PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II-Exploring the arterial side

Peripheral arterial disease (PAD) and its most severe form, critical limb ischaemia (CLI), are very common clinical conditions related to atherosclerosis and represent the major causes of morbidity, mortality, disability, and reduced quality of life (QoL), especially for the onset of ischaemic chronic leg ulcers (ICLUs) and the subsequent need of amputation in affected patients. Early identification of patients at risk of developing ICLUs may represent the best form of prevention and appropriate management. In this study, we used a Prediction System for Chronic Leg Ulcers (PredyCLU) based on fuzzy logic applied to patients with PAD. The patient population consisted of 80 patients with PAD, of which 40 patients (30 males [75%] and 10 females [25%]; mean age 66.18 years; median age 67.50 years) had ICLUs and represented the case group. Forty patients (100%) (27 males [67.50%] and 13 females [32.50%]; mean age 66.43 years; median age 66.50 years) did not have ICLUs and represented the control group. In patients of the case group, the higher was the risk calculated with the PredyCLU the more severe were the clinical manifestations recorded. In this study, the PredyCLU algorithm was retrospectively applied on a multicentre population of 80 patients with PAD. The PredyCLU algorithm provided a reliable risk score for the risk of ICLUs in patients with PAD.