Risk Factors for Developing Peak Plantar Pressure During Walking in the Diabetic Patients

Diabetes is one of the top three chronic diseases among the population, with type 2 diabetes accounting for 90% of all cases. Due to decreased insulin sensitivity, the body cannot effectively store glucose in muscle, fat, and liver cells, leading to elevated blood sugar levels. This condition often results in various comorbidities and complications, with diabetic peripheral neuropathy (DPN) being the most prominent. DPN symptoms include loss of sensation to pain, pressure, vibration, proprioception, and temperature changes, which can lead to foot ulcers and altered gait in patients. The primary risk factor for diabetic foot ulcers is excessive or concentrated plantar pressure. Currently, the main preventive measure for diabetic foot ulcers is the use of insoles or footwear to reduce foot pressure. However, the difficulty in obtaining plantar pressure monitoring equipment limits its widespread clinical use. In contrast, assessments of foot morphology and range of motion (ROM), as well as the application of new sensors for gait kinematic measurement, are relatively convenient for clinical use. Therefore, this study aims to establish the relationship between peak plantar pressure during walking in diabetic patients and clinically convenient dynamic and static measurement parameters, identify related risk factors, and develop a predictive model to estimate the likelihood of excessive plantar pressure.

The study plans to recruit 120 diabetic patients, using the NDS scale to measure participants' neuropathy disability levels, Von Frey monofilaments to assess plantar sensation, goniometers to record joint angles of the first metatarsophalangeal joint, ankle, and knee, graph paper to record foot shape, RehaGait(R) gait analysis system to record walking kinematics, and Noraxon(R) Ultium Insole to record plantar pressure values. Subsequently, correlation analysis will be used to identify the relationship between joint angles, foot shape, walking kinematics, and peak plantar pressure values, while chi-square tests will identify significant risk factors. Finally, multiple regression analysis will be employed to develop a predictive model, aiming to provide potential improvement strategies for preventing diabetic foot ulcers in the future.