Assessing the performance of a serological point-of-care test in measuring detectable antibodies against SARS-CoV-2
التاريخ
2022-01المؤلف
El Kahlout, Reham AwniCoyle, Peter V.
Dargham, Soha R.
Chemaitelly, Hiam
Kacem, Mohamed Ali Ben Hadj
Al-Mawlawi, Naema Hassan Abdulla
Gilliani, Imtiaz
Younes, Nourah
AlKanaani, Zaina
AlKhal, Abdullatif
ALKuwari, Einas
Jeremijenko, Andrew
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البيانات الوصفية
عرض كامل للتسجيلةالملخص
This study investigated the performance of a rapid point-of-care antibody test, the BioMedomics COVID-19 IgM/IgG Rapid Test, in comparison with a high-quality, validated, laboratory-based platform, the Roche Elecsys Anti-SARS-CoV-2 assay. Serological testing was conducted on 709 individuals. Concordance metrics were estimated. Logistic regression was used to assess associations with seropositivity. SARS-CoV-2 seroprevalence was 63.5% (450/709; 95% CI 59.8%-67.0%) using the BioMedomics assay and 71.9% (510/709; 95% CI 68.5%-75.2%) using the Elecsys assay. There were 60 discordant results between the two assays, all of which were seropositive in the Elecsys assay, but seronegative in the BioMedomics assay. Overall, positive, and negative percent agreements between the two assays were 91.5% (95% CI 89.2%-93.5%), 88.2% (95% CI 85.1%-90.9%), and 100% (95% CI 98.2%-100%), respectively, with a Cohen’s kappa of 0.81 (95% CI 0.78–0.84). Excluding specimens with lower (Elecsys) antibody titers, the agreement improved with overall, positive, and negative percent concordance of 94.4% (95% CI 92.3%-96.1%), 91.8% (95% CI 88.8%-94.3%), and 100% (95% CI 98.2%-100%), respectively, and a Cohen’s kappa of 0.88 (95% CI 0.85–0.90). Logistic regression confirmed better agreement with higher antibody titers. The BioMedomics COVID-19 IgM/IgG Rapid Test demonstrated good performance in measuring detectable antibodies against SARS-CoV-2, supporting the utility of such rapid point-of-care serological testing to guide the public health responses and vaccine prioritization. © 2022 Coyle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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