当假阳性出现时:在半自动化平台上解决SARS-Coronavirus-2 (SARS-CoV-2) 检测试验的故障
Kenneth J Hampel1, Diana L Gerrard1, Denise Francis1
1Department of Pathology and Laboratory Medicine, University of Vermont Medical Center, Burlington, VT, United States.
The journal of applied laboratory medicine
|March 20, 2024
概括
分子诊断实验室通过在半自动化工作流程中识别和纠正假阳性来改进SARS-CoV-2测试,减少了50%的污染,并建立了一个新的性能标准.
科学领域:
- 分子诊断学 分子诊断
- 传染病检测试验 传染病检测
- 实验室自动化 实验室自动化
背景情况:
- 高通量SARS-CoV-2测试在COVID-19大流行期间变得普遍,利用自动化工作流程.
- 疫苗接种运动导致疫苗接种者的测试增加,这引发了对积极结果的质疑.
- 启动了一项质量改进倡议,以调查和解决半自动化测试中错误阳性结果.
研究的目的:
- 调查半自动SARS-CoV-2分子诊断工作流程中假阳性结果的原因.
- 实施程序改进,以减轻污染和提高准确性.
- 为分子诊断实验室建立可靠的测试协议.
主要方法:
- 在Agilent Bravo液体处理器上使用了MagMax-96病毒RNA套件和CDC 2019-nCoV RT-qPCR面板.
- 进行环境,人员和仪器选,使用棋盘挑战来检测交叉污染.
- 评估了测试设计和报告算法,根据已识别的污染指标进行调整.
主要成果:
- 在Bravo系统的病毒提取过程中发现了样本污染.
- 程序的修改减少了50%的板块污染,并揭示了受污染的样品的一致的标志.
- 调整后的报告算法发现了假阳性,占超过45,000次测试的0.11%.
结论:
- 实施的调整确保了自信,高质量的结果,同时保持了及时的患者报告.
- 修正后的假阳性率与自动化系统发布的数据保持一致,可能会设定实验室性能标准.
- 改进的工作流可以作为其他面临类似测试异常的实验室的资源.
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