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Combining Donor Characteristics with Immunohistological Data Improves the Prediction of Islet Isolation Success
Joint Authors
Skibova, Jelena
Saudek, František
Berkova, Zuzana
Girman, Peter
Zacharovova, Klara
Kriz, Jan
Fabryova, Eva
Leontovyc, Ivan
Koblas, Tomas
Kosinova, Lucie
Neskudla, Tomas
Vavrova, Ema
Habart, David
Loukotova, Sarka
Zahradnicka, Martina
Lipar, Kvetoslav
Voska, Ludek
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-10
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Variability of pancreatic donors may significantly impact the success of islet isolation.
The aim of this study was to evaluate donor factors associated with isolation failure and to investigate whether immunohistology could contribute to organ selection.
Donor characteristics were evaluated for both successful ( n = 61 ) and failed ( n = 98 ) islet isolations.
Samples of donor pancreatic tissue ( n = 78 ) were taken for immunohistochemical examination.
Islet isolations with 250000 islet equivalents were considered successful.
We confirmed that BMI of less than 25 kg/m2 ( P < 0.001 ), cold ischemia time more than 8 hours ( P < 0.01 ), hospitalization longer than 96 hours ( P < 0.05 ), higher catecholamine doses ( P < 0.05 ), and edematous pancreases ( P < 0.01 ) all unfavorably affected isolation outcome.
Subsequent immunohistochemical examination of donor pancreases confirmed significant differences in insulin-positive areas ( P < 0.001 ).
ROC analyses then established that the insulin-positive area in the pancreas could be used to predict the likely success of islet isolation ( P < 0.001 ).
At the optimal cutoff point (>1.02%), sensitivity and specificity were 89% and 76%, respectively.
To conclude, while the insulin-positive area, determined preislet isolation, as a single variable, is sufficient to predict isolation outcome and helps to improve the success of this procedure, its combination with the established donor scoring system might further improve organ selection.
American Psychological Association (APA)
Berkova, Zuzana& Saudek, František& Girman, Peter& Zacharovova, Klara& Kriz, Jan& Fabryova, Eva…[et al.]. 2016. Combining Donor Characteristics with Immunohistological Data Improves the Prediction of Islet Isolation Success. Journal of Diabetes Research،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1108104
Modern Language Association (MLA)
Berkova, Zuzana…[et al.]. Combining Donor Characteristics with Immunohistological Data Improves the Prediction of Islet Isolation Success. Journal of Diabetes Research No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1108104
American Medical Association (AMA)
Berkova, Zuzana& Saudek, František& Girman, Peter& Zacharovova, Klara& Kriz, Jan& Fabryova, Eva…[et al.]. Combining Donor Characteristics with Immunohistological Data Improves the Prediction of Islet Isolation Success. Journal of Diabetes Research. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1108104
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1108104