BACKGROUND: New antiviral drugs are available for the treatment of influenza type A and type B infections. In clinical practice, antiviral use has rarely been guided by antecedent laboratory diagnosis. Defined clinical predictors of an influenza infection can help guide timely therapy and avoid unnecessary antibiotic use. OBJECTIVE: To examine which clinical signs and symptoms are most predictive of influenza infection in patients with influenza-like illness using a large data set derived from clinical trials of zanamivir. METHODS: This analysis is a retrospective, pooled analysis of baseline signs and symptoms from phase 2 and 3 clinical trial participants. It was conducted in mainly unvaccinated (mean age, 35 years) adults and adolescents who had influenza-like illness, defined as having fever or feverishness plus at least 2 of the following influenza-like symptoms: headache, myalgia, cough, or sore throat who underwent laboratory testing for influenza. Clinical signs and symptoms were evaluated in statistical models to identify those best predicting laboratory confirmation of influenza. RESULTS: Of 3744 subjects enrolled with baseline influenza-like symptoms, and included in this analysis, 2470 (66%) were confirmed to have influenza. Individuals with influenza were more likely to have cough (93% vs 80%), fever (68% vs 40%), cough and fever together (64% vs 33%), and/or nasal congestion (91% vs 81%) than those without influenza. The best multivariate predictors of influenza infections were cough and fever with a positive predictive value of 79% (P<. 001). The positive predictive value rose with the increase in the temperature at the time of recruitment. CONCLUSION: When influenza is circulating within the community, patients with an influenza-like illness who have both cough and fever within 48 hours of symptom onset are likely to have influenza and the administration of influenza antiviral therapy may be appropriate to consider. Arch Intern Med. 2000;160:3243-3247.
BACKGROUND: New antiviral drugs are available for the treatment of influenza type A and type B infections. In clinical practice, antiviral use has rarely been guided by antecedent laboratory diagnosis. Defined clinical predictors of an influenza infection can help guide timely therapy and avoid unnecessary antibiotic use. OBJECTIVE: To examine which clinical signs and symptoms are most predictive of influenza infection in patients with influenza-like illness using a large data set derived from clinical trials of zanamivir. METHODS: This analysis is a retrospective, pooled analysis of baseline signs and symptoms from phase 2 and 3 clinical trial participants. It was conducted in mainly unvaccinated (mean age, 35 years) adults and adolescents who had influenza-like illness, defined as having fever or feverishness plus at least 2 of the following influenza-like symptoms: headache, myalgia, cough, or sore throat who underwent laboratory testing for influenza. Clinical signs and symptoms were evaluated in statistical models to identify those best predicting laboratory confirmation of influenza. RESULTS: Of 3744 subjects enrolled with baseline influenza-like symptoms, and included in this analysis, 2470 (66%) were confirmed to have influenza. Individuals with influenza were more likely to have cough (93% vs 80%), fever (68% vs 40%), cough and fever together (64% vs 33%), and/or nasal congestion (91% vs 81%) than those without influenza. The best multivariate predictors of influenza infections were cough and fever with a positive predictive value of 79% (P<. 001). The positive predictive value rose with the increase in the temperature at the time of recruitment. CONCLUSION: When influenza is circulating within the community, patients with an influenza-like illness who have both cough and fever within 48 hours of symptom onset are likely to have influenza and the administration of influenza antiviral therapy may be appropriate to consider. Arch Intern Med. 2000;160:3243-3247.
Authors: Suzanne E Ohmit; John C Victor; Judy R Rotthoff; Esther R Teich; Rachel K Truscon; Laura L Baum; Bhavya Rangarajan; Duane W Newton; Matthew L Boulton; Arnold S Monto Journal: N Engl J Med Date: 2006-12-14 Impact factor: 91.245
Authors: Lionel A Mandell; Richard G Wunderink; Antonio Anzueto; John G Bartlett; G Douglas Campbell; Nathan C Dean; Scott F Dowell; Thomas M File; Daniel M Musher; Michael S Niederman; Antonio Torres; Cynthia G Whitney Journal: Clin Infect Dis Date: 2007-03-01 Impact factor: 9.079
Authors: Hui Zeng; Cynthia S Goldsmith; Taronna R Maines; Jessica A Belser; Kortney M Gustin; Andrew Pekosz; Sherif R Zaki; Jacqueline M Katz; Terrence M Tumpey Journal: J Virol Date: 2012-12-19 Impact factor: 5.103