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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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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. |
format | Online Article Text |
id | pubmed-9338117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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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