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Type: 
Journal
Description: 
Background and aims. Real-time reverse transcription polymerase chain reaction (RT-PCR) is the gold-standard assay to detect SARS-CoV-2, but it has limitations compared to viral load analysis. Quantitative detection improves surveillance, diagnosis, and prevention. We performed a comparative study of qualitative and quantitative tests for the diagnosis of COVID-19 on respiratory samples from patients screened for SARS-CoV-2 infection, and explored the correlation between viral load compared to the threshold cycle (Ct) value obtained in RT-PCR.Materials and methods. Sixty respiratory samples from patients affected by SARS-CoV-2 were subjected to both the qualitative (Allplex™ 2019-nCoV Seegene) and the quantitative (Clonit® Quanty COVID-19) assays, and the relationship between viral load and Ct value was assessed by Spearman correlation analysis (ρ). In addition, the viral load of samples collected from a patient with symptomatic cancer was monitored.Results. The results show 100% agreement between the results obtained with quantitative assay and the reference standards, whereas 99.2% agreement was found for the qualitative test. A strong negative Spearman’s correlation between the Ct values of the N genes and RdRP gene was observed from qualitative assay values and viral loads.Conclusions. Quantitative assay has a higher sensitivity than qualitative assay, and viral load testing allows the clinicians to better orient themself in the choice of therapeutic treatment to be adopted. The constantly higher viral load of clinical cases considered, irrespective of the different therapies used, confirms that viral load monitoring …
Publisher: 
Publication date: 
26 Oct 2021
Authors: 

Angela Saraiello, Federica Ferrentino, Nunzia Cuomo, Maria Grimaldi, Erasmo Falco, Marcello Raffone, Antimo Di Spirito, Nazareno Melillo, Gennaro Montanino, Valentino Guarino, Francesco Nappo, Martina Esposito, Ilaria Cavallaro, Giovanni D’Auria, Luigi Atripaldi, Claudia Tiberio

Biblio References: 
Volume: 36 Issue: 2
Origin: 
Microbiologia Medica