Abstract

Measurement uncertainty (MU) of results is one of the basic recommended and accepted statistical methods in laboratory medicine, with which analytical and clinical evaluation of laboratory test quality is assessed. Literature data indicate that the calculation of MU is not a simple process, but that its assessment in daily laboratory practice should be reduced to routine and simple presentation, understandable to both laboratory professionals and physicians. In order to achieve this, it is necessary to understand the purpose of the test for which MU is to be determined. Various suggestions have been given for presentation of MU as a quantitative indicator of the quality of the final measurement result in the medical laboratory. Although MU refers to the final measurement result, this metrological concept reflects the entire laboratory measurement process. The data on estimated MU is used to interpret the measured numerical result, and represents quantitatively the quality of the measurement itself, i.e. how different are the results of multiple measurements of the analyte of interest in the same sample, as well as whether the method of determination itself is subjected to significant random and systematic deviation. Initially, in the metrological concept, the MU is viewed in relation to the true value of the analyte of interest. However, the true value of the analyte measured in the biological fluid matrix of the study population cannot be known. It is therefore considered the closest value obtained by the perfect method, for which the bias and inaccuracy, as measures of systematic and random error, are equal to zero, which is practically impossible to achieve in routine laboratory practice. Although current standards require accredited medical laboratories to estimate MU, none of these guidelines provide clear guidance on how this can be achieved in daily laboratory work. This review examines literary data and documents dealing with MU issues, but also highlights what additional terms and data should be considered when interpreting MU. This paper ultimately draws attention, and once again points out, that a simpler solution is needed for this universal concept to be formally and universally applicable in routine laboratory medicine practice.

摘要

结果的测量不确定度 (MU) 是检验医学中推荐和接受的基本统计方法之一，用于评估实验室测试质量的分析和临床评估。文献资料表明，MU 的计算不是一个简单的过程，但它在实验室日常实践中的评估应简化为常规和简单的表示，实验室专业人员和医生都可以理解。为了实现这一点，有必要了解要确定 MU 的测试目的。对于将 MU 作为医学实验室最终测量结果质量的定量指标，人们提出了各种建议。虽然 MU 指的是最终的测量结果，这一计量概念反映了整个实验室测量过程。估计 MU 的数据用于解释测量的数值结果，并定量地表示测量本身的质量，即同一样品中目标分析物的多次测量结果有何不同，以及测量方法是否决定本身受到显着的随机和系统偏差的影响。最初，在计量概念中，MU 被视为与目标分析物的真实值相关。然而，在研究人群的生物体液基质中测得的分析物的真实值是未知的。因此，它被认为是通过完美方法获得的最接近的值，作为系统和随机误差的度量，其偏差和不准确度为零，这在常规实验室实践中几乎不可能实现。尽管当前的标准要求经认可的医学实验室来估计 MU，但这些指南都没有提供关于如何在日常实验室工作中实现这一目标的明确指导。本综述审查了处理 MU 问题的文学数据和文件，但也强调了在解释 MU 时应考虑的附加术语和数据。这篇论文最终引起了人们的注意，并再次指出，需要一个更简单的解决方案，使这一普遍概念正式和普遍适用于常规检验医学实践。这些指导方针都没有提供关于如何在日常实验室工作中实现这一目标的明确指导。本综述审查了处理 MU 问题的文学数据和文件，但也强调了在解释 MU 时应考虑的附加术语和数据。这篇论文最终引起了人们的注意，并再次指出，需要一个更简单的解决方案，使这一普遍概念正式和普遍适用于常规检验医学实践。这些指南都没有提供关于如何在日常实验室工作中实现这一目标的明确指导。本综述审查了处理 MU 问题的文学数据和文件，但也强调了在解释 MU 时应考虑的附加术语和数据。这篇论文最终引起了人们的注意，并再次指出，需要一个更简单的解决方案，使这一普遍概念正式和普遍适用于常规检验医学实践。