Dataset Information

Performance evaluation of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

ABSTRACT:

Objective

The aim of this study was to evaluate the QIAstat-Dx® Respiratory SARS-CoV-2 Panel (QIAstat-SARS-CoV-2), which is a closed, fully automated, multiplex polymerase chain reaction (PCR) assay that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 21 other pathogens that cause respiratory disease.

Methods

Nasopharyngeal swabs from patients with or suspected of having coronavirus disease 2019 were collected and tested at Bichat-Claude Bernard Hospital, Paris, France. Using the World Health Organisation-approved real-time-PCR assay developed by the Charité Institute of Virology as the reference, positive percent agreement (PPA) and negative percent agreement (NPA) were calculated.

Results

In total, 189 negative and 88 positive samples were analyzed. QIAstat-SARS-CoV-2 had an NPA of 90.48% (95% confidence interval (CI), 85.37%, 94.26%) and a PPA of 94.32% (95% CI, 87.24%, 98.13%). Co-infections were detected by QIAstat-SARS-CoV-2 in 4/277 specimens. The methods exhibited comparable failure rates (23/307 [7.5%] vs. 6/298 [2.0%] for QIAstat-SARS-CoV-2 and reference methods, respectively). The turnaround time was shorter for QIAstat-SARS-CoV-2 compared with the reference method (difference in mean -14:30 h [standard error, 0:03:23; 95% CI, -14:37, -14:24]; P < 0.001).

Conclusions

QIAstat-SARS-CoV-2 shows good agreement with the reference assay, providing faster and accurate results for detecting SARS-CoV-2.

SUBMITTER: Lebourgeois S

PROVIDER: S-EPMC8064816 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Publications

Performance evaluation of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

Lebourgeois Samuel S Storto Alexandre A Gout Bernard B Le Hingrat Quentin Q Ardila Tjader Gustave G Cerdan Maria Del Carmen MDC English Alistair A Pareja Josep J Love Joanna J Houhou-Fidouh Nadhira N Manissero Davide D Descamps Diane D Visseaux Benoit B

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 20210424

<h4>Objective</h4>The aim of this study was to evaluate the QIAstat-Dx® Respiratory SARS-CoV-2 Panel (QIAstat-SARS-CoV-2), which is a closed, fully automated, multiplex polymerase chain reaction (PCR) assay that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 21 other pathogens that cause respiratory disease.<h4>Methods</h4>Nasopharyngeal swabs from patients with or suspected of having coronavirus disease 2019 were collected and tested at Bichat-Claude Bernard Hospital, ...[more]

PMID: 33901651

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Project description:Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.

Project description:Syndromic multiplex panel testing enables simultaneous detection of multiple respiratory pathogens, but limited data is available on the comparative diagnostic performance of different testing systems. In this multicenter prospective study, we aimed to compare the QIAstat-Dx Respiratory Panel 2.0 (QIAstat-Dx-RP2.0) with the widely used BioFire-RP2.1, using 269 respiratory clinical specimens. Concordant test results were obtained in 232 (86.3%) cases. Discordant test results included 33 BioFire-RP2.1(+)/QIAstat-Dx-RP2.0(-) and 4 BioFire-RP2.1(-)/QIAstat-Dx-RP2.0(+) results. Discordant samples showed significantly lower pathogen loads than concordant ones (p < 0.01). Overall, the QIAstat-Dx-RP2.0 showed an analytical sensitivity of 50%-100% depending on the respiratory target, with an analytical specificity ≥ 99.0%. Most significant differences were found for the detection of adenovirus, human coronaviruses, respiratory syncytial virus, human rhinovirus/enterovirus and SARS-CoV-2 (kappa-score: 0.67-0.91). Co-detections of respiratory pathogens were identified in 47 cases by BioFire-RP2.1 and 29 by QIAstat-Dx-RP2.0. Agreement rates between the two multiplex panel tests decreased from 91.8% for single pathogen detections to 65.0% and 42.9% for co-detecting two and three pathogens, respectively. Pathogen loads were significantly lower in co-detections compared to single pathogen detections (p < 0.01), potentially explaining the lower detection rates with the QIAstat-Dx-RP2.0 in cases of multiple pathogens. In conclusion, our prospective multicenter evaluation showed good diagnostic performance of the QIAstat-Dx-RP2.0 assay, but lower detection rates for some respiratory targets compared to BioFire-RP2.1. As QIAstat-Dx-RP2.0 offers advantages in handling, noise emission, cost effectiveness, and provides semi-quantitative results compared to BioFire-RP2.1 an updated version with enhanced analytical sensitivity would be a viable alternative syndromic testing system for detecting respiratory pathogens.

Dataset Information

Performance evaluation of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

Objective

Methods

Results

Conclusions

Publications

Performance evaluation of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel.

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