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    Diagnostic Efficiency of Three Fully Automated Serology Assays and Their Correlation with a Novel Surrogate Virus Neutralization Test in Symptomatic and Asymptomatic SARS-COV-2 Individuals

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    microorganisms-09-00245 (1).pdf (702.5Kb)
    Date
    2020-01-25
    Author
    Younes, Salma
    Al-Jighefee, Hadeel
    Shurrab, Farah
    Al-Sadeq, Duaa W.
    Younes, Nadin
    Dargham, Soha R.
    Al-Dewik, Nader
    Qotba, Hamda
    Syed, Mohamed
    Alnuaimi, Ahmed
    Yassine, Hadi M.
    Tang, Patrick
    Abu-Raddad, Laith J.
    Nasrallah, Gheyath K.
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    Abstract
    Abstract: To support the deployment of serology assays for population screening during the COVID-19 pandemic, we compared the performance of three fully automated SARS-CoV-2 IgG assays: Mindray CL-900i® (target: spike [S] and nucleocapsid [N]), BioMérieux VIDAS®3 (target: receptor-binding domain [RBD]) and Diasorin LIAISON®XL (target: S1 and S2 subunits). A total of 111 SARS-CoV-2 RT-PCR- positive samples collected at ≥ 21 days post symptom onset, and 127 prepandemic control samples were included. Diagnostic performance was assessed in correlation to RT-PCR and a surrogate virus-neutralizing test (sVNT). Moreover, cross-reactivity with other viral antibodies was investigated. Compared to RT-PCR, LIAISON®XL showed the highest overall specificity (100%), followed by VIDAS®3 (98.4%) and CL-900i® (95.3%). The highest sensitivity was demonstrated by CL-900i® (90.1%), followed by VIDAS®3 (88.3%) and LIAISON®XL (85.6%). The sensitivity of all assays was higher in symptomatic patients (91.1–98.2%) compared to asymptomatic patients (78.4–80.4%). In correlation to sVNT, all assays showed excellent sensitivities (92.2–96.1%). In addition, VIDAS®3 demonstrated the best correlation (r = 0.75) with the sVNT. The present study provides insights on the performance of three fully automated assays, which could help diagnostic laboratories in the choice of a particular assay according to the intended use
    DOI/handle
    http://dx.doi.org/10.3390/microorganisms9020245
    http://hdl.handle.net/10576/17467
    http://dx.doi.org/10.3390/microorganisms9020245
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    • Biomedical Research Center Research [‎786‎ items ]
    • Biomedical Sciences [‎802‎ items ]
    • COVID-19 Research [‎848‎ items ]
    • Medicine Research [‎1755‎ items ]

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