The Society for Vascular Surgery lower extremity threatened limb classification system based on Wound, Ischemia, and foot Infection (WIfI) correlates with risk of major amputation and time to wound healing

Objective: The purpose of this study was to evaluate whether the new Society for Vascular Surgery (SVS) Wound, Ischemia, and foot Infection (WIfI) classification system correlates with important clinical outcomes for limb salvage and wound healing. Methods: A total of 201 consecutive patients with threatened limbs treated from 2010 to 2011 in an academic medical center were analyzed. These patients were stratified into clinical stages 1 to 4 on the basis of the SVS WIfI classification. The SVS objective performance goals of major amputation, 1-year amputation-free survival (AFS) rate, and wound healing time (WHT) according to WIfI clinical stages were compared. Results: The mean age was 58 years (79% male, 93% with diabetes). Forty-two patients required major amputation (21%); 159 (78%) had limb salvage. The amputation group had a significantly higher prevalence of advanced stage 4 patients (P < .001), whereas the limb salvage group presented predominantly as stages 1 to 3. Patients in clinical stages 3 and 4 had a significantly higher incidence of amputation (P < .001), decreased AFS (P < .001), and delayed WHT (P < .002) compared with those in stages 1 and 2. Among patients presenting with stage 3, primarily as a result of wound and ischemia grades, revascularization resulted in accelerated WHT (P = .008). Conclusions: These data support the underlying concept of the SVS WIfI, that an appropriate classification system correlates with important clinical outcomes for limb salvage and wound healing. As the clinical stage progresses, the risk of major amputation increases, 1-year AFS declines, and WHT is prolonged. We further demonstrated benefit of revascularization to improve WHT in selected patients, especially those in stage 3. Future efforts are warranted to incorporate the SVS WIfI classification into clinical decision-making algorithms in conjunction with a comorbidity index and anatomic classification.