Analytical performance of eight enzymatic assays for ethanol in serum evaluated by data from the Belgian external quality assessment scheme

W. Coucke, C. Charlier, K. Croes, B. Mahieu, Hugo Neels, C. Stove, J. Tytgat, André Vanescote, A. Verstraete, Sarah Wille, Arnaud Capron
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引用次数: 1

Abstract

Abstract Objectives Fast and reliable ethanol assays analysis are used in a clinical context for patients suspected of ethanol intoxication. Mostly, automated systems using an enzymatic reaction based on ethanol dehydrogenase are used. The manuscript focusses on the evaluation of the performance of these assays. Methods Data included 30 serum samples used in the Belgian EQA scheme from 2019 to 2021 and concentrations ranged from 0.13 to 3.70 g/L. A regression line between target concentrations and reported values was calculated to evaluate outliers, bias, variability and measurement uncertainty. Results A total of 1,611 results were taken into account. Bias was the highest for Alinity c over the whole concentration range and the lowest for Vitros for low concentrations and Cobas 8000 using the c702 module for high concentrations. The Architect and Cobas c501/c502 systems showed the lowest variability over the whole concentration range. Highest variability was observed for Cobas 8000 using the 702 module, Thermo Scientific and Alinity c. Cobas 8000 using the c702 module showed the highest measurement uncertainty for lower concentrations. For higher concentrations, Alinity c, Thermo Scientific and Vitros were the methods with the highest measurement uncertainty. Conclusions The bias of the enzymatic techniques is nearly negligible for all methods except Alinity c. Variability differs strongly between measurement procedures. This study shows that the Alinity c has a worse measurement uncertainty than other systems for concentrations above 0.5 g/L. Overall, we found the differences in measurement uncertainty to be mainly influenced by the differences in variability.
用比利时外部质量评价方案的数据评价血清中乙醇8种酶法的分析性能
摘要目的快速、可靠的乙醇分析方法用于临床疑似乙醇中毒的患者。大多数情况下,使用基于乙醇脱氢酶的酶促反应的自动化系统。该手稿的重点是这些分析的性能的评价。数据包括2019年至2021年比利时EQA计划中使用的30份血清样本,浓度范围为0.13至3.70 g/L。计算目标浓度与报告值之间的回归线,以评估异常值、偏差、变异性和测量不确定性。结果共考虑了1611个结果。在整个浓度范围内,Alinity c的偏倚最高,Vitros的偏倚最低,而使用c702模块的Cobas 8000的偏倚最低。Architect和Cobas c501/c502系统在整个浓度范围内表现出最低的可变性。使用702模块,Thermo Scientific和Alinity c观察到Cobas 8000的最高变异性。使用c702模块的Cobas 8000在较低浓度下显示出最高的测量不确定度。对于较高浓度,Alinity c、Thermo Scientific和Vitros是测量不确定度最高的方法。除Alinity c外,所有方法的酶技术偏差几乎可以忽略不计。测量程序之间的变异性差异很大。本研究表明,当浓度大于0.5 g/L时,Alinity c的测量不确定度比其他系统差。总体而言,我们发现测量不确定度的差异主要受变异性差异的影响。
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