Diagnostic Performance of Automated SARS-CoV-2 Antigen Assay in Nasal Swab during COVID-19 Vaccination Campaign
- PMID: 34829457
- PMCID: PMC8621910
- DOI: 10.3390/diagnostics11112110
Diagnostic Performance of Automated SARS-CoV-2 Antigen Assay in Nasal Swab during COVID-19 Vaccination Campaign
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.
Keywords: Ag-RDT; COVID-19; SARS-CoV2; diagnosis; rapid decisions.
Conflict of interest statement
The authors declare no conflict of interest.
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