New horizons in the understanding of the causes and management of diabetic foot disease: report from the 2017 Diabetes UK Annual Professional Conference Symposium

Diabetes-related foot disease remains a common problem. For wounds, classic teaching recommends the treatment of any infection, offloading the wound and ensuring a good blood supply, as well as ensuring that the other modifiable risk factors are addressed and optimized. There remain, however, several questions about these and other aspects of the care of diabetes-related foot disease. Some of these questions are addressed in the present report; in particular, the impact of newer technologies in the identification of any organisms present in a wound, as well as the use of novel approaches to treat infections. The use of new remote sensing technology to identify people at risk of developing foot ulceration is also considered, in an attempt to allow early intervention and prevention of foot ulcers. The psychological impact of foot disease is often overlooked, but with an increasing number of publications on the subject, the cause-and-effect role that psychology plays in foot disease, such as ulcers and Charcot neuroarthropathy, is considered. Finally, because of heterogeneity in diabetic foot studies, comparing results is difficult. A recently published document focusing on ensuring a standardized way of reporting foot disease trials is discussed

Assessing diabetic foot ulcer development risk with hyperspectral tissue oximetry

Foot ulceration remains a serious health concern for diabetic patients and has a major impact on the cost of diabetes treatment. Early detection and preventive care, such as offloading or improved hygiene, can greatly reduce the risk of further complications. We aim to assess the use of hyperspectral tissue oximetry in predicting the risk of diabetic foot ulcer formation. Tissue oximetry measurements are performed during several visits with hyperspectral imaging of the feet in type 1 and 2 diabetes mellitus subjects that are at risk for foot ulceration. The data are retrospectively analyzed at 21 sites that ulcerated during the course of our study and an ulceration prediction index is developed. Then, an image processing algorithm based on this index is implemented. This algorithm is able to predict tissue at risk of ulceration with a sensitivity and specificity of 95 and 80%, respectively, for images taken, on average, 58 days before tissue damage is apparent to the naked eye. Receiver operating characteristic analysis is also performed to give a range of sensitivity∕specificity values resulting in a Q-value of 89%