Researchers from California and Pennsylvania, USA, developed a prognostic model that determines patient survival outcomes after orthotopic liver transplantation (OLT), using readily available pretransplant variables.
Variables that may affect patient survival following OLT were analyzed in hepatitis C (HCV) recipients at the authors' center. This was because HCV is the most common indication for OLT.
The resulting patient survival model was examined and refined in both HCV and non-HCV patients in the United Network for Organ Sharing (UNOS) database.
Among HCV recipients, mortality was predicted using recipient age, recipient creatinine levels, donor female gender, and urgent UNOS classification.
The above variables, in addition to donor age, total bilirubin, prothrombin time (PT), retransplantation, and warm and cold ischemia times, were then applied to the UNOS database.
| Model based upon 8 variables.
| Annals of Surgery |
Of the 46,942 patients transplanted over the last 10 years, 25,772 patients had complete data sets.
An 8-factor model that accurately predicted survival was derived.
A post-transplantation mortality index was calculated using a combination of these variables, and was applicable to first or second liver transplants.
Patient survival rates, based on model-predicted risk scores for death and observed posttransplant survival rates, were similar.
Additionally, the model accurately predicted survival outcomes for HCV and non-HCV patients.
Dr Rafik M. Ghobrial, of the David Geffen School of Medicine at UCLA, Los Angeles, California, said on behalf of fellow authors, "Post-transplant patient survival can be accurately predicted based on 8 straightforward factors."
"The balanced application of a model for liver transplant survival estimate, in addition to disease severity, would markedly improve survival outcomes and maximize patients' benefits following OLT," it was concluded.