A novel prognostic model based on serum levels of total bilirubin and creatinine early after liver transplantation.
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.
Xu
Xiao
X
Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ling
Qi
Q
Wu
Jian
J
Chen
Jun
J
Gao
Feng
F
Feng
Xiao-Ning
XN
Zheng
Shu-Sen
SS
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
D015415:Biomarkers; D003404:Creatinine; D001663:Bilirubin