Cheng Shitong, Man Dongliang, Zhou Zhiwei, Kang Hui
National Clinical Research Center for Laboratory Medicine, Department of Laboratory Medicine, The First Hospital of China Medical University, Shenyang, 110001, PR China.
Research Unit of Medical Laboratory, Chinese Academy of Medical Sciences, PR China.
Pract Lab Med. 2024 Dec 24;44:e00445. doi: 10.1016/j.plabm.2024.e00445. eCollection 2025 Apr.
China is promoting the mutual recognition of clinical laboratory test results to reduce redundant testing, provide more convenient medical services, and lower economic burdens. This study aimed to enhance the consistency of test results across laboratories using a linear transformation method, focusing on five representative biochemical parameters: ALP, CA, TBIL, TC, and TG.
Five ISO 15189 accredited laboratories participated in this study. We established inter-laboratory and intra-laboratory conversion relationships using patient sample comparisons and daily quality control (QC) data. These relationships were used to develop a web-based tool enabling real-time conversion and mutual recognition of laboratory test results.
The study found that the linear transformation method effectively improved the consistency of test results. After three stages of conversion, most test results showed deviations within ±1/2 TEa when compared to a reference laboratory. However, some parameters in the low-value range exhibited less significant conversion effects, likely due to the sensitivity of percentage deviation measurements in this range.
The developed approach and web-based tool show potential for enhancing result consistency and facilitating mutual recognition across laboratories. Despite its effectiveness, the study's limitations, such as a small sample size and a narrow focus on five biochemical parameters, indicate the need for further research and broader application.
中国正在推进临床检验结果互认，以减少重复检测，提供更便捷的医疗服务，并减轻经济负担。本研究旨在使用线性变换方法提高各实验室检测结果的一致性，重点关注五个具有代表性的生化参数：碱性磷酸酶（ALP）、钙（CA）、总胆红素（TBIL）、总胆固醇（TC）和甘油三酯（TG）。
五家通过ISO 15189认可的实验室参与了本研究。我们利用患者样本比较和日常质量控制（QC）数据建立了实验室间和实验室内的转换关系。这些关系被用于开发一个基于网络的工具，实现实验室检测结果的实时转换和互认。
研究发现线性变换方法有效提高了检测结果的一致性。经过三个阶段的转换，与参考实验室相比，大多数检测结果的偏差在±1/2 TEa范围内。然而，低浓度范围内的一些参数转换效果不太显著，这可能是由于该范围内百分比偏差测量的敏感性所致。
所开发的方法和基于网络的工具显示出提高结果一致性和促进实验室间互认的潜力。尽管有效，但本研究存在样本量小和仅关注五个生化参数等局限性，表明需要进一步研究和更广泛的应用。
