Lower limb amputation is a devastating and preventable complication of diabetes. As the diabetes burden increases worldwide, care for affected individuals remains limited in Peru in terms of diagnosis, access to care, and complication management. Diabetic foot ulcers (DFUs) can be prevented with timely identification. There is an urgent need to implement a cost-effective and feasible strategy to reduce the morbidity associated with DFUs, and technology plays a key role in DFU prevention.

Considering the above, the development of an artificial intelligence application to promptly identify risk lesions (such as cracks, redness, calluses, edema, erythema) using photos taken with a mobile phone could improve the care and self-management of diabetic patients, with an emphasis on the early recognition of lesions that could potentially lead to diabetic foot ulcers and prevent additional complications.

Aim:

Evaluate innovative approaches for the prevention of diabetic foot ulcers and assess their implementability.

Study design:

The project has three phases that will be developed over 3 years:

1. Development of an Artificial Intelligence algorithm for the detection of pre-ulcers.
2. Co-design of an application called «foot selfie» for taking photos of the feet with the aim of preventing ulceration in people with diabetes.
3. Pilot study to assess the implementation of the «foot selfie».

During the life of the project, we will liaise closely with stakeholders and decision-makers at the national level in order to prepare plans for the future scale-up of interventions.

Result:

Ongoing project.

Contact:

María Lazo Porras, MD, MSc, PhD

maria.lazo@upch.pe