Since the beginning of the COVID-19 pandemic, important health and regulatory decisions relied on SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) results. Our diagnostic laboratory faced a rapid increase in the number of SARS-CoV-2 RT-PCR. To maintain a rapid turnaround time, we moved from a case-by-case validation of RT-PCR results to an automated validation and immediate results transmission to clinicians. A quality-monitoring tool based on a homemade algorithm coded in R was developed, to preserve high quality and to track aberrant results. We present the results of this quality-monitoring tool applied to 35,137 RT-PCR results. Patients tested several times led to 4,939 pairwise comparisons: 88% concordant and 12% discrepant. The algorithm automatically solved 428 out of 573 discrepancies. The most likely explanation for these 573 discrepancies was related for 44.9% of the situations to the clinical evolution of the disease, 27.9% to preanalytical factors, and 25.3% to stochasticity of the assay. Finally, 11 discrepant results could not be explained, including 8 for which clinical data was not available. For patients repeatedly tested on the same day, the second result confirmed a first negative or positive result in 99.2% or 88.9% of cases, respectively. The implemented quality-monitoring strategy allowed to: i) assist the investigation of discrepant results ii) focus the attention of medical microbiologists onto results requiring a specific expertise and iii) maintain an acceptable turnaround time. This work highlights the high RT-PCR consistency for the detection of SARS-CoV-2 and the necessity for automated processes to handle a huge number of microbiological results while preserving quality.

自 COVID-19 大流行开始以来，重要的健康和监管决策依赖于 SARS-CoV-2 逆转录聚合酶链反应 (RT-PCR) 结果。我们的诊断实验室面临着 SARS-CoV-2 RT-PCR 数量的迅速增加。为了保持快速的周转时间，我们从逐案验证 RT-PCR 结果转变为自动验证并立即将结果传输给临床医生。开发了一种基于用 R 编码的自制算法的质量监控工具，以保持高质量并跟踪异常结果。我们展示了应用于 35,137 个 RT-PCR 结果的这种质量监控工具的结果。多次测试的患者进行了 4,939 次成对比较：88% 一致，12% 不一致。该算法自动解决了 573 个差异中的 428 个。对这 573 个差异的最可能解释与 44.9% 的情况与疾病的临床演变有关，27.9% 与分析前因素有关，25.3% 与检测的随机性有关。最后，11 个不一致的结果无法解释，其中 8 个没有临床数据。对于在同一天重复检测的患者，第二个结果分别在 99.2% 或 88.9% 的病例中证实了第一个阴性或阳性结果。实施的质量监控策略允许：i) 协助调查不一致的结果 ii) 将医学微生物学家的注意力集中在需要特定专业知识的结果上，以及 iii) 保持可接受的周转时间。