PredyCLU: a prediction system for chronic leg ulcers based on fuzzy logic; part I – exploring the venous side

Abstract

Chronic leg ulcers (CLUs) are a common occurrence in the western population and are associated with a negative impact on the quality of life of patients. They also cause a substantial burden on the health budget. The pathogenesis of leg ulceration is quite heterogeneous, and chronic venous ulceration (CVU) is the most common manifestation representing the main complication of chronic venous disease (CVD). Prevention strategies and early identification of the risk represent the best form of management. Fuzzy logic is a flexible mathematical system that has proved to be a powerful tool for decision‐making systems and pattern classification systems in medicine. In this study, we have elaborated a computerised prediction system for chronic leg ulcers (PredyCLU) based on fuzzy logic, which was retrospectively applied on a multicentre population of 77 patients with CVD. This evaluation system produced reliable risk score patterns and served effectively as a stratification risk tool in patients with CVD who were at the risk of developing CVUs.