External validation of the Meggitt-Wagner, Texas University, SINBAD, and Saint Elian classifications for predicting major amputation in patients with diabetes at a public hospital in Peru

Abstract

Objective To externally validate and compare the prognostic performance of four diabetic foot ulcer classifications—Meggitt-Wagner, University of Texas, SINBAD, and Saint Elian— for predicting major amputation in patients with diabetes treated at a public hospital in Peru. Materials and methods We conducted a retrospective cohort study at María Auxiliadora Hospital, one of the few referral centers in Lima with a specialized Diabetic Foot Unit. The study period was January 2015 to December 2019. Eligible patients had a lower-limb ulcer, complete clinical data recorded within 48 hours of the index healthcare encounter (hospital admission or outpatient evaluation), and at least six months of follow-up. Patients with venous ulcers or pressure ulcers related to immobilization were excluded. The primary outcome was major amputation, defined as any procedure above the ankle. Prognostic performance of the four systems was assessed using the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, predictive values, and the Youden index Results A total of 342 patients were included. All had type 2 diabetes mellitus, median age was 62 years (IQR 54–69), and 229 (67.0%) were male. The six-month cumulative incidence of major amputation was 11%. The AUROC values were: Saint Elian, 0.90; University of Texas (3D stage), 0.81; Meggitt-Wagner, 0.81; and SINBAD, 0.74. The most discriminative thresholds were SE ≥ 18, TU stage 3D, MW ≥ 3, and SINBAD ≥5. Patients with SE > 20 had a 32-fold higher risk of amputation compared with those with SE < 16. Conclusion The Saint Elian and University of Texas systems showed the best prognostic accuracy, while Meggitt-Wagner and SINBAD performed moderately. These findings provide clinicians with clear cut-off points to identify high-risk patients and support early interventions in referral settings. Their effective use depends on multidisciplinary teams trained in diabetic foot management, and selecting the classification system most suited to hospital resources and patient profiles may help reduce amputation rates.