机构地区:[1]中南大学湘雅二医院检验医学科,长沙410011
出 处:《中华检验医学杂志》2023年第7期689-696,共8页Chinese Journal of Laboratory Medicine
摘 要:目的比较3种血脂检测系统结果的差异, 分析其对血脂管理中危险分层及临床决策的影响, 并寻找减小影响的方法。方法在2022年8—10月中南大学湘雅二医院体检者及住院患者中收集甘油三酯(TG)<4.5 mmol/L的血清样本196份, 分别用日立-和光(HW)、罗氏、迈瑞3种系统直接检测TG、总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C), 并由公式(TC-HDL-C)计算非高密度脂蛋白胆固醇(非HDL-C)以及根据Friedewald公式计算LDL-C(F-LDL-C), 进行方法学对比。分别计算这6个指标在3种检测系统间的变异系数(CV), 评价结果的一致性, 用Pearson相关系数评价各指标在不同系统间的相关性。根据《中国血脂管理指南》推荐的不同危险分层LDL-C的达标值将样本分成<1.4、1.4~<1.8、1.8~<2.6、2.6~<3.4和≥3.4 mmol/L组, 统计不同系统LDL-C检测结果分在同一组的样本数及百分率, 评估系统间LDL-C差异对血脂管理临床决策的影响。通过2种方法计算校正因子:(1)用EP9-A3的方法估算系统间LDL-C的平均偏差;(2)采用多元线性逐步回归建立系统间LDL-C差值与相关指标的回归模型。用这2种校正因子修正系统间LDL-C的偏差, 用卡方检验比较修正前后LDL-C分组一致率的差异。结果 3种检测系统间TG、TC、LDL-C、F-LDL-C、HDL-C、非HDL-C的CV均值分别为4.84%、1.92%、11.96%、3.81%、5.82%、2.61%。相关性分析显示, 3种系统进行两两比对时, 除HW与罗氏的LDL-C、迈瑞与罗氏的LDL-C的R2分别为0.938、0.947外, 其余指标R2均>0.97。3种系统LDL-C、F-LDL-C按危险分层达标值分组的一致率分别为51.0%(100/196)、90.8%(178/196), 差异有统计学意义(P<0.05)。两两比较时, 罗氏与HW、迈瑞与HW、迈瑞与罗氏系统LDL-C分组一致率分别为60.7%(119/196)、82.7%(162/196)、54.1%(106/196)。用平均偏差校正后罗氏与HW的分组一致率提高至73.7%~79.4%(P<0.05), 罗氏与迈瑞的分组�Objective The results of the three lipid detection systems were compared to analyze their influence on risk stratification and clinical treatment in lipid management,especially the target goal cut-off point determination,and to find ways to reduce the impact on target goal determination of various lipid measurement system.Methods A total of 196 serum samples with triglyceride TG<4.5 mmol/L were collected from people undergoing physical examinations and in-patients in the Second Xiangya Hospital of Central South University from August to October 2022.Triglyceride(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C)and high-density lipoprotein cholesterol(HDL-C)were directly detected with Hitachi-Woke(HW),Roche and Mindray detection systems,respectively.The non high-density lipoprotein cholesterol(non HDL-C)was calculated by formula(TC-HDL-C)and LDL-C(F-LDL-C)was calculated by Friedewald formula,and results from various methodology were compared.The coefficient of variation(CV)of these six indicators derived from the three detection systems were calculated to evaluate the consistency of the obtained results from different venders.In addition,the Pearson correlation coefficient was analyzed to evaluate the correlation of each indicator among different systems.According to the Chinese Guidelines for Blood Lipid Management,samples were divided into groups with LDL-C levels of<1.4,1.4-<1.8,1.8-<2.6,2.6-<3.4 and≥3.4 mmol/L according to the recommended LDL-C levels for different risk stratification levels.The sample size and percentage of LDL-C test results from different systems in the same group were counted to evaluate the impact of LDL-C differences between systems on clinical decision-making of blood lipid management.The correction factor was calculated through two methods:(1)The average deviation of LDL-C between systems was estimated by EP9-A3 method;(2)Multiple linear stepwise regression was used to establish the regression model of LDL-C difference and related indexes between systems.The two co
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