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Hemicellulose biomembrane dressing versus collagenase in the treatment of chronic venous ulcers: a randomized, open, controlled clinical trial

Grant number: 15/04562-9
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): November 01, 2015
Effective date (End): October 31, 2016
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Luciana Patrícia Fernandes Abbade
Grantee:Jéssica dos Santos Jacinto
Host Institution: Faculdade de Medicina (FMB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil


Chronic venous ulcers stall in inflammatory or proliferative phase of the healing process and tend to become colonized by bacteria or fungi, causing healing delay. Dressings include cleaning and covering an injury, aiming to assist the restoration of tissue integrity and prevent colonization and infection. Among the products developed to achieve the healing goals is the line of natural materials such as biomembrane produced from cellulose and used as a temporary skin substitute in the treatment of poorly healing lesions. The objective of the study is to evaluate the efficacy and safety of bio-membrane hemicellulose in the healing of venous ulcer process. Method: A randomized, open, controlled clinical trial will be conducted with 2 groups. Group 1 will consist of patients with venous ulcers treated with hemicellulose biomembrane and compression therapy and group 2 will have patients with venous ulcers treated with collagenase dressing and compression therapy. The sample size is 35 ulcers per group. Participants will be evaluated for a period of 90 days of treatment. Statistical analysis will be performed by intention-to-treat principle and binomial variables will be compared by Chi-square (c2) and Fisher exact tests. Numerical variables will be compared by Student t test or Mann-Whitney. The longitudinal follow-up of the ulcer areas, the score of quality of life, angiogenesis and clinical findings will be compared between groups by generalized linear mixed effects model with appropriate probability distribution of each variable. Data will be analyzed using SPSS 20.0 software and will be considered significant p value < 0.05.

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