Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

BACKGROUND: Clinical findings do not accurately predict laboratory diagnosis of influenza. Early identification of influenza is considered useful for proper management decisions in primary care. OBJECTIVE: We evaluated the diagnostic value of the presence and the severity of symptoms for the diagnosis of laboratory-confirmed influenza infection among adults presenting with influenza-like illness (ILI) in primary care. METHODS: Secondary analysis of patients with ILI who participated in a clinical trial from 2015 to 2018 in 15 European countries. Patients rated signs and symptoms as absent, minor, moderate, or major problem. A nasopharyngeal swab was taken for microbiological identification of influenza and other microorganisms. Models were generated considering (i) the presence of individual symptoms and (ii) the severity rating of symptoms. RESULTS: A total of 2,639 patients aged 18 or older were included in the analysis. The mean age was 41.8 ± 14.7 years, and 1,099 were men (42.1%). Influenza was microbiologically confirmed in 1,337 patients (51.1%). The area under the curve (AUC) of the model for the presence of any of seven symptoms for detecting influenza was 0.66 (95% confidence interval [CI]: 0.65-0.68), whereas the AUC of the symptom severity model, which included eight variables-cough, fever, muscle aches, sweating and/or chills, moderate to severe overall disease, age, abdominal pain, and sore throat-was 0.70 (95% CI: 0.69-0.72). CONCLUSION: Clinical prediction of microbiologically confirmed influenza in adults with ILI is slightly more accurate when based on patient reported symptom severity than when based on the presence or absence of symptoms.

Original publication




Journal article


Fam Pract

Publication Date



clinical decision rules, diagnosis, human, influenza, primary health care, symptom assessment