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.

Angelico, M., Nardi, A., Romagnoli, R., Marianelli, T., Corradini, S., Tandoi, F., et al. (2014). A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study. DIGESTIVE AND LIVER DISEASE, 46(4), 340-347 [10.1016/j.dld.2013.11.004].

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

ANGELICO, MARIO;NARDI, ALESSANDRA;
2014-01-09

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.
9-gen-2014
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore MED/12 - GASTROENTEROLOGIA
English
Con Impact Factor ISI
Graft failure; Donor-recipient match; Risk factors; Transplantation outcome; Hepatitis C; Donor Risk Index
Angelico, M., Nardi, A., Romagnoli, R., Marianelli, T., Corradini, S., Tandoi, F., et al. (2014). A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study. DIGESTIVE AND LIVER DISEASE, 46(4), 340-347 [10.1016/j.dld.2013.11.004].
Angelico, M; Nardi, A; Romagnoli, R; Marianelli, T; Corradini, S; Tandoi, F; Gavrila, C; Salizzoni, M; Pinna, A; Cillo, U; Gridelli, B; De Carlis, L; ...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/83651
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