Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Shanghai Senxu Medical Technology Corporation, Shanghai, China.
J Clin Lab Anal. 2022 Sep;36(9):e24651. doi: 10.1002/jcla.24651. Epub 2022 Aug 10.
It is critical for laboratories to conduct multianalyzer comparisons as a part of daily routine work to strengthen the quality management of test systems. Here, we explored the application of patient-based real-time quality controls (PBRTQCs) on comparative assays to monitor the consistency among clinical laboratories.
The present study included 11 commonly tested analytes that were detected using three analyzers. PBRTQC procedures were set up with exponentially weighted moving average (EWMA) algorithms and evaluated using the AI-MA artificial intelligence platform. Comparative assays were carried out on serum samples, and patient data were collected. Patients were divided into total patient (TP), inpatient (IP), and outpatient (OP) groups.
Optimal PBRTQC protocols were evaluated and selected with appropriate truncation limits and smoothing factors. Generally, similar comparative assay performance was achieved using both the EWMA and median methods. Good consistency between the results from patients' data and serum samples was obtained, and unacceptable bias was detected for alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) when using analyzer C. Categorizing patients' data and applying specific groups for comparative assays could significantly improve the performance of PBRTQCs. When monitoring the inter- and intraanalyzer stability on a daily basis, EWMA was superior in detecting very small quality-related changes with lower false-positive alarms.
We found that PBRTQCs have the potential to efficiently assess multianalyzer comparability. Laboratories should be aware of population variations concerning both analytes and analyzers to build more suitable PBRTQC protocols.
实验室作为日常工作的一部分进行多分析仪比较对于加强测试系统的质量管理至关重要。在这里，我们探索了基于患者的实时质量控制（PBRTQC）在比较分析中的应用，以监测临床实验室之间的一致性。
本研究包括使用三种分析仪检测的 11 种常见测试分析物。使用指数加权移动平均（EWMA）算法设置 PBRTQC 程序，并使用 AI-MA 人工智能平台进行评估。对血清样本进行比较分析，并收集患者数据。患者分为总患者（TP）、住院患者（IP）和门诊患者（OP）组。
评估并选择了具有适当截断限制和平滑因子的最佳 PBRTQC 方案。通常，使用 EWMA 和中位数方法均可获得类似的比较分析性能。从患者数据和血清样本中获得的结果之间具有良好的一致性，并且当使用分析仪 C 时，检测到碱性磷酸酶（ALP）和γ-谷氨酰转移酶（GGT）的不可接受的偏差。对患者数据进行分类并为比较分析应用特定组可以显著改善 PBRTQC 的性能。当每天监测仪器间和仪器内稳定性时，EWMA 能够更有效地检测到与质量相关的较小变化，并且假阳性警报较低。
我们发现 PBRTQC 有潜力有效地评估多分析仪的可比性。实验室应注意分析物和分析仪的人群变化，以建立更合适的 PBRTQC 方案。
