title: A novel prognostic model based on serum levels of total bilirubin and creatinine early after liver transplantation.
abstract: OBJECTIVE
  We aim to evaluate the impact of early renal dysfunction (ERD), early allograft dysfunction (EAD) on post-transplant mortality, and further explore a simple and accurate model to predict prognosis.
  
  
  METHODS
  A total of 161 adult patients who underwent liver transplantation for benign end-stage liver diseases were enrolled in the retrospective study. Another 38 patients were used for model validation.
  
  
  RESULTS
  Poor patient survival was associated with ERD or EAD. A post-transplant model for predicting mortality (PMPM) based on serum levels of total bilirubin and creatinine at 24-h post-transplantation was then established according to multivariate logistic regression. At 3 months, 6 months and 1 year, the area under receiver operating characteristic curves (AUC) of PMPM score at 24-h post-transplantation (0.876, 0.878 and 0.849, respectively) were significantly higher than those of pre-transplant model for end-stage liver diseases (MELD) score (0.673, 0.674 and 0.618, respectively) or the post-transplant MELD score at 24-h post-transplantation (0.787, 0.787 and 0.781, respectively) (P<0.05). Patients with PMPM score <or=-1.4 (low-risk group, n=114) achieved better survival than those with PMPM score >-1.4 (high-risk group, n=47) (P<0.001). The patients in the high-risk group showed a relatively good outcome if their PMPM scores decreased to <or=-1.4 at post-transplant day 7. The subsequent validation study showed that PMPM functioned with a predictive accuracy of 100%.
  
  
  CONCLUSIONS
  The PMPM score could effectively predict short- and medium-term mortality in liver transplant recipients.
authors.affiliation: Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Xu
authors.forename: Qi
authors.initials: Q
authors.lastname: Ling
authors.forename: Jian
authors.initials: J
authors.lastname: Wu
authors.forename: Jun
authors.initials: J
authors.lastname: Chen
authors.forename: Feng
authors.initials: F
authors.lastname: Gao
authors.forename: Xiao-Ning
authors.initials: XN
authors.lastname: Feng
authors.forename: Shu-Sen
authors.initials: SS
authors.lastname: Zheng
mesh_terms: D000328:Adult; D001663:Bilirubin / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D003404:Creatinine / Q000097:blood*; D005500:Follow-Up Studies; D006801:Humans; D015994:Incidence; D007674:Kidney Diseases / Q000097:blood* / Q000401:mortality; D008107:Liver Diseases / Q000097:blood / Q000401:mortality / Q000601:surgery*; D017093:Liver Failure / Q000097:blood* / Q000401:mortality; D016031:Liver Transplantation; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D003404:Creatinine; D001663:Bilirubin