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 eases of hepatic retransplantation at UCLA Cox proportional hazards regression analysis identified five variables that demonstrated independent simultaneous prognostic value in estimating patie nt survival after retransplantation: (1) age group (pediatric or adult), (2 ) recipient requiring preoperative mechanical ventilation, (3) donor organ cold ischemia greater than or equal to 12 hr, (4) preoperative serum creati nine, and (5) preoperative serum total bilirubin. The Cox regression equati on that predicts survival based on these covariates was simplified by assig ning individual patients a risk classification based on a 5-point scoring s ystem. We demonstrate that this system can be employed to identify a subgro up of patients in which the expected outcome is too poor to justify retrans plantation. These findings may assist in the rational selection of patients suitable for retransplantation.