TY - JOUR
T1 - Predictors of the cause of liver transplantation
AU - Brown, R. S.
AU - Lake, J. R.
AU - Ascher, N. L.
AU - Emond, J. L.
AU - Roberts, J. P.
PY - 1998
Y1 - 1998
N2 - Background. Orthotopic liver transplantation (OLT) is a highly effective but costly therapy for end-stage liver disease. However, there are limited data on the demographic and clinical variables that affect cost. We undertook a preliminary study using multiple regression techniques to analyze factors that influence the cost of OLT. Methods. Patient and demographic data, including laboratory values and charges for all liver transplantations performed between June 1992 and June 1993 were analyzed (n = 111). Linear regression with standard and log-transformed values was performed by using STATA software (Stata Corporation College Station, TX). Independent variables included in the analyses were age, sex, United Network for Organ Sharing (UNOS) status, primary versus retransplantation, liverkidney transplantation, and laboratory parameters of both liver (aspartate aminotransferase, AST; alkaline phosphatase; bilirubin; albumin; and prothrombin time) and kidney (blood urea nitrogen, BUN; creatinine) function. An F-toremove strategy was employed with a significance level set at P = .05. Results. The full model with 12 variables explained 37% of the total variation in charges. When one excludes variables that did not have a significant impact on cost, the remaining significant variables were BUN and UNOS status 1. The final model was Charges (US$) = 3,407 x BUN + 74,474 x status 1 + 102,662 This model accounted for 29% of the total variability with BUN accounting for the vast majority (26%). Conclusions. Renal function is the most important predictor of cost of OLT (P < .001). UNOS status 1 further increases cost, but other hospitalized patients have similar costs when one controls for other clinical variables. The degree of liver impairment is less important in predicting cost.
AB - Background. Orthotopic liver transplantation (OLT) is a highly effective but costly therapy for end-stage liver disease. However, there are limited data on the demographic and clinical variables that affect cost. We undertook a preliminary study using multiple regression techniques to analyze factors that influence the cost of OLT. Methods. Patient and demographic data, including laboratory values and charges for all liver transplantations performed between June 1992 and June 1993 were analyzed (n = 111). Linear regression with standard and log-transformed values was performed by using STATA software (Stata Corporation College Station, TX). Independent variables included in the analyses were age, sex, United Network for Organ Sharing (UNOS) status, primary versus retransplantation, liverkidney transplantation, and laboratory parameters of both liver (aspartate aminotransferase, AST; alkaline phosphatase; bilirubin; albumin; and prothrombin time) and kidney (blood urea nitrogen, BUN; creatinine) function. An F-toremove strategy was employed with a significance level set at P = .05. Results. The full model with 12 variables explained 37% of the total variation in charges. When one excludes variables that did not have a significant impact on cost, the remaining significant variables were BUN and UNOS status 1. The final model was Charges (US$) = 3,407 x BUN + 74,474 x status 1 + 102,662 This model accounted for 29% of the total variability with BUN accounting for the vast majority (26%). Conclusions. Renal function is the most important predictor of cost of OLT (P < .001). UNOS status 1 further increases cost, but other hospitalized patients have similar costs when one controls for other clinical variables. The degree of liver impairment is less important in predicting cost.
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U2 - 10.1002/lt.500040211
DO - 10.1002/lt.500040211
M3 - Article
C2 - 9516571
AN - SCOPUS:0032011783
SN - 1074-3022
VL - 4
SP - 170
EP - 176
JO - Liver Transplantation and Surgery
JF - Liver Transplantation and Surgery
IS - 2
ER -