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

doi: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

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 rivista › Articolo

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.

Lingua originale	Inglese
pagine (da-a)	N/A-N/A
Rivista	Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Numero di pubblicazione	Gennaio
DOI	https://doi.org/10.1016/j.dld.2013.11.004
Stato di pubblicazione	Pubblicato - 2014

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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10.1016/j.dld.2013.11.004

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Angelico, M., Nardi, A., Romagnoli, R., Marianelli, T., Corradini, S., Agnes, S., Gavrila, C., Salizzoni, M., Pinna, A., Cillo, U., Gridelli, B., De Carlis, L., Colledan, M., Gerunda, G., Costa, A., & Strazzabosco, M. (2014). A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study. Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver, (Gennaio), N/A-N/A. https://doi.org/10.1016/j.dld.2013.11.004

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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.",

keywords = "Donor Risk Index, Donor-recipient match, Graft failure, Hepatitis C, Risk factors, Transplantation outcome, Donor Risk Index, Donor-recipient match, Graft failure, Hepatitis C, Risk factors, Transplantation outcome",

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

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doi = "10.1016/j.dld.2013.11.004",

language = "English",

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journal = "Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver",

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Angelico, M, Nardi, A, Romagnoli, R, Marianelli, T, Corradini, S, Agnes, S, Gavrila, C, Salizzoni, M, Pinna, A, Cillo, U, Gridelli, B, De Carlis, L, Colledan, M, Gerunda, G, Costa, A & Strazzabosco, M 2014, 'A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study', Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver, n. Gennaio, pagg. N/A-N/A. https://doi.org/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, M; Nardi, A; Romagnoli, R et al.
In: Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver, N. Gennaio, 2014, pag. N/A-N/A.

Risultato della ricerca: Contributo in rivista › Articolo

TY - JOUR

T1 - A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study

AU - Angelico, M

AU - Nardi, A

AU - Romagnoli, R

AU - Marianelli, T

AU - Corradini, Sg

AU - Agnes, Salvatore

AU - Gavrila, C

AU - Salizzoni, M

AU - Pinna, Ad

AU - Cillo, U

AU - Gridelli, B

AU - De Carlis, Lg

AU - Colledan, M

AU - Gerunda, Ge

AU - Costa, An

AU - Strazzabosco, M.

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Donor Risk Index

KW - Donor-recipient match

KW - Graft failure

KW - Hepatitis C

KW - Risk factors

KW - Transplantation outcome

KW - Donor Risk Index

KW - Donor-recipient match

KW - Graft failure

KW - Hepatitis C

KW - Risk factors

KW - Transplantation outcome

UR - https://publicatt.unicatt.it/handle/10807/51139

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DO - 10.1016/j.dld.2013.11.004

M3 - Article

SN - 1878-3562

SP - N/A-N/A

JO - Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver

JF - Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver

IS - Gennaio

ER -

Angelico M, Nardi A, Romagnoli R, Marianelli T, Corradini S, Agnes S et al. A Bayesian methodology to improve prediction of early graft loss after liver transplantation derived from the Liver Match study. Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver. 2014;(Gennaio):N/A-N/A. doi: 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

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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