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Diagnostic Performance of Automated SARS-CoV-2 Antigen Assay in Nasal Swab during COVID-19 Vaccination Campaign
- Source :
- Diagnostics, Vol 11, Iss 11, p 2110 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Background: To control the spread of the pandemic brought about by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, it is necessary to have an automated reliable diagnostic assay. To date, the RT-PCR (RT-qPCR) has been the recommended laboratory method to diagnose SARS-CoV-2 infection, but there is a need for more automated and reliable tests. The aim of this real-life study was to assess the diagnostic performance of DiaSorin’s LIAISON SARS-CoV-2 antigen (Ag) chemiluminescence immunoassay in detecting SARS-CoV-2 in vaccinated and unvaccinated individuals. Methods: A prospective study was performed on 300 nasopharyngeal swabs randomly collected from 31 May to 6 July 2021. Nasopharyngeal samples were assayed with DiaSorin’s LIAISON SARS-CoV-2 Ag and TaqPath™ COVID-19 multiplex RT-qPCR. Results: Of 300 participants, 150 had a RT-qPCR confirmed SARS-CoV-2 infection of whom 113 (75.33%) were also detected by the DiaSorin LIAISON SARS-CoV-2 Ag. Taking RT-qPCR as a reference, the sensitivity and specificity of the DiaSorin LIAISON SARS-CoV-2 Ag assay were evaluated as 75.33% (95% CI = 67.64–82) and 100% (95% CI = 97.57–100), respectively. When a viral load cut-off was applied for high viral load (median cycle threshold (Ct) < 18.57), the overall sensitivity was increased to 96.55% (95% CI = 88.09–99.58). Interestingly, median RT-qPCR Ct and SARS-CoV-2 Ag values were similar between fully vaccinated and unvaccinated subjects. Conclusions: Automated, quantitative LIAISON SARS-CoV-2 Ag assay shows good performance to identify SARS-CoV-2-infected individuals with moderate to high viral loads. LIAISON SARS-CoV-2 Ag testing could be used as frontline testing for COVID-19 diagnosis and be more suitable for large utilization.
- Subjects :
- COVID-19
SARS-CoV2
Ag-RDT
diagnosis
rapid decisions
Medicine (General)
R5-920
Subjects
Details
- Language :
- English
- ISSN :
- 20754418
- Volume :
- 11
- Issue :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Diagnostics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4378034715a40c1af73767302fd743e
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/diagnostics11112110