Periodic Reporting for period 1 - DIALECT (Diabetes Lower Extremity Complications Research and Training Network in Foot Ulcer and Amputation Prevention)
Reporting period: 2022-10-01 to 2024-09-30
DIALECT focusses on five key objectives (within 3 research work packages) to improve treatment in ulcer and amputation prevention, taking a personalised treatment approach;
1. Establish a new risk stratification model to stratify patients at high risk for diabetic foot disease and to guide personalised medicine in foot ulcer and amputation prevention (Model)
2. Conduct beyond state-of-the-art biomechanical analyses to formulate new hypotheses on specific diabetic foot conditions and pave the way for personalised medicine in ulcer prevention (Model)
3. Establish beyond state-of-the-art physical activity and treatment adherence profiles using artificial intelligence to formulate new hypotheses on patient behaviour in diabetic foot disease (Measure)
4. Develop technologically advanced sensor system products for laboratory measurements and personalised at-home monitoring of foot(wear) biomechanics, activity, and adherence in diabetic foot disease (Measure, Make)
5. Make and validate beyond state-of-the-art personalised footwear using machine learning applications to improve biomechanical, activity, and adherence outcomes in foot ulcer and amputation prevention (Make)
The results of the DIALECT program will improve the personalized treatment approach for people with diabetes who are at moderate to high risk of developing foot disease. People with the disease will be better classified according to their risk of ulceration, we will better understand particular pathologies of the diabetic foot, we will be able to better monitor people for relevant biomechanical outcomes and we will deliver footwear that will better fit the patients foot and distribute pressure on the foot. With this personalised more data-driven approach to ulcer and amputation prevention a large impact is expected in reducing the patient and society burden of diabetic foot disease.
- Full description of research goals and projects for the full appointment period of the 11 DCs, after multiple and intensive discussions within the research teams and within the supervisory and science and technology boards.
- Report on incidence of diabetic foot complications in diabetes type 1 and type 2 individuals in a large Danish cohort
- Report through a systematic scoping review to identify and map existing research on psychological and emotional wellbeing of people living with diabetic foot disease
- Identification of risk factors for Charcot neuro-osteoarthropathy and predictive outcomes based on a retrospective population study.
- Report on Quantifying Mechanical and Morphological Properties of Plantar Foot Soft Tissues: A Systematic Review of Methods and their clinimetric properties
- Report on daily physical activity behaviour of individuals with type 2 diabetes and impaired vibration perception as marker of peripheral neuropathy
- Hardware and software parts developed for sensor system for wearable technology for long term pressure, adherence and activity monitoring
- Preliminary hardware and software work conducted for benchmark testing of a new shear force sensor to be used inside the shoe
- Report based on a review of the literature on transition state offloading modalities for people with diabetes who have just recovered from a foot ulcer and are at risk of re-ulceration
- Prototype model of a modular footwear setup to be used for experimental testing of midsole/outsole geometries and materials on relevant foot biomechanical parameters to be used to develop transition and preventative footwear for moderate to high risk people with diabetes
- Report on knowledge gaps in footwear design components in relation to biomechanical and user-related outcomes for individuals at moderate to high-risk of diabetes-related foot ulceration
- Identification of novel concepts and methods to offload pressure from at-risk sites of the foot in diabetes and to personalise prototype insoles using individual foot shape and pressure data.