How to identify patients with the need for early liver re-transplant? Development and validation of a comprehensive model to predict Early Allograft Failure

Alfonso Wolfango Avolio, Luciana Teofili, Salvatore Agnes, Gabriele Spoletini, A Franco, A Schlegel, Q Lai, S Meli, P Burra, D Patrono, M Ravaioli, D Bassi, F Ferla, D Pagano, P Violi, S Camagni, D Dondossola, R Montalti, W Alrawashdeh, A VitaleP Magistri, P Bongini, M Rossi, V Mazzaferro, Benedetto F Di, J Hammond, M Vivarelli, M Colledan, A Carraro, M Cescon, Carlis L De, L Caccamo, S Gruttadauria, P Muiesan, U Cillo, R Romagnoli, Simone P De

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

Abstract

ABSTRACT BACKGROUND Expansion of donor acceptance criteria for liver transplantation increased the risk for early allograft failure (EAF). Though EAF prediction is pivotal to optimize transplant outcomes, there is no consensus on specific EAF indicators or timing to evaluate EAF. Recently, the Liver Graft Assessment following Transplantation (L-GrAFT) algorithm, based on aspartate transaminase, bilirubin, platelets, and INR kinetics, has been developed from a single-center database gathered from 2002 to 2015. OBJECTIVE To develop and validate a simplified comprehensive model estimating the EAF risk at day 10 after liver transplantation (the Early Allograft failure Simplified Estimation, EASE score), and, secondarily, to early identify patients with unsustainable EAF risk, suitable for re-transplant. DESIGN This multicenter study was designed to elaborate a score catching the continuum from normal graft function to non-function after transplant. We included among EAF determinants both parenchymal and vascular factors, which provide an indication to list for re-transplant. The L-GrAFT kinetic approach was adopted and modified with less data-entries and novel variables. ClinicalTrials.gov Identifier: NCT03858088. SETTING The patient population included 1,609 Italian patients in the derivation set and 570 UK patients in the validation set, all transplanted in 2016 and 2017. MAIN OUTCOME and MEASURE EAF was defined as graft failure (codified by re-transplant or death) for any reason within day 90 after transplant. RESULTS The EAF incidence was 6.8%. The EASE score was developed through 17 entries derived from 8 variables: MELD, blood transfusions, early thrombosis of hepatic vessels, kinetic parameters of transaminases, platelets and bilirubin. Donor parameters (age, DCD, machine perfusion) were not predictive. Results were adjusted for Center-volume. At ROC curve analysis, the EASE score outperformed L-GrAFT, MEAF, EAD, ET-DRI, DMELD, and DRI scores, predicting day-90 EAF in 87% of cases. Patients could be stratified in five classes, with those in the highest class exhibiting an unsustainable EAF risk. CONCLUSIONS AND RELEVANCE The EASE score reliably predicts the EAF risk. Knowledge of contributing factors may help clinicians to mitigate risk factors and guide through the challenging clinical decision to allocate patients to early liver re-transplantation. EASE may be used in translational research across transplant Centers.
Lingua originaleEnglish
pagine (da-a)N/A-N/A
Numero di pagine35
RivistaJAMA Surgery
Volume2020
Stato di pubblicazionePubblicato - 2020

Keywords

  • LIVER TRANSPLANTATION, EARLY ALLOGRAFT FAILURE, OUTCOME, RISK QUANTIFICATION
  • TRAPIANTO DI FEGATO, SOPRAVVIVENZA, QUANTIFICAZIONE DEL RISCHIO
  • li

Fingerprint Entra nei temi di ricerca di 'How to identify patients with the need for early liver re-transplant? Development and validation of a comprehensive model to predict Early Allograft Failure'. Insieme formano una fingerprint unica.

Cita questo