Boyd Jessica M, Krause Richard, Waite Gayle, Hui William, Yazdi Elham, Wilmink David, Seiden-Long Isolde
Department of Pathology and Laboratory Medicine, University of Calgary and Calgary Laboratory Services, Canada.
Gamma-Dynacare Medical Laboratories, Canada.
Clin Chim Acta. 2015 Oct 23;450:31-8. doi: 10.1016/j.cca.2015.07.006. Epub 2015 Jul 8.
There is limited information about the effects of instituting CLSI Document C56A recommended workflows for the automated detection of hemolysis, lipemia and icterus (HIL) in different clinical laboratories and patient populations. We describe a process to develop and tailor automated reporting rules that are appropriate for the local laboratory population.
Automated decision algorithms were generated and applied to 2 high volume labs serving community and hospital populations. Proposed rules were applied to the datasets offline to predict the outcomes, and then were further optimized prior to implementation.
Introduction of automated serum indices decreased HIL flagging compared to manual flagging. Hemolysis flagging was the greatest in all 3 patient populations, and was successfully reduced for LD, CK and AST by optimized rules that incorporated both the H-index result and the analyte result. Changes in flagging rates were also patient population specific, particularly for icterus which was a problem in hospitalized populations but not in the community. Overall, concordance between manual and automated flagging methods was very low in both laboratories.
We demonstrate that flagging algorithms may not be universally transferable due to lab specific and population specific factors and demonstrate the benefits of local, a priori testing of algorithms prior to implementation.
关于在不同临床实验室和患者群体中采用临床和实验室标准协会（CLSI）文件C56A推荐的工作流程进行溶血、脂血和黄疸（HIL）自动检测的效果，相关信息有限。我们描述了一个制定和调整适用于当地实验室人群的自动报告规则的过程。
生成自动决策算法并应用于为社区和医院人群服务的2个大容量实验室。将提议的规则离线应用于数据集以预测结果，然后在实施前进一步优化。
与手动标记相比，引入自动血清指标减少了HIL标记。溶血标记在所有3个患者群体中最为常见，通过纳入H指数结果和分析物结果的优化规则，成功降低了乳酸脱氢酶（LD）、肌酸激酶（CK）和天门冬氨酸氨基转移酶（AST）的溶血标记。标记率的变化也因患者群体而异，尤其是黄疸，这在住院患者群体中是个问题，但在社区患者中不是。总体而言，两个实验室中手动和自动标记方法之间的一致性都非常低。
我们证明，由于实验室特定因素和人群特定因素，标记算法可能无法普遍转移，并证明了在实施前对算法进行本地先验测试的好处。
