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

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 [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.

Keywords: Early allograft dysfunction; Graft loss; Graft weight; Liver transplantation.

Conflict of interest statement

None.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Evaluation and comparison of the m-EAD and EAD predicting models on 90-day graft loss [Training-SET (A) and Validation-SET (B)]
Fig. 2
Fig. 2
Relative risk of 90-day graft loss according to the GRWR. The histograms represent the Training-Set population distribution according to the GRWR (reported on the right y-axis). The left y-axis shows the 90-day graft loss incidence (%). The line represents the relative risk (RR) of 90-day graft loss according to the GRWR. The GRWR RR = 1 represents the reference (median GRWR value = 1.9); the “red zone” represents the increase in the RR of 90-day graft loss when the GRWR > 2.0. Contrarily, the “green zone” represents the decrease in the risk (from GRWR = 1.57 to GRWR = 2.0). The RR curve remains stable (RR ∼ 5) when GRWR < 1.6 (yellow zone)
Fig. 3
Fig. 3
Relative risk of 90-day graft loss according to the mEAD. The histograms represent the Training-Set population distribution according to the mEAD (reported on the right y-axis). The left y-axis shows the 90-day graft loss incidence (%). The line represents the relative risk (RR) of 90-day graft loss according to the mEAD. The mEAD RR = 1 represents the reference. (median mEAD value = 4.3)

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Source: PubMed

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