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Early death or retransplantation in adults after orthotopic liver transplantation: Can outcome be predicted?

Doyle, HR and Marino, IR and Jabbour, N and Zetti, G and McMichael, J and Mitchell, S and Fung, J and Starzl, TE (1994) Early death or retransplantation in adults after orthotopic liver transplantation: Can outcome be predicted? Transplantation, 57 (7). 1028 - 1036. ISSN 0041-1337

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Early, reliable outcome prediction after a liver transplant would help improve organ use by minimizing unnecessary retransplantations. At the same time, early intervention in those cases destined to fail may ameliorate the high morbidity and mortality associated with retransplantation. The purpose of this study was to analyze several parameters that have been identified in the past as being associated with patient and graft outcome, and to try to develop a model that would allow us to make predictions based on data available in the early postoperative period. A total of 148 patients were followed in a prospective, observational study. Graft failure was defined as patient death or retransplantation within 3 months of surgery. Preoperative variables studied included patient demographics, need for life support, presence of ascites, serum bilirubin, serum albumin, prothrombin time, serum creatinine, and the results of the cytotoxic crossmatch. During the first 5 postoperative days, standard measurements included serum transaminases, serum bilirubin, ketone body ratio, prothrombin time, factor V, and serum lactate. Oxygen consumption was measured shortly after surgery, once the patients had rewarmed to 36°C. There were 131 successful transplants (88.5%) and 17 failures (11.5%). Most of the variables studied were found to be associated with outcome (by univariate analysis) at different points in the early postoperative period. However, receiver operating characteristic curve analysis showed that the predictive ability of even the best parameter was not adequate to make decisions on individual patients. Multivariate analysis, using stepwise logistic regression, yielded a model with an overall accuracy of 92.7%. Again, receiver operating characteristic curve analysis suggested that this model did not achieve the discriminating power needed for routine clinical use. We are still not able to accurately predict outcome in the early posttransplant period. We must be very careful when evaluating parameters, or scoring systems, that are said to accomplish this. It is especially important in this era of cost containment, with its renewed pressures to guide therapy based on our perceived understanding of a patient’s future clinical course. © 1994 by Williams & Wilkins.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Doyle, HR
Marino, IR
Jabbour, N
Zetti, G
McMichael, J
Mitchell, S
Fung, J
Starzl, TEtes11@pitt.eduTES11
Centers: Other Centers, Institutes, Offices, or Units > Thomas E. Starzl Transplantation Institute
Date: 1 January 1994
Date Type: Publication
Journal or Publication Title: Transplantation
Volume: 57
Number: 7
Page Range: 1028 - 1036
DOI or Unique Handle: 10.1097/00007890-199404150-00008
Institution: University of Pittsburgh
Refereed: Yes
ISSN: 0041-1337
Other ID: uls-drl:31735062124858, Starzl CV No. 1607
Date Deposited: 08 Apr 2010 17:27
Last Modified: 03 Feb 2019 02:55


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