|Authors||Bennett KM, Levinson H, Scarborough JE, Shortell CK|
|Journal||J. Vasc. Surg. Volume: 63 Issue: 2 Pages: 414-9|
|Publish Date||2016 Feb|
Groin wound infection is a costly and morbid event after lower extremity revascularization. To date, a comprehensive and validated method for identifying patients who are at greatest risk for this complication has yet to be developed.Our retrospective analysis included all patients at a single institution who underwent lower extremity revascularization using a groin incision from 2009 through 2012. Patients were randomly assigned to one of two groups: a test group, which was used to develop a predictive model for our primary outcome; and a validation group, which was used to test that model. The primary outcome for our analysis was severe groin wound infection, which we defined as postoperative groin infection that required operative intervention. Multimodel inference methods were used to evaluate all possible combinations, interactions, and transformations of potential predictor variables from the test group of patients. The resulting model that exhibited the lowest Akaike information criterion was then selected for testing with the validation group of patients.A total of 284 patients who underwent lower extremity revascularization procedures were included in our study (140 in the test group, 144 in the validation group). In the test group, 17 patients (12.1%) developed severe groin wound infection requiring operative intervention. The best-fit predictive model developed from this group identified the following independent risk factors for severe groin wound infection: prior ipsilateral groin incision, female gender, body mass index, end-stage renal disease, malnutrition, and urgent or emergency procedure status. The correct classification rate of this model in the test group was 88.6%. The incidence of severe groin wound infection in the validation group was 13.9%, and application of our predictive model to this group yielded a correct classification rate of 86.1%.We have developed and validated a statistical model that accurately predicts those patients who are likely to sustain severe groin wound infection after lower extremity revascularization.