Literature DB >> 22143890

Value of the SOFA score as a predictive model for short-term survival in high-risk liver transplant recipients with a pre-transplant labMELD score ≥ 30.

Harald Schrem1, Melanie Reichert, Benedikt Reichert, Thomas Becker, Frank Lehner, Moritz Kleine, Hüseyin Bektas, Kai Johanning, Christian P Strassburg, Jürgen Klempnauer.   

Abstract

INTRODUCTION: The Sequential Organ Failure Assessment (SOFA) score has been applied for the prediction of survival in critically ill patients. We analysed the value of the SOFA score for the prediction of short-term survival after liver transplantation in high-risk liver transplant recipients with a labMELD score ≥30. PATIENTS AND METHODS: We conducted a retrospective single-centre analysis including 88 consecutive liver transplants in adults between January 1, 2007 and December 31, 2010 with a pre-transplant labMELD score ≥30. The SOFA score was assessed preoperatively, directly after transplantation and on post-operative days (PODs) 1-10. Combined and living-related liver transplants were excluded. Receiver operating characteristic (ROC) curve analysis with the Hosmer-Lemeshow test and application of the Brier score were used to calculate sensitivity, specificity, overall model correctness and calibration. Cutoff values were selected with the best Youden index.
RESULTS: ROC curve analysis showed areas under the curve (AUROCs) >0.8 for the SOFA score on PODs 1-10 for the prediction of hospital mortality, 30-day mortality and 3-month mortality with Hosmer-Lemeshow test results that confirmed good model calibration (p > 0.05). The Brier score demonstrated an accuracy of prediction (<0.25) of hospital mortality, 30-day mortality and 3-month mortality for the SOFA scores on PODs 4-9 indicating superior accuracy on PODs 7 and 8 with cutoff values for the SOFA score between 16.5 and 18.5. The pre-transplant SOFA score failed to reach AUROCs >0.7 (0.603-0.663) for the prediction of short-term survival.
CONCLUSIONS: Our results confirm the usefulness of the SOFA score in high-risk liver recipients during the early post-operative course, especially on PODs 7-8 for the prediction of hospital mortality, 30-day mortality and 3-month mortality and may be useful to predict futile early acute retransplantation.

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Year:  2011        PMID: 22143890     DOI: 10.1007/s00423-011-0881-9

Source DB:  PubMed          Journal:  Langenbecks Arch Surg        ISSN: 1435-2443            Impact factor:   3.445


  30 in total

1.  Prognostic models in cirrhotics admitted to intensive care units better predict outcome when assessed at 48 h after admission.

Authors:  Evangelos Cholongitas; Alex Betrosian; Marco Senzolo; Steve Shaw; David Patch; Pinelopi Manousou; James O'Beirne; Andrew K Burroughs
Journal:  J Gastroenterol Hepatol       Date:  2007-12-13       Impact factor: 4.029

Review 2.  Liver transplantation: the current situation.

Authors:  Rene Adam; Emir Hoti
Journal:  Semin Liver Dis       Date:  2009-02-23       Impact factor: 6.115

3.  The Multiple Organ Dysfunction Score (MODS) versus the Sequential Organ Failure Assessment (SOFA) score in outcome prediction.

Authors:  Daliana Peres Bota; Christian Melot; Flavio Lopes Ferreira; Vinh Nguyen Ba; Jean-Louis Vincent
Journal:  Intensive Care Med       Date:  2002-09-06       Impact factor: 17.440

4.  Hepatocellular carcinoma patients are advantaged in the current liver transplant allocation system.

Authors:  K Washburn; E Edwards; A Harper; R Freeman
Journal:  Am J Transplant       Date:  2010-05-10       Impact factor: 8.086

5.  Multicentric evaluation of model for end-stage liver disease-based allocation and survival after liver transplantation in Germany--limitations of the 'sickest first'-concept.

Authors:  Tobias J Weismüller; Panagiotis Fikatas; Jan Schmidt; Ana P Barreiros; Gerd Otto; Susanne Beckebaum; Andreas Paul; Markus N Scherer; Hartmut H Schmidt; Hans J Schlitt; Peter Neuhaus; Jürgen Klempnauer; Johann Pratschke; Michael P Manns; Christian P Strassburg
Journal:  Transpl Int       Date:  2010-09-03       Impact factor: 3.782

6.  The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study. Working Group on Sepsis related Problems of the ESICM.

Authors:  R Moreno; J L Vincent; R Matos; A Mendonça; F Cantraine; L Thijs; J Takala; C Sprung; M Antonelli; H Bruining; S Willatts
Journal:  Intensive Care Med       Date:  1999-07       Impact factor: 17.440

Review 7.  [Model for end-stage liver disease. New basis of allocation for liver transplantations].

Authors:  G E Jung; J Encke; J Schmidt; A Rahmel
Journal:  Chirurg       Date:  2008-02       Impact factor: 0.955

8.  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

9.  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

Review 10.  Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review.

Authors:  Lilian Minne; Ameen Abu-Hanna; Evert de Jonge
Journal:  Crit Care       Date:  2008-12-17       Impact factor: 9.097

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  4 in total

1.  Massive blood transfusion after the first cut in liver transplantation predicts renal outcome and survival.

Authors:  Benedikt Reichert; Alexander Kaltenborn; Thomas Becker; Mario Schiffer; Jürgen Klempnauer; Harald Schrem
Journal:  Langenbecks Arch Surg       Date:  2014-03-30       Impact factor: 3.445

2.  Value and limitations of the BAR-score for donor allocation in liver transplantation.

Authors:  Harald Schrem; Anna-Luise Platsakis; Alexander Kaltenborn; Armin Koch; Courtney Metz; Marc Barthold; Christian Krauth; Volker Amelung; Felix Braun; Thomas Becker; Jürgen Klempnauer; Benedikt Reichert
Journal:  Langenbecks Arch Surg       Date:  2014-09-14       Impact factor: 3.445

3.  Matched-pair analysis: identification of factors with independent influence on the development of PTLD after kidney or liver transplantation.

Authors:  Lisa Rausch; Christian Koenecke; Hans-Friedrich Koch; Alexander Kaltenborn; Nikos Emmanouilidis; Lars Pape; Frank Lehner; Viktor Arelin; Ulrich Baumann; Harald Schrem
Journal:  Transplant Res       Date:  2016-08-02

4.  Prognostic Abilities and Quality Assessment of Models for the Prediction of 90-Day Mortality in Liver Transplant Waiting List Patients.

Authors:  Ricardo Salinas Saldaña; Harald Schrem; Marc Barthold; Alexander Kaltenborn
Journal:  PLoS One       Date:  2017-01-27       Impact factor: 3.240

  4 in total

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