Predicting end-stage renal disease after liver transplant

Am J Transplant. 2013 Jul;13(7):1782-92. doi: 10.1111/ajt.12257. Epub 2013 May 13.


Few equations have been developed to predict end-stage renal disease (ESRD) after deceased donor liver transplant. This retrospective observational cohort study analyzed all adult deceased donor liver transplant recipients in the Scientific Registry of Transplant Recipients (SRTR) database, 1995-2010. The prediction equation for ESRD was developed using candidate predictor variables available in SRTR after implementation of the allocation policy based on the model for end-stage liver disease. ESRD was defined as initiation of maintenance dialysis therapy, kidney transplant or registration on the kidney transplant waiting list. We used Cox proportional hazard models to develop separate equations for assessing risk of ESRD by 6 months posttransplant and between 6 months and 5 years posttransplant. Variables in the 6-month equation included recipient age, history of diabetes, history of dialysis before liver transplant, history of malignancy, body mass index, serum creatinine and liver donor risk index. Variables in the 6-month to 5-year equation included recipient race, history of diabetes, hepatitis C status, serum albumin, serum bilirubin and serum creatinine. The prediction equations have good calibration and discrimination (C statistics 0.74-0.78). We have produced risk prediction equations that can be used to aid in understanding the risk of ESRD after liver transplant.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Distribution
  • Age of Onset
  • Aged
  • Female
  • Follow-Up Studies
  • Humans
  • Incidence
  • Kidney Failure, Chronic / epidemiology*
  • Kidney Failure, Chronic / etiology
  • Liver Transplantation / adverse effects*
  • Male
  • Middle Aged
  • Postoperative Complications
  • Prognosis
  • Retrospective Studies
  • Risk Assessment / methods*
  • Sex Distribution
  • United States / epidemiology