A simple model to estimate survival after retransplantation of the liver.
To formulate a model predicting survival after liver retransplantation, we analyzed in detail the last 150 cases of hepatic retransplantation at UCLA. Cox proportional hazards regression analysis identified five variables that demonstrated independent simultaneous prognostic value in estimating patient survival after retransplantation: (1) age group (pediatric or adult), (2) recipient requiring preoperative mechanical ventilation, (3) donor organ cold ischemia > or =12 hr, (4) preoperative serum creatinine, and (5) preoperative serum total bilirubin. The Cox regression equation that predicts survival based on these covariates was simplified by assigning individual patients a risk classification based on a 5-point scoring system. We demonstrate that this system can be employed to identify a subgroup of patients in which the expected outcome is too poor to justify retransplantation. These findings may assist in the rational selection of patients suitable for retransplantation.
Markmann
J F
JF
Dumont-UCLA Center for Liver Transplantation and Surgery, Department of Surgery, UCLA Medical Center, Los Angeles, California 90095-7054, USA.
Gornbein
J
J
Markowitz
J S
JS
Levy
M F
MF
Klintmalm
G B
GB
Yersiz
H
H
Morrisey
M
M
Drazan
K
K
Farmer
D G
DG
Ghobrial
R M
RM
Goss
J
J
Seu
P
P
Martin
P
P
Goldstein
L I
LI
Busuttil
R W
RW
D000328:Adult; D000367:Age Factors; D002140:California; D002648:Child; D016001:Confidence Intervals; D005500:Follow-Up Studies; D006785:Hospitals, University; D006801:Humans; D007511:Ischemia; D008099:Liver; D016031:Liver Transplantation / Q000401:mortality*; D015233:Models, Statistical; D015999:Multivariate Analysis; D009926:Organ Preservation; D016016:Proportional Hazards Models; D012086:Reoperation / Q000401:mortality*; D012189:Retrospective Studies; D012307:Risk Factors; D016019:Survival Analysis; D013997:Time Factors; D014019:Tissue Donors