A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study

M Angelico, A Nardi, R Romagnoli*, T Marianelli, Sg Corradini, Salvatore Agnes, C Gavrila, M Salizzoni, Ad Pinna, U Cillo, B Gridelli, Lg De Carlis, M Colledan, Ge Gerunda, An Costa, M. Strazzabosco

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo

11 Citazioni (Scopus)

Abstract

To generate a robust predictive model of Early (3 months) Graft Loss after liver transplantation, we used a Bayesian approach to combine evidence from a prospective European cohort (Liver-Match) and the United Network for Organ Sharing registry.

All Science Journal Classification (ASJC) codes

  • Epatologia
  • Gastroenterologia

Keywords

  • Donor Risk Index
  • Donor-recipient match
  • Graft failure
  • Hepatitis C
  • Risk factors
  • Transplantation outcome

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