An Evaluation of Real-world Smart Sock–Based Temperature Monitoring Data as a Physiological Indicator of Early Diabetic Foot Injury: Case-Control Study

Abstract

BackgroundLower extremity complications of diabetes represent major health care complications both in terms of cost and impact to quality of life for patients with diabetic peripheral neuropathy. Temperature monitoring has been shown in previous studies to provide a useful signal of inflammation that may indicate the early presence of a foot injury. ObjectiveIn this study, we evaluated the temperature data for patients that presented with a diabetic foot injury while using a sock-based remote temperature monitoring device. MethodsThe study abstracted data from patients who were enrolled in a remote temperature monitoring program (2020-2021) using a smart sock (Siren Care). In the study cohort, a total of 5 participants with a diabetes-related lower extremity injury during the study period were identified. In the second comparison cohort, a total of 26 patients met the criteria for monitoring by the same methods but did not present with a diabetes-related podiatric lower extremity injury during the same period. The 15-day temperature differential between 6 defined locations on each foot was the primary outcome measure among subjects who presented with a diagnosed foot injury. Paired t tests were used to compare the differences between the two groups. ResultsA significant difference in temperature differential (temperature measured in °F) was observed in the group that presented with a podiatric injury over the course of evaluation versus the comparator group that did not present with a podiatric injury. The average difference from all 6 measured points was 1.4 °F between the injury group (mean 3.6, SD 3.0) and the comparator group (mean 2.2, SD 2.5, t=–71.4, df=39; P<.001). ConclusionsThe results of this study suggest temperature monitoring in a sock form factor could be used to predict a developing foot injury. The continuous temperature monitoring system employed has implications for further algorithm development to enable early detection. The study was limited by a nonrandomized, observational design with limited injuries present in the study period. We look forward to further studies that will refine the predictive potential and confirm or refute the current promising data.