Development of a prediction tool for patients presenting with acute cough in primary care : A prognostic study spanning six European countries

Background: Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. Aim: The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Design and setting: Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Method: Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. Results: The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or or