Is in-Shoe Microclimate a Neglected Contributor in the Pathway to Diabetic Foot Ulceration?

The identification of the key contributing factors which predispose the foot to ulceration, increasing the risk of recurrence and slow wound healing in diabetes mellitus (DM), has led to some significant research studies over the last 30 years, providing valuable insight into the mechanism leading to diabetic foot ulceration (DFU). Although, these contributory factors are similar to those identified in pressure ulceration occurring in other parts of the body (such as "bed pressure sores') where magnitude and/or duration of mechanical stress in the presence of sensory deficits are key causal factors, research investigating pressure ulceration has also included measurement of temperature and relative humidity at the interface between the skin and supporting surface. The possible influence of these parameters (in-shoe temperature and humidity) does not appear frequently in diabetic foot ulceration research. Referred to as "microclimate", this has an important role in the pathway to tissue breakdown evidenced in pressure ulcer research and may be particularly relevant in countries with warm and humid climates. As the microclimate is influential in the ulceration pathway for other body sites, its role in the DFU causal pathway justifies further investigation.

A Novel Method to Determine Dynamic Temperature Trends Applied to In-Shoe Temperature Data During Walking.

Body temperature is one of the fundamental measures considered in the assessment of health and well-being, with various medical conditions known to give rise to abnormal changes in temperature. In particular, abnormal variations in dynamic temperature patterns during walking or exercise may be linked to a range of foot problems, which are of particular concern in diabetic patients.A number of studies have investigated normative temperature patterns of a population by considering data from multiple participants and averaging results after an acclimatisation interval. In this work we demonstrate that the temperature patterns obtained using such an approach may not be truly representative of temperature changes in a population, and the averaging process adopted may yield skewed results.An alternative approach to determine generic reference temperature patterns based on a minimization of root mean square differences between time-shifted versions of temperature data collected from multiple participants is proposed. The results obtained indicate that this approach can yield a general trend that is more representative of actual temperature changes across a population than conventional averaging methods. The method we propose is also shown to better capture and link the effects of factors that influence dynamic temperature trends, which could in turn lead to a better understanding of underlying physiological phenomena.