一种利用检定数据计算临床常规实验室初步测量不确定度的方法

IF 2.9 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2025-09-11 DOI:10.1016/j.cca.2025.120605

Simon Michaelis , Laura Binder , Christopher Schneider , Wolfgang J. Schnedl , Andreas Baranyi , Dietmar Enko

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引用次数: 0

摘要

测量不确定度是临床常规实验室测量质量的重要指标。其估算是ISO 15189认证的强制性要求。然而，对于如何建立联合管理委员会，目前还没有达成共识。这项研究的目的是评估一种基于现有的核查数据和外部质量评估（EQA）方案的结果计算初步指标的程序。方法采用Nordtest方法对2个不同数据集的29个测量值进行扩展测量不确定度(U)计算。第一个U用一年的内部质量控制（IQC）数据（60个测量/水平，2个水平）和6个EQA样本（muiqc -方案）进行测定，第二个U根据CLSI EP15-A3指南（25个测量/水平，5 × 5方案，2个水平）和4个EQA样本（muverification -方案）进行验证。计算MUIQC和MUVerification （ΔU）之间的差异。将MUIQC和MUVerification与公布的验收标准（Rili-BAEK和Westgard）进行比较。结果MUIQC的U值（2.2% ~ 20.9%）高于MUVerification的U值（2.2% ~ 13.0%）。ΔU的取值范围为- 1.8% - 13.8%。5个测量值ΔU为>； 5%，而7个测量值显示更高的U为MUVerification （ΔU-range−1.8% -−0.8%）。对于所有的测量，MUIQC和MUVerification的U都在rii - baek和Westgard的验收标准之内。结论验证数据可作为临床常规实验室初步MU值估计的一种合适方法。

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An approach for the calculation of preliminary measurement uncertainty values in clincial routine laboratories using verification data

Background

The measurement uncertainty is an essential measure of quality in clinical routine laboratories. Its estimation is mandatory for the ISO 15189 accreditation. However, there is no in consensus on how to establish the MU. The study aimed to evaluate a procedure for calculating a preliminary MU based on already existing verification data and results from external quality assessment (EQA) schemes.

Methods

Expanded measurement uncertainty (U) was calculated for 29 measurands using two different data sets applying the Nordtest protocol. One U was determined with internal quality control (IQC) data from one year (60 measurements/level; two levels) and six EQA-samples (MU_IQC-scheme), the second U was performed with verification data according to the CLSI EP15-A3 guideline (25 measurements/level, 5x5-scheme; two levels) and four EQA samples (MU_Verification-scheme). The difference between MU_IQC and MU_Verification (ΔU) was calculated. MU_IQC and MU_Verification were compared to published acceptance criteria (Rili-BAEK and Westgard).

Results

For most measurands, U was higher for MU_IQC (range 2.2 %–20.9 %) compared with MU_Verification (range 2.2 %–13.0 %). The ΔU ranged between −1.8 %–13.8 %. Five measurands showed a ΔU of > 5 %, while seven measurands showed a higher U for MU_Verification (ΔU-range −1.8 %–−0.8 %). For all measurands, the U for MU_IQC and MU_Verification were within the Rili-BAEK and Westgard acceptance criteria.

Conclusion

The use of verification data may serve as a suitable approach for the estimation of preliminary MU values in clinical routine laboratories.

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来源期刊

Clinica Chimica Acta 医学-医学实验技术

CiteScore

10.10

自引率

2.00%

发文量

1268

审稿时长

23 days

期刊介绍： The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.