Predictive models in cirrhosis: correlation with the final results and costs of liver transplantation in Chile.
Medical scores for predicting survival are essential to stratify patients with end-stage liver disease (ESLD) for prioritization for liver transplantation (OLT). Recently the UNOS has adopted the Mayo Model for End-stage Liver Disease (MELD) score as the basis for liver allocation in the United States. We retrospectively evaluated and assessed the prognostic impact, the length of stay (LOS), and hospital charges for OLT using two severity scores (Child-Turcotte-Pugh [CTP] versus MELD) to stratify cirrhotic patients before OLT. Twenty-six consecutive adult cirrhotic patients (11 women, mean age 46 years) underwent LT between 2000 and 2002. The main causes for transplantation were alcohol and primary biliary cirrhosis. The mean CTP and MELD scores at the moment of listing for OLT were 8.9 and 16.3 points, respectively. The best discriminative values with prognostic impact in terms of outcome and costs of OLT were a Child Pugh score >/=11 points or a MELD score >/=20 points. Patients in these strata showed a significant increase in LOS in the hospital (from a mean of 12 to 22 days) and intensive care stay (from a mean of 4 to 14 days) post-OLT when compared with patients with a lower CTP or MELD score (P <.05). There was also a trend toward higher hospital charges (P =.06). Organ allocation by MELD score will probably adversely affect the LOS and hospital charges of patients being transplanted due to ESLD.
Zapata
R
R
Liver Transplant Unit, Department of Medicine and Surgery, Clínica Alemana de Santiago, Santiago, Chile. rzapata@alemana.cl
Innocenti
F
F
Sanhueza
E
E
Humeres
R
R
Rios
H
H
Suarez
L
L
Palacios
J M
JM
Rius
M
M
Hepp
J
J
D000328:Adult; D002677:Chile; D003365:Costs and Cost Analysis; D004469:Economics, Hospital; D006801:Humans; D007902:Length of Stay / Q000191:economics; D008103:Liver Cirrhosis / Q000191:economics* / Q000401:mortality / Q000601:surgery*; D016031:Liver Transplantation / Q000191:economics*; D015233:Models, Statistical; D012189:Retrospective Studies; D016019:Survival Analysis