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八种血清乙醇酶分析法的分析性能评价——来自比利时室间质量评价计划的数据。

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

机构信息

Sciensano, Brussels, Belgium.

Quality of Laboratories, Sciensano, Brussels, Belgium.

出版信息

Clin Chem Lab Med. 2022 Jun 8;60(8):1211-1217. doi: 10.1515/cclm-2022-0285. Print 2022 Jul 26.

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.

摘要

目的

在疑似乙醇中毒的患者的临床环境中,快速可靠的乙醇分析检测常用于分析。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被用于该检测。本文重点评估这些检测方法的性能。

方法

数据包括 2019 年至 2021 年期间参加比利时室间质量评价计划的 30 份血清样本,浓度范围为 0.13 至 3.70 g/L。为评估离群值、偏差、变异性和测量不确定度,计算了目标浓度与报告值之间的回归线。

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,而 Vitros 的偏倚最低,对于低浓度,Cobas 8000 使用 c702 模块,对于高浓度,Cobas 8000 使用 c702 模块。在整个浓度范围内,Architect 和 Cobas c501/c502 系统的变异性最低。Cobas 8000 使用 702 模块、Thermo Scientific 和 Alinity c 的变异性最高。Cobas 8000 使用 c702 模块在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 是具有最高测量不确定度的方法。

结论

除了 Alinity c 之外,所有方法的酶技术偏差几乎可以忽略不计。不同的测量程序之间存在很大的差异。本研究表明,对于浓度高于 0.5 g/L 的方法,Alinity c 的测量不确定度比其他系统差。总的来说,我们发现测量不确定度的差异主要受变异性的差异影响。

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