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Clinical prediction rules for surgical site infection after minor surgery in general practice
1MBChB, DRANZCOG, DipGUMed, SM Epi, FRACGP, MPHTM, PhD, General Practitioner; Promotional Chair, Discipline of General Practice, Mackay Clinical School, College of Medicine and Dentistry, James Cook University, Mackay, Qld.
Background And Objectives:
Surgical site infection (SSI) after dermatological surgery is associated with poor outcomes. Developing clinical prediction rules based on the predicted probability of infection might encourage guided prophylaxis and judicious prescribing. The purpose of this study was to develop a clinical prediction rule based on identified risk factors for SSI in a large general practice patient cohort.
Method:
We examined a large, pooled dataset from four randomised controlled trials performed in a regional centre of North Queensland, Australia. Multivariable logistic regression identified a prediction model. Bootstrapping was used for internal validation. A scoring system was based on predicted probabilities of infection.
Results:
The final prediction rule included age >55 years and the anatomical site, histology and complexity of the excision. The area under the curve was 0.704.
Discussion:
Our prediction rule encourages judicious use of prophylaxis in clinical practice.
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