Risk prediction models for diabetic foot ulcer development or amputation: a review of reviews

In adults with diabetes, diabetic foot ulcer (DFU) and amputation are common and associated with significant morbidity and mortality.

Identify tools predicting risk of DFU or amputation that are prognostically accurate and clinically feasible.

We searched for systematic reviews (SRs) of tools predicting DFU or amputation published in multiple databases from initiation to January, 2023. We assessed risk of bias (ROB) and provided a narrative review of reviews describing performance characteristics (calibration and discrimination) of prognostically accurate tools. For such tools, we additionally reviewed original studies to ascertain clinical applicability and usability (variables included, score calculation, and risk categorization).

We identified 3 eligible SRs predicting DFU or amputation risk. Two recent SRs (2020 and 2021) were rated as moderate and low ROB respectively. Four risk prediction models - Boyko, Martins-Mendes (simplified), Martins-Mendes (original), and PODUS 2020 had good prognostic accuracy for predicting DFU or amputation over time horizons ranging from 1- to 5-years. PODUS 2020 predicts absolute average risk (e.g., 6% risk of DFU at 2 years) and consists of 3-binary variables with a simple, summative scoring (0-4) making it feasible for clinic use. The other 3 models categorize risk subjectively (e.g., high-risk for DFU at 3 years), include 2-7 variables, and require a calculation device. No data exist to inform rescreening intervals. Furthermore, the effectiveness of targeted interventions in decreasing incidence of DFU or amputation in response to prediction scores is unknown.

In this review of reviews, we identified 4 prognostically accurate models that predict DFU or amputation in persons with diabetes. The PODUS 2020 model, predicting absolute average DFU risk at 2 years, has the most favorable prognostic accuracy and is clinically feasible. Rescreening intervals and effectiveness of intervention based on prediction score are uncertain.