Regression-Adjusted Real-Time Quality Control
Regression-Adjusted Real-Time Quality Control
复制标题
回归调整实时质量控制
DOI：
10.1093/clinchem/hvab115
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发表时间：
2021-08-06
影响因子：
9.3
通讯作者：
Guo, Wei
中科院分区：
文献类型：
--
作者：
Duan, Xincen;Wang, Beili;Guo, Wei
背景：近年来，基于患者的实时质量控制在临床实验室管理领域受到越来越多的关注。尽管PBRTQC给实验室管理系统带来了许多好处，但它的性能和对一些分析的实际适用性受到了质疑。为了提高实时质量控制协议的性能，引入了一种扩展的方法--回归调整实时质量控制(RARTQC)。方法：与PBRTQC不同，RARTQC在使用移动平均等常见统计过程控制算法之前增加了回归调整步骤来判断是否存在分析误差。我们使用复旦大学中山医院2019年4种分析物的所有患者测试结果来比较两种框架的性能。在研究中增加了三种类型的分析误差来比较PBRTQC和RARTQC协议的性能：恒定误差、随机误差和比例误差。使用误警率和错误检测图表对协议进行评估。结果：研究表明RARTQC优于PBRTQC。与PBRTQC相比，RARTQC在常量误差和比例误差的总允许误差下，将检测前受影响的患者平均数量(TANPed)提高了约50%。结论：RARTQC框架中的回归步骤消除了测试结果中的自相关性，允许研究人员添加额外的变量，并改进了数据转换。RARTQC是实时质量控制研究的强大框架。
BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained increasing attention in the field of clinical laboratory management in recent years. Despite the many upsides that PBRTQC brings to the laboratory management system, it has been questioned for its performance and practical applicability for some analytes. This study introduces an extended method, regression-adjusted real-time quality control (RARTQC), to improve the performance of real-time quality control protocols.METHODS: In contrast to the PBRTQC, RARTQC has an additional regression adjustment step before using a common statistical process control algorithm, such as the moving average, to decide whether an analytical error exists. We used all patient test results of 4 analytes in 2019 from Zhongshan Hospital, Fudan University, to compare the performance of the 2 frameworks. Three types of analytical error were added in the study to compare the performance of PBRTQC and RARTQC protocols: constant, random, and proportional errors. The false alarm rate and error detection charts were used to assess the protocols.RESULTS: The study showed that RARTQC outperformed PBRTQC. RARTQC, compared with the PBRTQC, improved the trimmed average number of patients affected before detection (tANPed) at total allowable error by about 50% for both constant and proportional errors.CONCLUSIONS: The regression step in the RARTQC framework removes autocorrelation in the test results, allows researchers to add additional variables, and improves data transformation. RARTQC is a powerful framework for real-time quality control research.