Predicting poor outcome in patients presenting to primary care with acute cough

Abstract

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. We 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. 2604 adults presenting to primary care with acute cough
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 to that of existing prediction rules, using the models’ area under the receiver operator characteristic curve (AUC), and improvement obtained by including additional test results (C-reactive protein (CRP), blood urea nitrogen (BUN), chest radiography or etiology) 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 (above or below 45 years), severity of sputum, presence of crackles and diastolic blood pressure (above or below 85 mmHg), and severity of sputum. Although performance of the new prediction rule was moderate (sensitivity 62%; specificity 59%; positive predictive value 27%; negative predictive value 86%; AUC 0.62 [0.61-0.67]), it outperformed all existing prediction rules used today (highest AUC 0.53 [0.51-0.56]) and could not be improved by including additional test results (highest AUC 0.64 [0.62-0.68]).
Conclusion. The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results.

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Identifiers

ORCID for Paul Little: orcid.org/0000-0003-3664-1873

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