Development and Potential Usefulness of the COVID-19 Ag Respi-Strip Diagnostic Assay in a Pandemic Context

COVID-19 Ag Respi-Strip 诊断检测试剂盒在疫情背景下的开发及其潜在用途

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作者:Pascal Mertens, Nathalie De Vos, Delphine Martiny, Christian Jassoy, Ali Mirazimi, Lize Cuypers, Sigi Van den Wijngaert, Vanessa Monteil, Pierrette Melin, Karolien Stoffels, Nicolas Yin, Davide Mileto, Sabrina Delaunoy, Henri Magein, Katrien Lagrou, Justine Bouzet, Gabriela Serrano, Magali Wautier, 

Conclusion

The COVID-19 Ag Respi-Strip represents a promising rapid SARS-CoV-2 antigen assay for the first-line diagnosis of COVID-19 in 15 min at the peak of the pandemic. Its role in the proposed diagnostic algorithm is complementary to the currently-used molecular techniques.

Methods

Development of the COVID-19 Ag Respi-Strip resulted in a ready-to-use ICT assay based on a membrane technology with colloidal gold nanoparticles using monoclonal antibodies directed against the SARS-CoV and SARS-CoV-2 highly conserved nucleoprotein antigen. Four hundred observations were recorded for the analytical performance study and thirty tests were analyzed for the cross-reactivity study. The clinical performance study was performed in a retrospective multi-centric evaluation on aliquots of 328 nasopharyngeal samples. COVID-19 Ag Respi-Strip

Results

In the analytical performance study, the reproducibility showed a between-observer disagreement of 1.7%, a robustness of 98%, an overall satisfying user friendliness and no cross-reactivity with other virus-infected nasopharyngeal samples. In the clinical performance study performed in three different clinical laboratories during the ascendant phase of the epidemiological curve, we found an overall sensitivity and specificity of 57.6 and 99.5%, respectively with an accuracy of 82.6%. The cut-off of the ICT was found at CT <22. User-friendliness analysis and risk management assessment through Ishikawa diagram demonstrate that COVID-19 Ag Respi-Strip may be implemented in clinical laboratories according to biosafety recommendations.

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