ArticlePloS one2011
A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Trial
- Clinical Practice Guidelines by the Infectious Diseases Society of America: 2018 Update on Diagnosis, Treatment, Chemoprophylaxis, and Institutional Outbreak Management of Seasonal Influenzaa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019Article
- The eyes have it: influenza virus infection beyond the respiratory tract.The Lancet. Infectious diseases · 2018Review
- Risk factors for febrile respiratory illness and mono-viral infections in a semi-closed military environment: a case-control study.BMC infectious diseases · 2015Article
- An under-recognized influenza epidemic identified by rapid influenza testing, southern Sri Lanka, 2013.The American journal of tropical medicine and hygiene · 2015Article
- Retrospective analysis of demographic and clinical factors associated with etiology of febrile respiratory illness among US military basic trainees.BMC infectious diseases · 2014Article
- Respiratory viral pathogens among Singapore military servicemen 2009-2012: epidemiology and clinical characteristics.BMC infectious diseases · 2014Article
- Prediction of clinical factors associated with pandemic influenza A (H1N1) 2009 in Pakistan.PloS one · 2014Article
- Clinical characteristics and outcomes of influenza and other influenza-like illnesses in Mexico City.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2013Article
- Occurrence of AH1N1 viral infection and clinical features in symptomatic patients who received medical care during the 2009 influenza pandemic in Central Mexico.BMC infectious diseases · 2012Article
- Circulation of other respiratory viruses and viral co-infection during the 2009 pandemic influenza.Enfermedades infecciosas y microbiologia clinica · 2012Review
- The viral etiology of an influenza-like illness during the 2009 pandemic.Journal of medical virology · 2012Article
- Determination of clinical and demographic predictors of laboratory-confirmed influenza with subtype analysis.BMC infectious diseases · 2012Article
- Differing clinical characteristics between influenza strains among young healthy adults in the tropics.BMC infectious diseases · 2012Article
Corrections and comments
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Authors and funding
18 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionInfluenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI) to determine predictors of influenza infection.
methodsPersonnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat) were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model.
results821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9%) had 2009 influenza A (H1N1), 58 (7.1%) seasonal influenza A (H3N2) and 269 (32.8%) influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%), specificity of 69% (95% CI: 62%, 75%), and overall accuracy of 68% (95% CI: 64%, 71%), performing significantly better than conventional influenza-like illness (ILI) criteria.
conclusionsUse of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.
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