Investigation and management of chronic cough using a probability-based algorithm

Chronic cough is a common and distressing symptom. A novel algorithm has been developed for the management of chronic cough, in which an assessment of clinical probability of disease determines the need to proceed to investigation. In this study, the performance of this algorithm in clinical practice was prospectively evaluated. A total of 131 consecutively referred patients (86 females) whose principal presenting symptom was a cough of duration >8 weeks were studied. Their age (median (range)) was 60 (16-88) yrs and cough duration 5.9 (0.2-65) yrs. A cause of cough was established in 93% of cases. The most frequent diagnoses were asthma (24% of cases), gastro-oesophageal disease (22%), post-viral cough (8%), bronchiectasis (8%) and interstitial lung disease (8%). Primary pulmonary disease was significantly more likely in patients with a productive cough and in patients with an abnormal chest radiograph. Only a small proportion (<8%) of patients had multiple causes of cough. The probability of treatment started on the basis of a high clinical suspicion of either asthma, gastro-oesophageal disease or rhinitis being successful was 74%. Overall, 26% of the patients were managed successfully without the need for any form of investigation other than chest radiography and spirometry. Use of the algorithm resulted in identification of the cause of cough and successful treatment in the large majority of cases. It is concluded that this protocol has the potential to improve management by providing a structured approach, reducing the number of investigations performed, and minimising unnecessary delays in treatment.