Literature DB >> 16952176

Development and validation of a model predicting graft survival after liver transplantation.

George N Ioannou1.   

Abstract

This study aimed to develop and validate a comprehensive model that predicts survival after liver transplantation based on pretransplant donor and recipient characteristics. Complete data were available from the United Network for Organ Sharing for 20,301 persons who underwent liver transplantation in the United States between 1994 and 2003. Proportional-hazards regression was used to identify the donor and recipient characteristics that best predicted survival and incorporate these characteristics in a multivariate model. A data-splitting approach was used to compare survival predicted by the model to the observed survival in samples not used in the derivation of the model. A model was derived using 4 donor characteristics (age, cold ischemia time, gender, and race/ethnicity) and 9 recipient characteristics (age, body max index, model for end-stage liver disease score, United Network for Organ Sharing priority status, gender, race/ethnicity, diabetes mellitus, cause of liver disease, and serum albumin) that adequately predicted survival after liver transplantation in patients without hepatitis C virus, and a slightly different model was used for patients with hepatitis C virus. The models illustrate that variations in both pretransplant donor and recipient characteristics have a large effect on posttransplant survival. In conclusion, the models presented here can be used to derive scores that are proportional to the excess risk of graft loss after liver transplantation for potential donors, recipients, or donor/recipient combinations. The models may be used to inform liver transplant candidates and their doctors what posttransplant survival would be expected when a given donor is offered and may be particularly helpful for marginal or high-risk donors. (c) 2006 AASLD

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Year:  2006        PMID: 16952176     DOI: 10.1002/lt.20764

Source DB:  PubMed          Journal:  Liver Transpl        ISSN: 1527-6465            Impact factor:   5.799


  28 in total

1.  Recipient-donor race mismatch for African American liver transplant patients with chronic hepatitis C.

Authors:  Varun Saxena; Jennifer C Lai; Jacqueline G O'Leary; Elizabeth C Verna; Robert S Brown; R Todd Stravitz; James F Trotter; Kartik Krishnan; Norah A Terrault
Journal:  Liver Transpl       Date:  2012-05       Impact factor: 5.799

Review 2.  Quantitative Assessment of Liver Fat with Magnetic Resonance Imaging and Spectroscopy.

Authors:  Scott B Reeder; Irene Cruite; Gavin Hamilton; Claude B Sirlin
Journal:  J Magn Reson Imaging       Date:  2011-09-16       Impact factor: 4.813

Review 3.  Quantification of liver fat with magnetic resonance imaging.

Authors:  Scott B Reeder; Claude B Sirlin
Journal:  Magn Reson Imaging Clin N Am       Date:  2010-08       Impact factor: 2.266

Review 4.  Development of organ-specific donor risk indices.

Authors:  Sanjeev K Akkina; Sumeet K Asrani; Yi Peng; Peter Stock; W Ray Kim; Ajay K Israni
Journal:  Liver Transpl       Date:  2012-04       Impact factor: 5.799

5.  Donor race does not predict graft failure after liver transplantation.

Authors:  Sumeet K Asrani; Young-Suk Lim; Terry M Therneau; Rachel A Pedersen; Julie Heimbach; W Ray Kim
Journal:  Gastroenterology       Date:  2010-02-19       Impact factor: 22.682

Review 6.  Prioritization for liver transplantation.

Authors:  Evangelos Cholongitas; Giacomo Germani; Andrew K Burroughs
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2010-11-02       Impact factor: 46.802

7.  Preoperative assessment of the risk factors that help to predict the prognosis after living donor liver transplantation.

Authors:  Ryuichi Yoshida; Takayuki Iwamoto; Takahito Yagi; Daisuke Sato; Yuzo Umeda; Kenji Mizuno; Susumu Shinoura; Hiroyoshi Matsukawa; Hiroaki Matsuda; Hiroshi Sadamori; Noriaki Tanaka
Journal:  World J Surg       Date:  2008-11       Impact factor: 3.352

8.  The effect of donor race on the survival of Black Americans undergoing liver transplantation for chronic hepatitis C.

Authors:  Phillip S Pang; Ahmad Kamal; Jeffrey S Glenn
Journal:  Liver Transpl       Date:  2009-09       Impact factor: 5.799

9.  Perioperative risks of bariatric surgery among patients with and without history of solid organ transplant.

Authors:  John R Montgomery; Jordan A Cohen; Craig S Brown; Kyle H Sheetz; Grace F Chao; Seth A Waits; Dana A Telem
Journal:  Am J Transplant       Date:  2020-05-08       Impact factor: 8.086

10.  Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

Authors:  Lawrence Lau; Yamuna Kankanige; Benjamin Rubinstein; Robert Jones; Christopher Christophi; Vijayaragavan Muralidharan; James Bailey
Journal:  Transplantation       Date:  2017-04       Impact factor: 4.939

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