TY - JOUR
T1 - Association between semi-quantitative microbial load and respiratory symptoms among Thai military recruits
T2 - A prospective cohort study 11 Medical and Health Sciences 1108 Medical Microbiology
AU - Tam, Clarence C.
AU - Offeddu, Vittoria
AU - Anderson, Katie B
AU - Weg, Alden L.
AU - Macareo, Louis R.
AU - Ellison, Damon W.
AU - Rangsin, Ram
AU - Fernandez, Stefan
AU - Gibbons, Robert V.
AU - Yoon, In Kyu
AU - Simasathien, Sriluck
N1 - Funding Information:
This work was supported by the United States Department of Defense - Global Emerging Infectious Disease Surveillance (DoD - GEIS), Protocol 989A.
PY - 2018/9/14
Y1 - 2018/9/14
N2 - 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.
AB - 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.
KW - Asymptomatic infection
KW - Haemophilus influenza
KW - Influenza
KW - Influenza-like illness
KW - Multiplex PCR diagnostics
KW - Respiratory illness
KW - Upper respiratory tract infection
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U2 - 10.1186/s12879-018-3358-4
DO - 10.1186/s12879-018-3358-4
M3 - Article
C2 - 30217168
AN - SCOPUS:85053356287
VL - 18
JO - BMC Infectious Diseases
JF - BMC Infectious Diseases
SN - 1471-2334
IS - 1
M1 - 462
ER -