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Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study
BACKGROUND: Multiplex real-time polymerase chain reaction assays have improved diagnostic sensitivity for a wide range of pathogens. However, co-detection of multiple agents and bacterial colonization make it difficult to distinguish between asymptomatic infection or illness aetiology. We assessed w...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137728/ https://www.ncbi.nlm.nih.gov/pubmed/30217168 http://dx.doi.org/10.1186/s12879-018-3358-4 |
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author | Tam, Clarence C. Offeddu, Vittoria Anderson, Kathryn B. Weg, Alden L. Macareo, Louis R. Ellison, Damon W. Rangsin, Ram Fernandez, Stefan Gibbons, Robert V. Yoon, In-Kyu Simasathien, Sriluck |
author_facet | Tam, Clarence C. Offeddu, Vittoria Anderson, Kathryn B. Weg, Alden L. Macareo, Louis R. Ellison, Damon W. Rangsin, Ram Fernandez, Stefan Gibbons, Robert V. Yoon, In-Kyu Simasathien, Sriluck |
author_sort | Tam, Clarence C. |
collection | PubMed |
description | BACKGROUND: Multiplex real-time polymerase chain reaction assays have improved diagnostic sensitivity for a wide range of pathogens. However, co-detection of multiple agents and bacterial colonization make it difficult to distinguish between asymptomatic infection or illness aetiology. We assessed whether semi-quantitative microbial load data can differentiate between symptomatic and asymptomatic states for common respiratory pathogens. METHODS: We obtained throat and nasal swab samples from military trainees at two Thai Army barracks. Specimens were collected at the start and end of 10-week training periods (non-acute samples), and from individuals who developed upper respiratory tract infection during training (acute samples). We analysed the samples using a commercial multiplex respiratory panel comprising 33 bacterial, viral and fungal targets. We used random effects tobit models to compare cycle threshold (Ct) value distributions from non-acute and acute samples. RESULTS: We analysed 341 non-acute and 145 acute swab samples from 274 participants. Haemophilus influenzae type B was the most commonly detected microbe (77.4% of non-acute and 64.8% of acute samples). In acute samples, nine specific microbe pairs were detected more frequently than expected by chance. Regression models indicated significantly lower microbial load in non-acute relative to acute samples for H. influenzae non-type B, Streptococcus pneumoniae and rhinovirus, although it was not possible to identify a Ct-value threshold indicating causal etiology for any of these organisms. CONCLUSIONS: Semi-quantitative measures of microbial concentration did not reliably differentiate between illness and asymptomatic colonization, suggesting that clinical symptoms may not always be directly related to microbial load for common respiratory infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3358-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6137728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61377282018-09-15 Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study Tam, Clarence C. Offeddu, Vittoria Anderson, Kathryn B. Weg, Alden L. Macareo, Louis R. Ellison, Damon W. Rangsin, Ram Fernandez, Stefan Gibbons, Robert V. Yoon, In-Kyu Simasathien, Sriluck BMC Infect Dis Research Article BACKGROUND: Multiplex real-time polymerase chain reaction assays have improved diagnostic sensitivity for a wide range of pathogens. However, co-detection of multiple agents and bacterial colonization make it difficult to distinguish between asymptomatic infection or illness aetiology. We assessed whether semi-quantitative microbial load data can differentiate between symptomatic and asymptomatic states for common respiratory pathogens. METHODS: We obtained throat and nasal swab samples from military trainees at two Thai Army barracks. Specimens were collected at the start and end of 10-week training periods (non-acute samples), and from individuals who developed upper respiratory tract infection during training (acute samples). We analysed the samples using a commercial multiplex respiratory panel comprising 33 bacterial, viral and fungal targets. We used random effects tobit models to compare cycle threshold (Ct) value distributions from non-acute and acute samples. RESULTS: We analysed 341 non-acute and 145 acute swab samples from 274 participants. Haemophilus influenzae type B was the most commonly detected microbe (77.4% of non-acute and 64.8% of acute samples). In acute samples, nine specific microbe pairs were detected more frequently than expected by chance. Regression models indicated significantly lower microbial load in non-acute relative to acute samples for H. influenzae non-type B, Streptococcus pneumoniae and rhinovirus, although it was not possible to identify a Ct-value threshold indicating causal etiology for any of these organisms. CONCLUSIONS: Semi-quantitative measures of microbial concentration did not reliably differentiate between illness and asymptomatic colonization, suggesting that clinical symptoms may not always be directly related to microbial load for common respiratory infections. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-018-3358-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-14 /pmc/articles/PMC6137728/ /pubmed/30217168 http://dx.doi.org/10.1186/s12879-018-3358-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Tam, Clarence C. Offeddu, Vittoria Anderson, Kathryn B. Weg, Alden L. Macareo, Louis R. Ellison, Damon W. Rangsin, Ram Fernandez, Stefan Gibbons, Robert V. Yoon, In-Kyu Simasathien, Sriluck Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title | Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title_full | Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title_fullStr | Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title_full_unstemmed | Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title_short | Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study |
title_sort | association between semi-quantitative microbial load and respiratory symptoms among thai military recruits: a prospective cohort study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137728/ https://www.ncbi.nlm.nih.gov/pubmed/30217168 http://dx.doi.org/10.1186/s12879-018-3358-4 |
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