BACKGROUND: Although influenza is a commonly encountered condition in primary care, and diagnosis is increasingly important given the availability of new treatments, there has been no systematic review of the evidence on clinical diagnosis. METHODS: This was a systematic review of the literature with meta-analysis where appropriate. We included cohort studies and randomized trials that compared the history and physical examination with a reference laboratory test for the diagnosis of influenza A and/or B. The primary outcomes were the sensitivity, specificity, likelihood ratios, and area under the receiver-operating characteristic (ROC) curve. RESULTS: Seven studies reported the sensitivity and specificity for a total of 59 variables. We combined studies of influenza A or B alone with those of influenza A and B. Rigors [likelihood ratio (LR) +7.2], the combination of fever and presenting within 3 days of the onset of illness (LR +4.0), and sweating (LR +3.0) were best at ruling-in influenza when present. When absent, the following decreased the likelihood of influenza: any systemic symptoms (LR -0.36), coughing (LR -0.38), not being able to cope with daily activities (LR -0.39), and being confined to bed (LR -0.50). Cough, nasal congestion, and fever (subjective or objective) had the highest calculable areas under the ROC curve. CONCLUSIONS: Individual signs and symptoms are of limited value for the diagnosis of influenza. Development of clinical decision rules that systematically combine symptoms may be a more useful strategy.
BACKGROUND: Although influenza is a commonly encountered condition in primary care, and diagnosis is increasingly important given the availability of new treatments, there has been no systematic review of the evidence on clinical diagnosis. METHODS: This was a systematic review of the literature with meta-analysis where appropriate. We included cohort studies and randomized trials that compared the history and physical examination with a reference laboratory test for the diagnosis of influenza A and/or B. The primary outcomes were the sensitivity, specificity, likelihood ratios, and area under the receiver-operating characteristic (ROC) curve. RESULTS: Seven studies reported the sensitivity and specificity for a total of 59 variables. We combined studies of influenza A or B alone with those of influenza A and B. Rigors [likelihood ratio (LR) +7.2], the combination of fever and presenting within 3 days of the onset of illness (LR +4.0), and sweating (LR +3.0) were best at ruling-in influenza when present. When absent, the following decreased the likelihood of influenza: any systemic symptoms (LR -0.36), coughing (LR -0.38), not being able to cope with daily activities (LR -0.39), and being confined to bed (LR -0.50). Cough, nasal congestion, and fever (subjective or objective) had the highest calculable areas under the ROC curve. CONCLUSIONS: Individual signs and symptoms are of limited value for the diagnosis of influenza. Development of clinical decision rules that systematically combine symptoms may be a more useful strategy.
Authors: Andrea F Dugas; Alexandra Valsamakis; Mihir R Atreya; Komal Thind; Peter Alarcon Manchego; Annum Faisal; Charlotte A Gaydos; Richard E Rothman Journal: Am J Emerg Med Date: 2015-03-12 Impact factor: 2.469
Authors: Daniel J Mollura; Deborah S Asnis; Robert S Crupi; Rick Conetta; David S Feigin; Mike Bray; Jeffery K Taubenberger; David A Bluemke Journal: AJR Am J Roentgenol Date: 2009-12 Impact factor: 3.959
Authors: Anastasia F Hutchinson; Jim Black; Michelle A Thompson; Steven Bozinovski; Caroline A Brand; David M Smallwood; Louis B Irving; Gary P Anderson Journal: Influenza Other Respir Viruses Date: 2010-01 Impact factor: 4.380
Authors: Tae Un Yang; Hee Jin Cheong; Joon Young Song; Jin Soo Lee; Seong-Heon Wie; Young Keun Kim; Won Suk Choi; Jacob Lee; Hye Won Jeong; Woo Joo Kim Journal: PLoS One Date: 2014-01-24 Impact factor: 3.240