4.7 Article

Verification of analytical bacterial spectrum of QIAstat-Dx® GI V2 and Novodiag® Bacterial GE+V2-0 diagnostic panels

Journal

JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY
Volume 76, Issue -, Pages 50-57

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/jac/dkab242

Keywords

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Funding

  1. QIAGEN
  2. Mobidiag

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This study assessed and compared the performance of two syndromic panel-based testing systems, QIAstat-Dx (R) Gastrointestinal Panel V2 (QGI) and Novodiag (R) Bacterial GE+ V2-0 (NGE) in detecting microbial species causing acute diarrhoea. QGI demonstrated higher sensitivity in identifying C. difficile, while NGE showed suboptimal detection in certain bacteria.
Background: Implementing multiplex PCR or syndromic panel-based testing platforms to detect microbial species that cause acute diarrhoea may guide patient management more effectively and efficiently. Objectives: To assess and compare the performance of two syndromic panel-based testing systems, QIAstat-Dx (R) Gastrointestinal Panel V2 (QGI) and the Novodiag (R) Bacterial GE+ V2-0 (NGE). Methods: The QGI and NGE panels include 16 and 14 bacterial gastrointestinal pathogens, respectively. The performance of the panels was tested retrospectively using 141 positive clinical stool specimens, External Quality Assessment (EQA) panels and spiked faecal specimens. Results: For Campylobacter jejuni and coli (n=20), Salmonella (n=24), Shigella (n=13), Yersinia enterocolitica (non-1A biotypes) (n=8), Clostridioides difficile (n=24) and Vibrio parahaemolyticus (n=2), QGI correctly verified 19/20, 20/24, 13/13, 8/8, 23/24 and 2/2, whereas NGE correctly verified 20/20, 17/24, 13/13, 8/8, 14/24 and 1/2. Among diarrhoeagenic Escherichia coli (n=29), QGI reported one Shiga toxin-producing E. coli (STEC) stx1a O26:H11 as STEC serotype O157:H7 and NGE failed on one enteropathogenic E. coli, one enteroaggregative E. coli and one STEC (stx2e). Y. enterocolitica biotype 1A (non-pathogenic) (n=6) were all positive in QGI, but negative in NGE. Conclusions: Both QGI and NGE testing panels can improve laboratory workflow and patient management by providing user-friendly platforms that can rapidly detect a number of targets with one specimen. QGI was significantly more sensitive in identifying C. difficile. Both methods had suboptimal detection of Salmonella and this needs to be examined further. The short hands-on time and turnaround time are of value for on-demand testing and use in a high-throughput setting.

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