Research Article: Clinical and laboratory predictors of influenza infection among individuals with influenza-like illness presenting to an urban Thai hospital over a five-year period

Date Published: March 7, 2018

Publisher: Public Library of Science

Author(s): Kathryn B. Anderson, Sriluck Simasathien, Veerachai Watanaveeradej, Alden L. Weg, Damon W. Ellison, Detchvijitr Suwanpakdee, Chonticha Klungthong, Thipwipha Phonpakobsin, Phirangkul Kerdpanich, Danabhand Phiboonbanakit, Robert V. Gibbons, Stefan Fernandez, Louis R. Macareo, In-Kyu Yoon, Richard G. Jarman, Baochuan Lin.

http://doi.org/10.1371/journal.pone.0193050

Abstract

Early diagnosis of influenza infection maximizes the effectiveness of antiviral medicines. Here, we assess the ability for clinical characteristics and rapid influenza tests to predict PCR-confirmed influenza infection in a sentinel, cross-sectional study for influenza-like illness (ILI) in Thailand. Participants meeting criteria for acute ILI (fever > 38°C and cough or sore throat) were recruited from inpatient and outpatient departments in Bangkok, Thailand, from 2009–2014. The primary endpoint for the study was the occurrence of virologically-confirmed influenza infection (based upon detection of viral RNA by RT-PCR) among individuals presenting for care with ILI. Nasal and throat swabs were tested by rapid influenza test (QuickVue) and by RT-PCR. Vaccine effectiveness (VE) was calculated using the case test-negative method. Classification and Regression Tree (CART) analysis was used to predict influenza RT-PCR positivity based upon symptoms reported. We enrolled 4572 individuals with ILI; 32.7% had detectable influenza RNA by RT-PCR. Influenza cases were attributable to influenza B (38.6%), A(H1N1)pdm09 (35.1%), and A(H3N2) (26.3%) viruses. VE was highest against influenza A(H1N1)pdm09 virus and among adults. The most important symptoms for predicting influenza PCR-positivity among patients with ILI were cough, runny nose, chills, and body aches. The accuracy of the CART predictive model was 72.8%, with an NPV of 78.1% and a PPV of 59.7%. During epidemic periods, PPV improved to 68.5%. The PPV of the QuickVue assay relative to RT-PCR was 93.0% overall, with peak performance during epidemic periods and in the absence of oseltamivir treatment. Clinical criteria demonstrated poor predictive capability outside of epidemic periods while rapid tests were reasonably accurate and may provide an acceptable alternative to RT-PCR testing in resource-limited areas.

Partial Text

Infection with influenza viruses poses a significant public health threat globally, with a disproportionate impact in the developing world [1]. Southeast Asia is a particularly important region of interest for influenza epidemiology and ecology, with a high burden of disease and complex transmission patterns. Many areas experience year-round transmission, promoting the emergence and seeding of viruses into other regions.

A total of 4572 individuals were enrolled between August 2009 and August 2014, of which 1493 (32.7%) had detectable influenza RNA by RT-PCR (hereafter described as influenza “cases”). The majority of influenza cases were attributable to influenza B (38.6%), then influenza A(H1N1)pdm09 (35.1%), followed by influenza A(H3N2) (26.4%). All influenza A infections were attributable to influenza A(H1N1)pdm09 or influenza A(H3N2) in the cohort. There was one case of dual infection with influenza B and influenza A(H1N1)pdm09 detected by RT-PCR.

Our clinical prediction algorithm to discern influenza from non-influenza ILI had moderate accuracy (73%) but poor PPV (59.7%). This is consistent with prior studies which indicated that it is more feasible to identify what is not influenza than what is influenza among patients with ILI [14–17], given significant overlap of clinical symptoms between influenza and other respiratory pathogens. PPV improved to 69% during epidemic months, however, overall test performance (by AUC) was not dramatically improved. For this study, our efforts were likely further limited by a lack of longitudinal data regarding the time course of symptoms. Future efforts will include retrospective chart reviews of influenza cases and hospitalized patients to inform the development of more dynamic clinical prediction algorithms and to attempt to identify individuals at high risk of progression to severe disease.

Despite the widespread availability of influenza vaccines and antivirals, the global burden of influenza-related disease continues to be high. In this manuscript, we report on predictors of vaccination, influenza infection, and vaccine effectiveness in a cohort of individuals presenting with ILI to an urban Thai hospital. Based upon the significant overlap in the clinical presentation between influenza and other influenza-like illnesses, we do not recommend the routine use of clinical algorithms for the identification of seasonal influenza. We suggest that the expanded use of rapid influenza diagnostic tests such as QuickVue would allow early detection of influenza infection in resource-limited settings and facilitate the appropriate allocation of antimicrobial medications. Finally, we suggest that there are multiple groups who would benefit from targeted vaccination campaigns such as members of the military, healthcare workers, and adults with medical comorbidities, given their relatively high rates of influenza infection but low rates of reported vaccination.

 

Source:

http://doi.org/10.1371/journal.pone.0193050

 

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