Document Type

Journal Article

Publication Title

Diagnostic Microbiology and Infectious Disease

Volume

109

Issue

2

PubMed ID

38574444

Publisher

Elsevier

School

Centre for Precision Health

RAS ID

69840

Funders

Special Major Application Research Project for COVID-19 Prevention and Control in Universities / Department of Education of Guangdong / Provincial Program of Innovation and Strengthening School, Guangdong, China / Special Project for COVID-19 Prevention and Treatment of Shantou Science and Technology Bureau, Guangdong, China

Comments

Liu, M., Tian, C., Chen, Y., Zhu, J., Zheng, Y., Chen, J., . . . Cai, Y. (2024). Effectiveness of a standardized quality control management procedure for COVID-19 RT-PCR testing: A large-scale diagnostic accuracy study in China. Diagnostic Microbiology and Infectious Disease, 109(2), article 116287. https://doi.org/10.1016/j.diagmicrobio.2024.116287

Abstract

Background: The study aimed to construct a standardized quality control management procedure (QCMP) and access its accuracy in the quality control of COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR). Methods: Considering the initial RT-PCR results without applying QCMP as the gold standard, a large-scale diagnostic accuracy study including 4,385,925 participants at three COVID-19 RT-PCR testing sites in China, Foshan (as a pilot test), Guangzhou and Shenyang (as validation sites), was conducted from May 21, 2021, to December 15, 2022. Results: In the pilot test, the RT-PCR with QCMP had a high accuracy of 99.18% with 100% specificity, 100% positive predictive value (PPV), and 99.17% negative predictive value (NPV). The rate of retesting was reduced from 1.98% to 1.16%. Its accuracy was then consistently validated in Guangzhou and Shenyang. Conclusions: The RT-PCR with QCMP showed excellent accuracy in identifying true negative COVID-19 and relieved the labor and time spent on retesting.

DOI

10.1016/j.diagmicrobio.2024.116287

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Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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