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. 2020 Nov;57(6):429-434.
doi: 10.1177/0004563220963847.

Performance verification of anti-SARS-CoV-2-specific antibody detection by using four chemiluminescence immunoassay systems

Affiliations

Performance verification of anti-SARS-CoV-2-specific antibody detection by using four chemiluminescence immunoassay systems

Yafang Wan et al. Ann Clin Biochem. 2020 Nov.

Abstract

Objectives: The purpose of the current study was to evaluate the analytical performance of seven kits for detecting IgM/IgG antibodies against coronavirus (SARS-CoV-2) by using four chemiluminescence immunoassay systems.

Methods: Fifty patients diagnosed with SARS-CoV-2 infection and 130 controls without coronavirus infection from the General Hospital of Chongqing were enrolled in the current retrospective study. Four chemiluminescence immunoassay systems, including seven IgM/IgG antibody detection kits for SARS-CoV-2 (A_IgM, A_IgG, B_IgM, B_IgG, C_IgM, C_IgG and D_Ab), were employed to detect antibody concentrations. The chi-square test, the receiver operating characteristic (ROC) curve and Youden's index were determined to verify the cut-off value of each detection system.

Results: The repeatability verification results of the A, B, C and D systems are all qualified. D_Ab performed best (92% sensitivity and 99.23% specificity), and B_IgM performed worse than the other systems. Except for the A_IgM and C_IgG systems, the optimal diagnostic thresholds and cut-off values of the other kits and their recommendations are inconsistent with each other. B_IgM had the worst AUC, and C_IgG had the best diagnostic accuracy. More importantly, the B_IgG system had the highest false-positive rate for testing patients with AIDS, tumours and pregnancies. The A_IgM system test showed the highest false-positive rates among elderly individuals over 90 years old. COVID-2019 IgM/IgG antibody test systems exhibit performance differences.

Conclusions: The Innodx Biotech Total Antibody serum diagnosis kit is the most reliable detection system for anti-SARS-CoV-2 antibodies, which can be used together with nucleic acid tests as an alternative method for SARS-CoV-2 detecting.

Keywords: COVID-19; SARS-CoV-2; antibody; chemiluminescence immunoassay; performance verification.

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Conflict of interest statement

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
ROC curve for different kits.

References

    1. Lu R, Zhao X, Li J, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet (London, England) 2020; 395: 565–574. - PMC - PubMed
    1. Ren SY, Wang WB, Hao YG, et al. Stability and infectivity of coronaviruses in inanimate environments. World J Clin Cases 2020; 8: 1391–1399. - PMC - PubMed
    1. Chan JF, Yuan S, Kok KH, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet (London, England) 2020; 395: 514–523. - PMC - PubMed
    1. Lin L, Lu L, Cao W, et al. Hypothesis for potential pathogenesis of Sars-Cov-2 infection-a review of immune changes in patients with viral pneumonia. Emerg Microbes Infect 2020; 9: 727–732. - PMC - PubMed
    1. P.R.China NHCoNovel corona virus pneumonia diagnosis and treatment guideline (trial version 7). [EB/OL], www.nhc.gov.cn/xcs/zhengcwj/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml (2020, accessed 24 September 2020).

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