Clinical prediction of laboratory-confirmed influenza in adults with influenza-like illness in primary care. A randomized controlled trial secondary analysis in 15 European countries. (6th October 2021)

• Record Type: Journal Article
• Authors: Ouchi, Dan; García-Sangenís, Ana; Moragas, Ana; van der Velden, Alike W; Verheij, Theo J; Butler, Christopher C; Bongard, Emily; Coenen, Samuel; Cook, Johanna; Francis, Nick A; Godycki-Cwirko, Maciek; Lundgren, Pia Touboul; Lionis, Christos; Radzeviciene Jurgute, Ruta; Chlabicz, Sławomir; De Sutter, An; Bucher, Heiner C; Seifert, Bohumil; Kovács, Bernadett; de Paor, Muireann; Sundvall, Pär-Daniel; Aabenhus, Rune; Harbin, Nicolay Jonassen; Ieven, Greet; Goossens, Herman; Lindbæk, Morten; Bjerrum, Lars; Llor, Carl
• Is Part Of: Family practice. Volume 39:Number 3(2022)
• Page Start: 398
• Page End: 405
• Publication Date: 2021-10-06
• Subjects: clinical decision rules -- diagnosis -- human -- influenza -- primary health care -- symptom assessment; Primary care (Medicine) -- Periodicals; Clinical medicine -- Periodicals; 616.005
• DOI: 10.1093/fampra/cmab122
• Languages: English
• ISSNs: 0263-2136

Abstract

Abstract: 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. Lay Summary: Influenza is usually diagnosed clinically. However, the accuracy of a diagnosis of influenza based on clinical features is limited because symptoms overlap considerably with those caused by other microorganisms. This study examined whether identification of the severity rather than the presence of key signs and symptoms could aid in the diagnosis of influenza, thereby helping clinicians to determine when antiviral agent use is appropriate. The authors used the database of a previous randomized clinical trial on the effectiveness of an antiviral carried out in primary care centers in 15 countries in Europe during three epidemic periods from 2015/2016 to 2017/2018. Participants with influenza symptoms were included and they were asked about the presence and severity of different symptoms during the baseline visit with their doctors and a nasopharyngeal swab was taken for microbiological analysis. Overall, only 51% of the patients aged 18 or older had a confirmed influenza infection. Clinical findings are not particularly useful for confirming or excluding the diagnosis of influenza. However, the results of our study recommend considering how intense the different symptoms are, since key symptoms rated as moderate or severe are slightly better for predicting flu rather than the presence or absence of these symptoms.