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• W4319080763 abstract "Although it is clinically important for acute respiratory tract (co)infections to have a rapid and accurate diagnosis, it is critical that respiratory medicine understands the advantages of current laboratory methods. In this study, we tested nasopharyngeal samples (n = 29) with a commercially available PCR assay and compared the results with those of a hybridization-capture-based mNGS workflow. Detection criteria for positive PCR samples was Ct < 35 and for mNGS samples it was >40% target coverage, median depth of 1X and RPKM > 10. A high degree of concordance (98.33% PPA and 100% NPA) was recorded. However, mNGS yielded positively 29 additional microorganisms (23 bacteria, 4 viruses, and 2 fungi) beyond PCR. We then characterized the microorganisms of each method into three phenotypic categories using the IDbyDNA Explify® Platform (Illumina® Inc, San Diego, CA, USA) for consideration of infectivity and trafficking potential to the lower respiratory region. The findings are significant for providing a comprehensive yet clinically relevant microbiology profile of acute upper respiratory infection, especially important in immunocompromised or immunocompetent with comorbidity respiratory cases or where traditional syndromic approaches fail to identify pathogenicity. Accordingly, this technology can be used to supplement current syndrome-based tests, and data can quickly and effectively be phenotypically characterized for trafficking potential, clinical (co)infection, and comorbid consideration-with promise to reduce morbidity and mortality." @default.
• W4319080763 created "2023-02-04" @default.
• W4319080763 creator A5008930001 @default.
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• W4319080763 date "2023-02-02" @default.
• W4319080763 modified "2023-09-27" @default.
• W4319080763 title "Deciphering Microbiota of Acute Upper Respiratory Infections: A Comparative Analysis of PCR and mNGS Methods for Lower Respiratory Trafficking Potential" @default.
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• W4319080763 doi "https://doi.org/10.3390/arm91010006" @default.
• W4319080763 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36825940" @default.
• W4319080763 hasPublicationYear "2023" @default.
• W4319080763 type Work @default.

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