-value subgroup of albumin. ALB and ALB were compared in all groups and subgroups. Passing-Bablok regression and Bland-Altman diagram analysis were used to evaluate the application of ALB in each group. Immunoturbidimetry was used as a reference method to evaluate the bias of ALB, and the differences between ALB and ALB were shown as follows:ALB= ALB-ALB. Pearson correlation analysis and multiple linear regression analysis were used to assess the correlation between ALB and ALB autoconcentration (ALB), α-globulin, α-globulin, β-globulin, β-globulin, γ-globulin, creatinine (Cr), urea (UN), uric acid (UA), aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBil), direct bilirubin (DBil), and C-reactive protein (CRP) levels.The results showed that ALB were higher than ALB in the relative low subgroups of total patients group, chronic kidney disease group, liver disease group and other disease groups, and the differences were statistically significant ( value was 8.025, 6.878, 2.628, 4.915, respectively, <0.05). In the relatively high value subgroup, ALB was lower than ALB, and the differences were statistically significant in the relative high value subgroup of total patients group, liver disease group and other disease groups ( value was -4.388, -2.927, -3.979, <0.05). Passing-Bablok regression and Bland-Altman analysis showed that the BCG method had proportional bias. In the chronic kidney disease group, the concentrations of ALB and Cr had the greatest influence on BCG bias, and the regression model equation was ALB=5.437-0.146× Alb-0.001 ×Cr, ²=0.505. In the liver disease group, the concentrations of ALB, α-globulin, β-globulin had the greatest influence on BCG bias, and the regression model equation was ALB=3.652-0.230×ALB+0.398×α-globulin+1.171×β-globulin, ²=0.658. In the other disease group, the concentration of ALB and α-globulin had the greatest influence on BCG bias, and the regression equation was ALB=5.558-0.225×Alb-0.281×α-globulin, ²=0.646. The BCG method has a proportion error, and its bias may lead to unacceptable differences. BCG method is mainly affected by the concentration of ALB itself, and may also be affected by α-globulin, α -globulin, β-globulin, Cr.
探讨溴甲酚绿比色法(BCG法)在测定血清白蛋白(ALB)中的应用,并评估其在不同疾病中的影响因素。本研究为横断面研究,纳入了2021年7月在中南大学湘雅三医院肾内科、普通外科、感染科等科室住院的128例患者。根据疾病类型将其分组,包括慢性肾脏病组(47例)、肝脏疾病组(40例)、其他疾病组(41例),同时采用BCG法和免疫比浊法检测血清ALB,结果分别记为ALB和ALB,每组根据ALB结果再细分为三个亚组:白蛋白相对高值亚组、相对中值亚组和相对低值亚组。对所有组和亚组的ALB和ALB进行比较。采用Passing - Bablok回归和Bland - Altman图分析评估ALB在各组中的应用情况。以免疫比浊法作为参考方法评估ALB的偏差,ALB与ALB的差值表示为:ALB = ALB - ALB。采用Pearson相关分析和多元线性回归分析评估ALB与ALB自身浓度(ALB)、α球蛋白、α球蛋白、β球蛋白、β球蛋白、γ球蛋白、肌酐(Cr)、尿素(UN)、尿酸(UA)、天冬氨酸氨基转移酶(AST)、丙氨酸氨基转移酶(ALT)、总胆红素(TBil)、直接胆红素(DBil)及C反应蛋白(CRP)水平之间的相关性。结果显示,在总患者组、慢性肾脏病组、肝脏疾病组和其他疾病组的相对低值亚组中,ALB高于ALB,差异有统计学意义(值分别为8.025、6.878、2.628、4.915,均<0.05)。在相对高值亚组中,总患者组、肝脏疾病组和其他疾病组的相对高值亚组中ALB低于ALB,差异有统计学意义(值分别为 - 4.388、 - 2.927、 - 3.979,均<0.05)。Passing - Bablok回归和Bland - Altman分析显示BCG法存在比例偏差。在慢性肾脏病组中,ALB和Cr的浓度对BCG偏差影响最大,回归模型方程为ALB = 5.437 - 0.146×Alb - 0.001×Cr,² = 0.505。在肝脏疾病组中,ALB、α球蛋白、β球蛋白的浓度对BCG偏差影响最大,回归模型方程为ALB = 3.652 - 0.230×ALB + 0.398×α球蛋白 + 1.171×β球蛋白,² = 0.658。在其他疾病组中,ALB和α球蛋白的浓度对BCG偏差影响最大,回归方程为ALB = 5.558 - 0.225×Alb - 0.281×α球蛋白,² = 0.646。BCG法存在比例误差,其偏差可能导致不可接受的差异。BCG法主要受ALB自身浓度影响,也可能受α球蛋白、α球蛋白、β球蛋白、Cr的影响。