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一种运用模式识别对临床实验室常规分析方法进行客观评估的技术。

A technique for the objective assessment of routine analytical methods in clinical laboratories using pattern recognition.

作者信息

Jansen R T, Pijpers F W, de Valk G A

出版信息

Ann Clin Biochem. 1981 Jul;18(Pt 4):218-25. doi: 10.1177/000456328101800406.

DOI:10.1177/000456328101800406
PMID:7283374
Abstract

A technique is presented to assess objectively the reliability of analytical methods used routinely in clinical laboratories. From the Netherlands National Coupled External/Internal Quality Control Programme information can be gathered about the performance of routine analytical methods. The performance of a method in a trial is described by four 'features': the accuracy of a method; its day to-day precision; its susceptibility to give erroneous results (eg, extreme bias, drift, extreme week-to-week variations); and its susceptibility to give systematic errors for different laboratories. These four features obtained in a trial for a given analytical method determine the position of a 'pattern' in the four-dimensional space. The results of six trials discussed in this paper provided six 'patterns' per analytical method. Using pattern recognition techniques, clusters of patterns were detected in the four-dimensional space. A weighting procedure revealed the relative importance of the various features for discrimination between the detected clusters. For various blood components, different features are of importance for this discrimination. Patterns belonging to the same clusters appeared to be patterns of the same (or comparable) analytical methods; thus analytical methods could be distinguished from each other. The means of the feature values of the patterns in a cluster determine the quality of that cluster. Thus the quality of an analytical method can be objectively assessed. Some tentative conclusions on the validity of analytical methods are given.

摘要

本文介绍了一种客观评估临床实验室常规使用的分析方法可靠性的技术。通过荷兰国家外部/内部联合质量控制计划,可以收集有关常规分析方法性能的信息。一种方法在一次试验中的性能由四个“特征”来描述:方法的准确性;其日常精密度;给出错误结果的易感性(例如,极端偏差、漂移、每周极端变化);以及其在不同实验室产生系统误差的易感性。在一次试验中针对给定分析方法获得的这四个特征决定了一个“模式”在四维空间中的位置。本文讨论的六项试验结果为每种分析方法提供了六个“模式”。使用模式识别技术,在四维空间中检测到了模式簇。加权程序揭示了各种特征对于区分检测到的簇的相对重要性。对于各种血液成分,不同的特征对于这种区分很重要。属于同一簇的模式似乎是相同(或可比)分析方法的模式;因此可以相互区分分析方法。一个簇中模式的特征值均值决定了该簇的质量。因此,可以客观地评估分析方法的质量。文中给出了关于分析方法有效性的一些初步结论。

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