Measurement uncertainties in clinical chemistry are commonly regarded as heteroscedastic - having a constant relative standard deviation irrespective of the concentration of the measurand. The uncertainty is usually determined at two concentrations using stabilized control materials and assumed to represent the analytical goal. The purpose of the present study was to use duplicates of unselected patient samples to calculate the absolute and relative repeatability component of the intra-laboratory measurement uncertainty from duplicates, using the Dahlberg formula and analysis of variance components. Estimates were made at five different concentration intervals of ALT, AST, Calcium, Cholesterol, Creatinine, CRP, Triglycerides and TSH covering the entire concentration interval of the patient cohort. This partioning allows detailing their repeatability profiles. The calculations of the profiles were based on randomly selected results from sets of duplicates ranging from 12,000 to 65,000 pairs. The repeatability of the measurands showed substantial variability within the measuring interval. Therefore, characterizing imprecision profiles as purely homo- or heteroscedastic or by a single number may not be optimal for the intended use. The present data make a case for nuancing the evaluation of analytical goals and minimal differences of measurement results by establishing uncertainty profiles under repeatability conditions, using natural patient samples.

中文翻译：

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通过重复测量患者样品确定的八种临床化学中经常被测量的测量重复性曲线。

临床化学中的测量不确定度通常被认为是异方差的-相对于被测物的浓度具有恒定的相对标准偏差。通常使用稳定的控制材料在两个浓度下确定不确定度，并假设其代表分析目标。本研究的目的是使用Dahlberg公式和方差分析，使用未经选择的患者样本的重复样本，从重复样本中计算实验室内测量不确定度的绝对和相对重复性成分。在覆盖患者队列整个浓度区间的ALT，AST，钙，胆固醇，肌酐，CRP，甘油三酸酯和TSH的五个不同浓度区间进行估算。这种划分允许详细说明其可重复性配置文件。配置文件的计算基于从12,000至65,000对重复项中随机选择的结果。被测物的重复性在测量间隔内显示出很大的可变性。因此，将不精确轮廓描述为纯均一或异方差或仅用一个数来表征可能不是最佳的预期用途。本数据为通过使用自然患者样本在可重复性条件下建立不确定度分布图，提高分析目标的评估和最小化测量结果差异提供了理由。被测物的重复性在测量间隔内显示出很大的可变性。因此，将不精确轮廓描述为纯均一或异方差或仅用一个数来表征可能不是最佳的预期用途。本数据为通过使用自然患者样本在可重复性条件下建立不确定度分布图，提高分析目标的评估和最小化测量结果差异提供了理由。被测物的重复性在测量间隔内显示出很大的可变性。因此，将不精确轮廓描述为纯均一或异方差或仅用一个数来表征可能不是最佳的预期用途。本数据为通过使用自然患者样本在可重复性条件下建立不确定度分布图，提高分析目标的评估和最小化测量结果差异提供了理由。