Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12879-018-3358-4
Title: Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: A prospective cohort study 11 Medical and Health Sciences 1108 Medical Microbiology
Authors: Tam, C.C 
Offeddu, V 
Anderson, K.B
Weg, A.L
Macareo, L.R
Ellison, D.W
Rangsin, R
Fernandez, S
Gibbons, R.V
Yoon, I.-K
Simasathien, S
Keywords: adult
Article
asymptomatic disease
cohort analysis
controlled study
Haemophilus influenzae type b
human
major clinical study
microorganism detection
multiplex polymerase chain reaction
mycosis
nose smear
pathogen load
prospective study
quantitative analysis
real time polymerase chain reaction
regression analysis
Rhinovirus
soldier
Streptococcus pneumoniae
Thai (citizen)
throat culture
training
upper respiratory tract infection
virus infection
acute disease
female
genetics
isolation and purification
male
metabolism
microbiology
nose cavity
pharynx
procedures
respiratory tract infection
soldier
Thailand
virology
bacterial DNA
virus RNA
Acute Disease
DNA, Bacterial
Female
Haemophilus influenzae type b
Humans
Male
Military Personnel
Multiplex Polymerase Chain Reaction
Nasal Cavity
Pharynx
Prospective Studies
Respiratory Tract Infections
Rhinovirus
RNA, Viral
Streptococcus pneumoniae
Thailand
Issue Date: 2018
Citation: Tam, C.C, Offeddu, V, Anderson, K.B, Weg, A.L, Macareo, L.R, Ellison, D.W, Rangsin, R, Fernandez, S, Gibbons, R.V, Yoon, I.-K, Simasathien, S (2018). Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits: A prospective cohort study 11 Medical and Health Sciences 1108 Medical Microbiology. BMC Infectious Diseases 18 (1) : 462. ScholarBank@NUS Repository. https://doi.org/10.1186/s12879-018-3358-4
Rights: Attribution 4.0 International
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. © 2018 The Author(s).
Source Title: BMC Infectious Diseases
URI: https://scholarbank.nus.edu.sg/handle/10635/181178
ISSN: 14712334
DOI: 10.1186/s12879-018-3358-4
Rights: Attribution 4.0 International
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