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Published in: BMC Infectious Diseases 1/2018

Open Access 01-12-2018 | Research article

Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study

Authors: Clarence C. Tam, Vittoria Offeddu, Kathryn B. Anderson, Alden L. Weg, Louis R. Macareo, Damon W. Ellison, Ram Rangsin, Stefan Fernandez, Robert V. Gibbons, In-Kyu Yoon, Sriluck Simasathien

Published in: BMC Infectious Diseases | Issue 1/2018

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Abstract

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.
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Literature
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Metadata
Title
Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study
Authors
Clarence C. Tam
Vittoria Offeddu
Kathryn B. Anderson
Alden L. Weg
Louis R. Macareo
Damon W. Ellison
Ram Rangsin
Stefan Fernandez
Robert V. Gibbons
In-Kyu Yoon
Sriluck Simasathien
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2018
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-018-3358-4

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