Predicting Influenza in Young Military Personnel
Author Information
Author(s): Lee Vernon J., Yap Jonathan, Cook Alex R., Tan Chi Hsien, Loh Jin-Phang, Koh Wee-Hong, Lim Elizabeth A. S., Liaw Jasper C. W., Chew Janet S. W., Hossain Iqbal, Chan Ka Wei, Ting Pei-Jun, Ng Sock-Hoon, Gao Qiuhan, Kelly Paul M., Chen Mark I., Tambyah Paul A., Tan Boon Huan
Primary Institution: Biodefence Centre, Ministry of Defence, Singapore
Hypothesis
Can clinical features help predict influenza infection among young adults with febrile respiratory illness?
Conclusion
A clinical diagnostic model can better predict influenza than conventional definitions among young adults with febrile respiratory illness.
Supporting Evidence
- 821 out of 2858 subjects had influenza, with various subtypes identified.
- Influenza-positive cases were more likely to present with running nose and chills.
- The clinical diagnostic model had a sensitivity of 65% and specificity of 69%.
- The model performed significantly better than conventional influenza-like illness criteria.
Takeaway
Doctors can use certain symptoms to guess if someone has the flu, which helps them decide how to treat patients better.
Methodology
The study used nasal washes and questionnaires to collect data from military personnel with febrile respiratory illness, analyzing symptoms and testing for influenza.
Potential Biases
Potential biases include consultation patterns unique to the military population and recall biases from follow-up interviews.
Limitations
The study primarily involved young male adults and may not represent other demographics; it also focused on symptomatic cases, potentially missing mild infections.
Participant Demographics
Average age was 21 years, with 99.8% being male.
Statistical Information
P-Value
<0.001
Confidence Interval
95% CI: 58%, 72%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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