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Islets ; 3(6): 352-7, 2011.
Article in English | MEDLINE | ID: mdl-21983190

ABSTRACT

BACKGROUND: Many studies have evaluated whether there are characteristics related to pancreas donors and the islet isolation process that can influence pancreatic islet yield. However, this analysis has not yet been performed in Brazil, one of the world leaders in whole pancreas organ transplantation (WOPT), where pancreas allocation for pancreatic islet transplantation (PIT) has no officially defined criteria. Definition of parameters that would predict the outcome of islet isolation from local pancreas donors would be useful for defining allocation priority in Brazil. OBJECTIVE: To analyze the relationship between multiple donor-related and islet isolation variables with the total number of isolated pancreatic islet equivalents (IEQ) in a brazilian sample of pancreas donors. METHODS: Several variables were analyzed in 74 pancreata relative to the outcome of total IEQs obtained at the end of the process. RESULTS: In univariate analysis, body mass index (BMI) (p = 0.003), the presence of fatty infiltrates in the pancreas as observed during harvesting (p = 0.042) and pancreas digestion time (p = 0.046) were identified as variables related to a greater IEQ yield. In a multivariate analysis a statistically significant contribution to the variability of islet yield was found only for the BMI (p = 0.017). A ROC curve defined a BMI = 30 as a cut-off point, with pancreata from donors with BMI > 30 yielding more islets than donors with BMI < 30 (p< 0.001). CONCLUSION: These data reinforce the importance of the donor BMI as a defining parameter for successful islet isolation and establishes this variable as a potential pancreas allocation criterion in Brazil, where there is unequal competition for good quality organs between WOPT and PIT.


Subject(s)
Islets of Langerhans Transplantation/methods , Pancreas Transplantation/methods , Tissue and Organ Procurement/methods , Adult , Body Mass Index , Brazil , Female , Humans , Male , Middle Aged , Predictive Value of Tests , ROC Curve , Sensitivity and Specificity , Statistics, Nonparametric
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