Literature DB >> 26373873

Survival outcomes in liver transplant recipients with Model for End-stage Liver Disease scores of 40 or higher: a decade-long experience.

Hina J Panchal1, Joel B Durinka2, Jeromy Patterson3, Farah Karipineni2, Sarah Ashburn4, Eric Siskind5, Jorge Ortiz6.   

Abstract

BACKGROUND: The Model for End-stage Liver Disease (MELD) has been used as a prognostic tool since 2002 to predict pre-transplant mortality. Increasing proportions of transplant candidates with higher MELD scores, combined with improvements in transplant outcomes, mandate the need to study surgical outcomes in patients with MELD scores of ≥40.
METHODS: A retrospective longitudinal analysis of United Network for Organ Sharing (UNOS) data on all liver transplantations performed between February 2002 and June 2011 (n = 33,398) stratified by MELD score (<30, 30-39, ≥40) was conducted. The primary outcomes of interest were short- and longterm graft and patient survival. A Kaplan-Meier product limit method and Cox regression were used. A subanalysis using a futile population was performed to determine futility predictors.
RESULTS: Of the 33,398 transplant recipients analysed, 74% scored <30, 18% scored 30-39, and 8% scored ≥40 at transplantation. Recipients with MELD scores of ≥40 were more likely to be younger (P < 0.001), non-White and to have shorter waitlist times (P < 0.001). Overall patient survival correlated inversely with increasing MELD score; this trend was consistent for both short-term (30 days and 90 days) and longterm (1, 3 and 5 years) graft and patient survival. In multivariate analysis, increasing age, African-American ethnicity, donor obesity and diabetes were negative predictors of survival. Futility predictors included patient age of >60 years, obesity, peri-transplantation intensive care unit hospitalization with ventilation, and multiple comorbidities.
CONCLUSIONS: Liver transplantation in recipients with MELD scores of ≥40 offers acceptable longterm survival outcomes. Futility predictors indicate the need for prospective follow-up studies to define the population to gain the highest benefit from this precious resource.
© 2015 International Hepato-Pancreato-Biliary Association.

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Year:  2015        PMID: 26373873      PMCID: PMC4644359          DOI: 10.1111/hpb.12485

Source DB:  PubMed          Journal:  HPB (Oxford)        ISSN: 1365-182X            Impact factor:   3.647


  12 in total

Review 1.  Liver transplantation in the era of model for end-stage liver disease.

Authors:  Victor S Wang; Sammy Saab
Journal:  Liver Int       Date:  2004-02       Impact factor: 5.828

2.  The survival benefit of liver transplantation.

Authors:  Robert M Merion; Douglas E Schaubel; Dawn M Dykstra; Richard B Freeman; Friedrich K Port; Robert A Wolfe
Journal:  Am J Transplant       Date:  2005-02       Impact factor: 8.086

3.  Outcomes after liver transplantation in patients achieving a model for end-stage liver disease score of 40 or higher.

Authors:  Sophoclis Alexopoulos; Lea Matsuoka; Yong Cho; Elizabeth Thomas; Mohd Sheikh; Maria Stapfer; Kiran Dhanireddy; Linda Sher; Rick Selby; Yuri Genyk
Journal:  Transplantation       Date:  2013-02-15       Impact factor: 4.939

4.  MELD scores of liver transplant recipients according to size of waiting list: impact of organ allocation and patient outcomes.

Authors:  James F Trotter; Michael J Osgood
Journal:  JAMA       Date:  2004-04-21       Impact factor: 56.272

5.  Selection of patients for liver transplantation and allocation of donated livers in the UK.

Authors:  J Neuberger; A Gimson; M Davies; M Akyol; J O'Grady; A Burroughs; M Hudson
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6.  MELD score predicts 1-year patient survival post-orthotopic liver transplantation.

Authors:  Sammy Saab; Victor Wang; Ayman B Ibrahim; Francisco Durazo; Steven Han; Douglas G Farmer; Hasan Yersiz; Marcia Morrisey; Leonard I Goldstein; R Mark Ghobrial; Ronald W Busuttil
Journal:  Liver Transpl       Date:  2003-05       Impact factor: 5.799

7.  Pretransplant MELD score and post liver transplantation survival in the UK and Ireland.

Authors:  Mathew Jacob; Lynn P Copley; James D Lewsey; Alex Gimson; Giles J Toogood; Mohamed Rela; Jan H P van der Meulen
Journal:  Liver Transpl       Date:  2004-07       Impact factor: 5.799

8.  A correlation between the pretransplantation MELD score and mortality in the first two years after liver transplantation.

Authors:  Nicholas N Onaca; Marlon F Levy; Edmund Q Sanchez; Srinath Chinnakotla; Carlos G Fasola; Mark J Thomas; Jeffrey S Weinstein; Natalie G Murray; Robert M Goldstein; Goran B Klintmalm
Journal:  Liver Transpl       Date:  2003-02       Impact factor: 5.799

9.  Impact of the center on graft failure after liver transplantation.

Authors:  Sumeet K Asrani; W Ray Kim; Erick B Edwards; Joseph J Larson; Gabriel Thabut; Walter K Kremers; Terry M Therneau; Julie Heimbach
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Review 10.  Important predictor of mortality in patients with end-stage liver disease.

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Journal:  Clin Mol Hepatol       Date:  2013-06-27
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1.  Single-Center Experience on Liver Transplantation for Model for End-Stage Liver Disease Score 40 Patients.

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3.  A case series on simultaneous liver and kidney transplantation: do we need intraoperative renal replacement therapy?

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4.  Outcomes of Liver Transplant Recipients With Acute-on-Chronic Liver Failure Based on EASL-CLIF Consortium Definition: A Single-center Study.

Authors:  Uchenna Agbim; Anuj Sharma; Benedict Maliakkal; Saradasri Karri; Masahiko Yazawa; William Goldkamp; Pradeep S B Podila; Jason M Vanatta; Humberto Gonzalez; Miklos Z Molnar; Satheesh P Nair; James D Eason; Sanjaya K Satapathy
Journal:  Transplant Direct       Date:  2020-03-18

Review 5.  Approaches for patients with very high MELD scores.

Authors:  Florent Artru; Didier Samuel
Journal:  JHEP Rep       Date:  2019-02-23

6.  Outcomes of liver transplant recipients with high MELD scores: an experience from a Canadian centre.

Authors:  Michael S Bleszynski; Subin Punnen; Sameer Desai; Trana Hussaini; Vladimir Marquez; Eric M Yoshida; Saumya Jayakumar; Stephanie Chartier-Plante; Maja Segedi; Charles H Scudamore; Stephen Chung; Andrzej K Buczkowski; Peter T W Kim
Journal:  Can J Surg       Date:  2022-07-05       Impact factor: 2.840

Review 7.  Literature review of the mechanisms of acute kidney injury secondary to acute liver injury.

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8.  The Role of Predictive Models in the Assessment of the Poor Outcomes in Pediatric Acute Liver Failure.

Authors:  Tudor Lucian Pop; Cornel Olimpiu Aldea; Dan Delean; Bogdan Bulata; Dora Boghiţoiu; Daniela Păcurar; Coriolan Emil Ulmeanu; Alina Grama
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