Abstract
was developed from this group yielded the following independent predictors of operative groin wound infection: previous groin incision, female gender, body mass index, end-stage renal disease, malnutrition, and urgent/emergency operation status. The C index of the resulting model was 0.845 and resulted in a correct classification of 88.6% of patients. Subsequent testing in the validation group (13.9% of whom sustained an operative groin wound infection) yielded an accuracy of 86.1% for our predictive model. We therefore developed a user-friendly computer program, which will be publicly accessible, that can be used to calculate an individual patient’s risk of developing operative groin wound infection after lower extremity revascularization (Fig). Conclusions: Our study is the first known attempt to develop and internally validate a statistical model that will accurately predict those patients who are likely to sustain an operative groin wound infection after lower extremity revascularization.
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