Prediction of diabetic foot ulceration: The value of using microclimate sensor arrays - Petra Jones; Richard Bibb; Melanie Davies; Kamlesh Khunti; Matthew McCarthy; David Webb; Francesco Zaccardi (2019)
Background: Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure or shear rather than the overall foot microclimate. Method: A systematic review was conducted by searching PubMed reports with no restrictions on start date covering literature published until 20 February 2019 using relevant keywords, including temperature, pressure, shear and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. Results: Current prognostic models rely either solely on contralateral temperature, pressure or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Conclusions: Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time inshoe data collection and wireless transmission, providing a potentially rich source of data to better predict risk of DFU.