Literature DB >> 19210688

MELD and other predictors of survival after liver transplantation.

Ajacio Brandão1, Sandra C Fuchs, Ana L Gleisner, C Marroni, Maria L Zanotelli, Guido Cantisani.   

Abstract

BACKGROUND: This study examined how reliable is the pre-transplant model for end-stage liver disease (MELD) score in predicting post-transplantation survival and analyzed variables associated with patient survival.
METHODS: A cohort study was conducted. Receiver operating characteristic curve c-statistics were used to determine the ability of MELD score to predict mortality. The Kaplan-Meier (KM) method was used to analyze survival as a function of time regarding the MELD score and Child-Turcotte-Pugh (CTP) category. The Cox model was employed to assess the association between baseline risk factors and mortality.
RESULTS: Recipients and donors were mostly male, with a mean age of 51.6 and 38.5 yr, respectively (n = 436 transplants). The c-statistic values for three-month patient mortality were 0.60 and 0.61 for MELD score and CTP category, respectively. KM survival at three, six and 12 months were lower in those who had a MELD score > or =21 or were CTP category C. Multivariate analysis revealed that recipient age > or =65 yr, MELD > or = 21, CTP C category, bilirubin > or = 7 mg/dL, creatinine > or = 1.5 mg/dL, platelet transfusion, hepatocellular carcinoma, and non-white color donor skin were predictors of mortality.
CONCLUSIONS: Severe pre-transplant liver disease, age > or = 65, non-white skin donor, and hepatocellular carcinoma are associated with poor outcome.

Entities:  

Mesh:

Year:  2009        PMID: 19210688     DOI: 10.1111/j.1399-0012.2008.00943.x

Source DB:  PubMed          Journal:  Clin Transplant        ISSN: 0902-0063            Impact factor:   2.863


  12 in total

1.  Pre-transplant MELD and sodium MELD scores are poor predictors of graft failure and mortality after liver transplantation.

Authors:  Jacek B Cywinski; Edward J Mascha; Jing You; Daniel I Sessler; Leonardo Kapural; Maged Argalious; Brian M Parker
Journal:  Hepatol Int       Date:  2011-02-17       Impact factor: 6.047

2.  Living Donor Liver Transplantation in South Asia: Single Center Experience on Intermediate-Term Outcomes.

Authors:  Faisal S Dar; Abu Bakar H Bhatti; Ammal I Qureshi; Nusrat Y Khan; Zahaan Eswani; Haseeb H Zia; Eitzaz U Khan; Nasir A Khan; Atif Rana; Najmul H Shah; Mohammad Salih; Rashid Nazer
Journal:  World J Surg       Date:  2018-04       Impact factor: 3.352

3.  Living donor liver transplantation for high model for end-stage liver disease score: What have we learned?

Authors:  Hany Dabbous; Mohammad Sakr; Sara Abdelhakam; Iman Montasser; Mohamed Bahaa; Hany Said; Mahmoud El-Meteini
Journal:  World J Hepatol       Date:  2016-08-08

4.  Albumin-Bilirubin Score: Predicting Short-Term Outcomes Including Bile Leak and Post-hepatectomy Liver Failure Following Hepatic Resection.

Authors:  Nikolaos Andreatos; Neda Amini; Faiz Gani; Georgios A Margonis; Kazunari Sasaki; Vanessa M Thompson; David J Bentrem; Bruce L Hall; Henry A Pitt; Ana Wilson; Timothy M Pawlik
Journal:  J Gastrointest Surg       Date:  2016-09-12       Impact factor: 3.452

5.  The MELD score predicts the short-term and overall survival after liver transplantation in patients with primary sclerosing cholangitis or autoimmune liver diseases.

Authors:  Katrin Hoffmann; Ulf Hinz; Norbert Hillebrand; Tom Ganten; Daniel Gotthardt; Thomas Longerich; Peter Schirmacher; Peter Schemmer
Journal:  Langenbecks Arch Surg       Date:  2014-08-09       Impact factor: 3.445

6.  Impact of MELD allocation policy on survival outcomes after liver transplantation: a single-center study in northeast Brazil.

Authors:  Thales Paulo Batista; Bernardo David Sabat; Paulo Sérgio V Melo; Luiz Eduardo C Miranda; Olival Cirilo L Fonseca-Neto; Américo Gusmão Amorim; Cláudio Moura Lacerda
Journal:  Clinics (Sao Paulo)       Date:  2011       Impact factor: 2.365

7.  Model for End-Stage Liver Disease, Model for Liver Transplantation Survival and Donor Risk Index as predictive models of survival after liver transplantation in 1,006 patients.

Authors:  Elisa Maria de Camargo Aranzana; Adriana Zuolo Coppini; Maurício Alves Ribeiro; Paulo Celso Bosco Massarollo; Luiz Arnaldo Szutan; Fabio Gonçalves Ferreira
Journal:  Clinics (Sao Paulo)       Date:  2015-06-01       Impact factor: 2.365

8.  The Impact of the Introduction of MELD on the Dynamics of the Liver Transplantation Waiting List in São Paulo, Brazil.

Authors:  Eleazar Chaib; Eduardo Massad; Bruno Butturi Varone; Andre Leopoldino Bordini; Flavio Henrique Ferreira Galvão; Alessandra Crescenzi; Arnaldo Bernal Filho; Luiz Augusto Carneiro D'Albuquerque
Journal:  J Transplant       Date:  2014-11-27

9.  Prediction of postoperative outcomes using intraoperative hemodynamic monitoring data.

Authors:  Varesh Prasad; Maria Guerrisi; Mario Dauri; Filadelfo Coniglione; Giuseppe Tisone; Elisa De Carolis; Annagrazia Cillis; Antonio Canichella; Nicola Toschi; Thomas Heldt
Journal:  Sci Rep       Date:  2017-11-27       Impact factor: 4.379

10.  BAR, SOFT AND DRI POST-HEPATIC TRANSPLANTATION: WHAT IS THE BEST FOR SURVIVAL ANALYSIS?

Authors:  Fernando Torterolli; Rafael Katsunori Watanabe; Fernando Issamu Tabushi; Igor Luna Peixoto; Paulo Afonso Nunes Nassif; Nertan Luiz Tefilli; Sergio Luiz Rocha; Osvaldo Malafaia
Journal:  Arq Bras Cir Dig       Date:  2021-06-11
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