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

Tommaso Maria Manzia, Quirino Lai*, Hermien Hartog, Virginia Aijtink, Marco Pellicciaro, Roberta Angelico, Carlo Gazia, Wojciech G. Polak, Massimo Rossi, Giuseppe Tisone

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
4 Downloads (Pure)

Abstract

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 ≤ 1.57 = 2.5, GRWR ≥ 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.

Original languageEnglish
Pages (from-to)1307-1316
Number of pages10
JournalUpdates in Surgery
Volume74
Issue number4
DOIs
Publication statusPublished - Aug 2022

Bibliographical note

Funding
Open access funding provided by Alma Mater Studiorum - Università di Bologna within the CRUI-CARE Agreement.

Publisher Copyright: © 2022, The Author(s).

Fingerprint

Dive into the research topics of 'Graft weight integration in the early allograft dysfunction formula improves the prediction of early graft loss after liver transplantation'. Together they form a unique fingerprint.

Cite this