Several well-accepted classification systems are available for diabetic foot ulcers. However, there are only a few and scientifically not validated severity scores. The aim of this study was to establish a new wound-based clinical scoring system for diabetic foot ulcers suitable for daily clinical practice anticipating chances for healing and risk of amputation.RESEARCH DESIGN AND METHODS
Four clinically defined parameters, namely palpable pedal pulses, probing to bone, ulcer location, and presence of multiple ulcerations, were prospectively assessed in 1,000 consecutive patients. In the next step, a new diabetic ulcer severity score (DUSS) was created from these parameters. Palpable pedal pulses were categorized by the absence (scored as 1) or presence (scored as 0) of pedal pulses, while probing to bone was defined as yes (scored as 1) or no (scored as 0). The site of ulceration was defined as toe (scored as 0) or foot (scored as 1) ulcer. Patients with multiple ulcerations were graded as 1 compared with those with single ulcers (scored as 0). The DUSS was calculated by adding these separate gradings to a theoretical maximum of 4. Wounds were followed-up for 365 days or until healing or amputation if earlier. Probability of healing and risk of amputation were calculated by the Kaplan-Meier method.RESULTS
Uni- and multivariate analyses showed a significantly higher probability of healing for patients with palpable pulses, no probing to bone, toe ulcers, and absence of multiple ulcerations. When patients were divided into subgroups with the same DUSS, we found significantly different probabilities for healing. We showed a decreasing probability of healing for ulcers with a high DUSS, concurrent with increasing amputation rates. An increase in the DUSS by one score point reduced the chance for healing by 35%. Similarly, the higher the ulcer score, the larger the initial wound area, the longer the wound history, and the more likely the need for surgery or hospitalization.CONCLUSIONS
The DUSS categorizes different ulcers into subgroups with specific severity and similar clinical outcome. Using this score, the probabilities for healing, amputation, need for surgery, and hospitalization are predictable with high accuracy. This might be useful for the anticipation of health care costs and for comparison of subgroups of patients in clinical studies.