PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II—Exploring the arterial side
Autor: | Alessandro Gallo, Pasquale Mastroroberto, Umberto Bracale, Davide Turchino, Nicola Ielapi, Raffaele Serra, Salvatore Fregola, Noemi Licastro, Stefano de Franciscis, Andrea Barbetta, Vincenzo Gasbarro |
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Přispěvatelé: | Serra, Raffaele, Bracale, Umberto M, Barbetta, Andrea, Ielapi, Nicola, Licastro, Noemi, Gallo, Alessandro, Fregola, Salvatore, Turchino, Davide, Gasbarro, Vincenzo, Mastroroberto, Pasquale, de Franciscis, Stefano |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Male
medicine.medical_specialty chronic leg ulcer Population Dermatology Fuzzy logic Risk Assessment 030207 dermatology & venereal diseases 03 medical and health sciences Peripheral Arterial Disease 0302 clinical medicine Fuzzy Logic Predictive Value of Tests amputation Severity of illness medicine Humans 030212 general & internal medicine Risk factor Intensive care medicine education critical limb ischaemia fuzzy logic peripheral arterial disease Aged Retrospective Studies education.field_of_study Framingham Risk Score business.industry Leg Ulcer Case-control study Retrospective cohort study Original Articles Surgery body regions Tibial Arteries Early Diagnosis Italy Chronic Disease Female Risk assessment business Algorithms |
Zdroj: | Int Wound J |
Popis: | 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. |
Databáze: | OpenAIRE |
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