Clinical prediction rules combining signs, symptoms and epidemiological context to distinguish influenza from influenza-like illnesses in primary care: a cross sectional study

Abstract

Background: During an influenza epidemic prompt diagnosis of influenza is important. This diagnosis however is still essentially based on the interpretation of symptoms and signs by general practitioners. No single symptom is specific enough to be useful in differentiating influenza from other respiratory infections. Our objective is to formulate prediction rules for the diagnosis of influenza with the best diagnostic performance, combining symptoms, signs and context among patients with influenza-like illness.

Methods: During five consecutive winter periods (2002-2007) 138 sentinel general practitioners sampled (naso- and oropharyngeal swabs) 4597 patients with an influenza-like illness (ILI) and registered their symptoms and signs, general characteristics and contextual information. The samples were analysed by a DirectigenFlu-A&B and RT-PCR tests. 4584 records were useful for further analysis.Starting from the most relevant variables in a Generalized Estimating Equations (GEE) model, we calculated the area under the Receiver Operating Characteristic curve (ROC AUC), sensitivity, specificity and likelihood ratios for positive (LR+) and negative test results (LR-) of single and combined signs, symptoms and context taking into account pre-test and post-test odds.

Results: In total 52.6% (2409/4584) of the samples were positive for influenza virus: 64% (2066/3212) during and 25% (343/1372) pre/post an influenza epidemic. During and pre/post an influenza epidemic the LR+ of 'previous flu-like contacts', 'coughing', 'expectoration on the first day of illness' and 'body temperature above 37.8°C' is 3.35 (95%CI 2.67-4.03) and 1.34 (95%CI 0.97-1.72), respectively. During and pre/post an influenza epidemic the LR- of 'coughing' and 'a body temperature above 37.8°C' is 0.34 (95%CI 0.27-0.41) and 0.07 (95%CI 0.05-0.08), respectively.

Conclusions: Ruling out influenza using clinical and contextual information is easier than ruling it in. Outside an influenza epidemic the absence of cough and fever (> 37,8°C) makes influenza 14 times less likely in ILI patients. During an epidemic the presence of 'previous flu-like contacts', cough, 'expectoration on the first day of illness' and fever (>37,8°C) increases the likelihood for influenza threefold. The additional diagnostic value of rapid point of care tests especially for confirming influenza still has to be established.

Figure 1

Number of influenza-like illness (ILI) per 100 consultations and number of influenza positive specimens season 2002/2003 to season 2006/2007. Note: this figure is part of the historical graphs made by the National Influenza Centre, Virology, Brussels, Belgium http://www.euroflu.org/html/hist_graphs.html and used here with their permission.

Figure 2

Diagnostic flow-diagram pre/post and during the influenza epidemics n = 4584 (imputed data). Note: about 30% of all the ILI patients were swabbed. No information is available about the no swabbed ILI patients. From the 4597 swabbed patients 13 records missed any clinical information. Of the remaining 4584, 18.7% had missing values in at least one of the following items: age, number of illness days and/or temperature, 3738 were full records.