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- W1974203721 abstract "The benefit of liver transplantation (LT) is determined not only by the severity of illness, but also by the likelihood of posttransplantation survival. Current models are unable to accurately predict which patients will have the best posttransplant survival. We hypothesized that the Charlson Comorbidity Index (CCI), which includes nine comorbidities, could be used to predict survival after LT. We performed a retrospective study of 624 patients undergoing LT, with a median follow-up time of 4.3 yr. Data on pretransplant comorbidities were collected, along with potential confounders such as age, gender, etiology, and severity of liver disease. Proportional hazards analysis was performed to determine the independent effect of each variable on posttransplantation survival, and to recalibrate the CCI for use in the liver transplant population. A total of 40% of patients had 1 or more comorbidities prior to transplantation. In the multivariate analysis, CCI was an independent predictor of posttransplantation survival (hazard ratio [HR] 1.21 per unit, P < 0.001). When the individual components of the CCI were analyzed, coronary disease (HR 2.33), diabetes (HR 1.38), chronic obstructive pulmonary disease (COPD) (HR 2.67), connective tissue disease (HR 2.32), and renal insufficiency (HR 1.61) were all independent predictors of posttransplant survival. The CCI was recalibrated using a simplified weighting system to create the CCI-orthotopic LT (OLT), which improved the likelihood ratio chi-squared value from 15 to 24 for predicting posttransplantation survival. In conclusion, survival after LT is diminished in patients with pretransplantation coronary disease, diabetes, COPD, connective tissue disease, and renal insufficiency. We demonstrate the usefulness of a modified comorbidity index, the CCI-OLT, for predicting posttransplantation survival." @default.
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- W1974203721 date "2007-01-01" @default.
- W1974203721 modified "2023-10-18" @default.
- W1974203721 title "Modified Charlson Comorbidity Index for predicting survival after liver transplantation" @default.
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- W1974203721 doi "https://doi.org/10.1002/lt.21172" @default.
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