Influence of CRP testing and clinical findings on antibiotic prescribing in adults presenting with acute cough in primary care
- PMID: 20704523
- PMCID: PMC3444795
- DOI: 10.3109/02813432.2010.506995
Influence of CRP testing and clinical findings on antibiotic prescribing in adults presenting with acute cough in primary care
Abstract
Objective: Respiratory tract infections are the most common indication for antibiotic prescribing in primary care. The value of clinical findings in lower respiratory tract infection (LRTI) is known to be overrated. This study aimed to determine the independent influence of a point of care test (POCT) for C-reactive protein (CRP) on the prescription of antibiotics in patients with acute cough or symptoms suggestive of LRTI, and how symptoms and chest findings influence the decision to prescribe when the test is and is not used.
Design: Prospective observational study of presentation and management of acute cough/LRTI in adults.
Setting: Primary care research networks in Norway, Sweden, and Wales.
Subjects: Adult patients contacting their GP with symptoms of acute cough/LRTI.
Main outcome measures: Predictors of antibiotic prescribing were evaluated in those tested and those not tested with a POCT for CRP using logistic regression and receiver operating characteristic (ROC) curve analysis.
Results: A total of 803 patients were recruited in the three networks. Among the 372 patients tested with a POCT for CRP, the CRP value was the strongest independent predictor of antibiotic prescribing, with an odds ratio (OR) of CRP ≥ 50 mg/L of 98.1. Crackles on auscultation and a patient preference for antibiotics perceived by the GP were the strongest predictors of antibiotic prescribing when the CRP test was not used.
Conclusions: The CRP result is a major influence in the decision whether or not to prescribe antibiotics for acute cough. Clinicians attach less weight to discoloured sputum and abnormal lung sounds when a CRP value is available. CRP testing could prevent undue reliance on clinical features that poorly predict benefit from antibiotic treatment.
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