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Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation

The role of the graft-to-recipient weight ratio (GRWR) in adult liver transplantation (LT) has been poorly investigated so far. The aim is to evaluate the contribution of the GRWR to the well-recognized early allograft dysfunction (EAD) model (i.e., Olthoff model) for the prediction of 90-day graft...

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Autores principales: Manzia, Tommaso Maria, Lai, Quirino, Hartog, Hermien, Aijtink, Virginia, Pellicciaro, Marco, Angelico, Roberta, Gazia, Carlo, Polak, Wojciech G., Rossi, Massimo, Tisone, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338117/
https://www.ncbi.nlm.nih.gov/pubmed/35306614
http://dx.doi.org/10.1007/s13304-022-01270-0
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author Manzia, Tommaso Maria
Lai, Quirino
Hartog, Hermien
Aijtink, Virginia
Pellicciaro, Marco
Angelico, Roberta
Gazia, Carlo
Polak, Wojciech G.
Rossi, Massimo
Tisone, Giuseppe
author_facet Manzia, Tommaso Maria
Lai, Quirino
Hartog, Hermien
Aijtink, Virginia
Pellicciaro, Marco
Angelico, Roberta
Gazia, Carlo
Polak, Wojciech G.
Rossi, Massimo
Tisone, Giuseppe
author_sort Manzia, Tommaso Maria
collection PubMed
description The role of the graft-to-recipient weight ratio (GRWR) in adult liver transplantation (LT) has been poorly investigated so far. The aim is to evaluate the contribution of the GRWR to the well-recognized early allograft dysfunction (EAD) model (i.e., Olthoff model) for the prediction of 90-day graft loss after LT in adults. Three hundred thirty-one consecutive adult patients undergoing LT between 2009 and 2018 at Tor Vergata and Sapienza University in Rome, Italy, served as the Training-Set. The Validation-Set included 123 LTs performed at the Erasmus Medical Center, Rotterdam, the Netherlands. The mEAD model for 90-day graft loss included the following variables: GRWR [Formula: see text] 1.57 = 2.5, GRWR [Formula: see text] 2.13 = 2.5, total bilirubin ≥ 10.0 mg/dL = 2.0, INR ≥ 1.60 = 2.3, and aminotransferase > 2000 IU/L = 2.2. The mEAD model showed an AUC = 0.74 (95%CI = 0.66–0.82; p < 0.001) and AUC = 0.68 (95%CI = 0.58–0.88; p = 0.01) in the Training-Set and Validation-Set, respectively, outperforming conventional EAD in both cohorts (Training-Set: AUC = 0.64, 95%CI = 0.57–0.72; p = 0.001; Validation-Set: AUC = 0.52, 95%CI = 0.35–0.69, p = 0.87). Incorporation of graft weight in a composite multivariate model allowed for better prediction of patients who presented an aminotransferase peak > 2000 IU/L after LT (OR = 2.39, 95%CI = 1.47–3.93, p = 0.0005). The GRWR is important in determining early graft loss after adult LT, and the mEAD model is a useful predictive tool in this perspective, which may assist in improving the graft allocation process.
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spelling pubmed-93381172022-07-31 Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation Manzia, Tommaso Maria Lai, Quirino Hartog, Hermien Aijtink, Virginia Pellicciaro, Marco Angelico, Roberta Gazia, Carlo Polak, Wojciech G. Rossi, Massimo Tisone, Giuseppe Updates Surg Original Article The role of the graft-to-recipient weight ratio (GRWR) in adult liver transplantation (LT) has been poorly investigated so far. The aim is to evaluate the contribution of the GRWR to the well-recognized early allograft dysfunction (EAD) model (i.e., Olthoff model) for the prediction of 90-day graft loss after LT in adults. Three hundred thirty-one consecutive adult patients undergoing LT between 2009 and 2018 at Tor Vergata and Sapienza University in Rome, Italy, served as the Training-Set. The Validation-Set included 123 LTs performed at the Erasmus Medical Center, Rotterdam, the Netherlands. The mEAD model for 90-day graft loss included the following variables: GRWR [Formula: see text] 1.57 = 2.5, GRWR [Formula: see text] 2.13 = 2.5, total bilirubin ≥ 10.0 mg/dL = 2.0, INR ≥ 1.60 = 2.3, and aminotransferase > 2000 IU/L = 2.2. The mEAD model showed an AUC = 0.74 (95%CI = 0.66–0.82; p < 0.001) and AUC = 0.68 (95%CI = 0.58–0.88; p = 0.01) in the Training-Set and Validation-Set, respectively, outperforming conventional EAD in both cohorts (Training-Set: AUC = 0.64, 95%CI = 0.57–0.72; p = 0.001; Validation-Set: AUC = 0.52, 95%CI = 0.35–0.69, p = 0.87). Incorporation of graft weight in a composite multivariate model allowed for better prediction of patients who presented an aminotransferase peak > 2000 IU/L after LT (OR = 2.39, 95%CI = 1.47–3.93, p = 0.0005). The GRWR is important in determining early graft loss after adult LT, and the mEAD model is a useful predictive tool in this perspective, which may assist in improving the graft allocation process. Springer International Publishing 2022-03-19 2022 /pmc/articles/PMC9338117/ /pubmed/35306614 http://dx.doi.org/10.1007/s13304-022-01270-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Manzia, Tommaso Maria
Lai, Quirino
Hartog, Hermien
Aijtink, Virginia
Pellicciaro, Marco
Angelico, Roberta
Gazia, Carlo
Polak, Wojciech G.
Rossi, Massimo
Tisone, Giuseppe
Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title_full Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title_fullStr Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title_full_unstemmed Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title_short Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
title_sort graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338117/
https://www.ncbi.nlm.nih.gov/pubmed/35306614
http://dx.doi.org/10.1007/s13304-022-01270-0
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