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Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods
Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them diffi...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10022352/ https://www.ncbi.nlm.nih.gov/pubmed/36962439 http://dx.doi.org/10.1371/journal.pgph.0000811 |
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author | Bartlow, Andrew W. Stromberg, Zachary R. Gleasner, Cheryl D. Hu, Bin Davenport, Karen W. Jakhar, Shailja Li, Po-E Vosburg, Molly Garimella, Madhavi Chain, Patrick S. G. Erkkila, Tracy H. Fair, Jeanne M. Mukundan, Harshini |
author_facet | Bartlow, Andrew W. Stromberg, Zachary R. Gleasner, Cheryl D. Hu, Bin Davenport, Karen W. Jakhar, Shailja Li, Po-E Vosburg, Molly Garimella, Madhavi Chain, Patrick S. G. Erkkila, Tracy H. Fair, Jeanne M. Mukundan, Harshini |
author_sort | Bartlow, Andrew W. |
collection | PubMed |
description | Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks. |
format | Online Article Text |
id | pubmed-10022352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100223522023-03-17 Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods Bartlow, Andrew W. Stromberg, Zachary R. Gleasner, Cheryl D. Hu, Bin Davenport, Karen W. Jakhar, Shailja Li, Po-E Vosburg, Molly Garimella, Madhavi Chain, Patrick S. G. Erkkila, Tracy H. Fair, Jeanne M. Mukundan, Harshini PLOS Glob Public Health Research Article Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks. Public Library of Science 2022-07-20 /pmc/articles/PMC10022352/ /pubmed/36962439 http://dx.doi.org/10.1371/journal.pgph.0000811 Text en © 2022 Bartlow et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bartlow, Andrew W. Stromberg, Zachary R. Gleasner, Cheryl D. Hu, Bin Davenport, Karen W. Jakhar, Shailja Li, Po-E Vosburg, Molly Garimella, Madhavi Chain, Patrick S. G. Erkkila, Tracy H. Fair, Jeanne M. Mukundan, Harshini Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title | Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title_full | Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title_fullStr | Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title_full_unstemmed | Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title_short | Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods |
title_sort | comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and pcr-based methods |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10022352/ https://www.ncbi.nlm.nih.gov/pubmed/36962439 http://dx.doi.org/10.1371/journal.pgph.0000811 |
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