Symptoms of Influenza Virus Infection in Hospitalized Patients

Author:

van den Dool C.,Hak E.,Wallinga J.,van Loon A. M.,Lammers J. W. J.,Bonten M. J. M.

Abstract

Background.During influenza outbreaks, fever and cough are the most accurate symptoms in predicting influenza virus infection in the community.Objective.To determine the usefulness of fever, cough, and other symptoms for diagnosing influenza virus infection in hospitalized patients.Design.Prospective cohort study.Setting.Three wards (pulmonology, internal medicine and infectious diseases, and geriatrics) of a tertiary care hospital in the Netherlands.Patients.All patients staying in the wards during peak national influenza activity in the 2005-2006 and 2006-2007 influenza seasons.Methods.During peak influenza activity, the presence of fever, cough, and/or other symptoms possibly associated with influenza was monitored for all patients, and nose and throat swab samples were taken twice weekly for virologic analysis.Results.Of 264 patients, 23 (9%) tested positive for influenza virus. The positive predictive value of fever and cough for the diagnosis of influenza virus infection was 23% (95% confidence interval, 0%-62%), and the sensitivity was 35% (95% confidence interval, 11%-58%). The combination of symptoms with the highest positive predictive value (40%) was that of cough, chills, and obstructed nose or coryza. The combination of cough and chills or fever had the highest sensitivity (60%). None of the combinations of symptoms had both a positive predictive value and a sensitivity higher than 40%.Conclusions.Both the sensitivity and the positive predictive value of fever, cough, and/or other symptoms for the diagnosis of influenza virus infection in hospitalized patients are low. The use of these common symptoms for treatment decisions and infection control management will probably be insufficient to contain a nosocomial outbreak, because many influenza cases will remain unidentified.

Publisher

Cambridge University Press (CUP)

Subject

Infectious Diseases,Microbiology (medical),Epidemiology

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