Predictive model of short-term amputation during hospitalization of patients due to acute diabetic foot infections.

INTRODUCTION Factors predicting short-term amputation during hospital treatment of patients admitted for acute diabetic foot infections are of interest for clinicians managing the acute episode. METHODS A retrospective clinical records analysis of 78 consecutive patients hospitalized for acute diabetic foot infections was performed to identify predictive factors for short-term amputation by comparing the data of patients who ultimately required amputation and those who did not. Clinical/epidemiological, laboratory, imaging, and treatment variables were comparatively analyzed. A logistic regression model was performed, with amputation as the dependent variable and factors showing significant differences in the bivariate analysis as independent variables. A prediction score was calculated (and validated by ROC curve analysis) using beta coefficients for significant variables in the regression analysis to predict amputation. RESULTS Of the 78 patients (70.5% with peripheral vasculopathy) included, 26 ultimately required amputation. In the bivariate analysis, white blood cell count, previous homolateral lesions, odor, lesion depth, sedimentation rate, Wagner ulcer grade, and arterial obstruction on Doppler study were significantly higher in patients ending in amputation. In the multivariate analysis, the risk of amputation was increased only by Wagner grade 4 or 5 (20-fold higher), obstruction (12.5-fold higher), and elevated sedimentation rate (6% higher per unit). Logistic regression predicted outcome in 76.9% of patients who underwent amputation and 92.3% of those who did not. CONCLUSION The score calculated using beta coefficients for significant variables in the regression model (Wagner grades 4 and 5, obstruction on Doppler, and elevated sedimentation rate for the clinical, imaging, and laboratory data, respectively) correctly predicted amputation during hospital management of acute diabetic foot infections.