Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study
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 as...
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doaj-fcc75012fd4f4b5ab833ca21a6bd296e2020-11-25T03:54:18ZengBMCBMC Infectious Diseases1471-23342018-09-0118111010.1186/s12879-018-3358-4Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort studyClarence C. Tam0Vittoria Offeddu1Kathryn B. Anderson2Alden L. Weg3Louis R. Macareo4Damon W. Ellison5Ram Rangsin6Stefan Fernandez7Robert V. Gibbons8In-Kyu Yoon9Sriluck Simasathien10Saw Swee Hock School of Public Health, National University of Singapore and National University Health SystemSaw Swee Hock School of Public Health, National University of Singapore and National University Health SystemUniversity of MinnesotaArmed Forces Research Institute of Medical SciencesArmed Forces Research Institute of Medical SciencesArmed Forces Research Institute of Medical SciencesPhramongkutklao College of MedicineArmed Forces Research Institute of Medical SciencesUniversity of Texas at San AntonioInternational Vaccine InstitutePhramongkutklao HospitalAbstract 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.http://link.springer.com/article/10.1186/s12879-018-3358-4Multiplex PCR diagnosticsRespiratory illnessUpper respiratory tract infectionAsymptomatic infectionInfluenza-like illnessInfluenza |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 |
spellingShingle |
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 Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: a prospective cohort study BMC Infectious Diseases Multiplex PCR diagnostics Respiratory illness Upper respiratory tract infection Asymptomatic infection Influenza-like illness Influenza |
author_facet |
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 |
author_sort |
Clarence C. Tam |
title |
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_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_sort |
association between semi-quantitative microbial load and respiratory symptoms among thai military recruits: a prospective cohort study |
publisher |
BMC |
series |
BMC Infectious Diseases |
issn |
1471-2334 |
publishDate |
2018-09-01 |
description |
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. |
topic |
Multiplex PCR diagnostics Respiratory illness Upper respiratory tract infection Asymptomatic infection Influenza-like illness Influenza |
url |
http://link.springer.com/article/10.1186/s12879-018-3358-4 |
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