Literature DB >> 18645485

Cost prediction in liver transplantation using pretransplant donor and recipient characteristics.

T Markley Earl1, Bruce Cooil, Josh E Rubin, Ravi S Chari.   

Abstract

BACKGROUND: Liver transplantation is a costly procedure and its cost is likely driven by both donor and recipient factors. Recently, the recipient model for end-stage liver disease (MELD) score has been correlated with increased posttransplant cost; however, other factors have not been identified. We sought to identify if other donor and recipient factors are associated with increased cost.
METHODS: One hundred sixty-six liver transplants performed at our center from January 2004 through February 2006 were included in the estimation sample, and the subsequent 75 transplants were used as a validation cohort. To determine whether donor factors influenced cost, two latent class linear regression models were created from the estimation sample: one considering only recipient variables (model A) and a second incorporating both donor and recipient factors (model B). The resultant models were then validated in the second group of patients and compared with the best single-segment linear regression models.
RESULTS: Model A predictors include pretransplant intensive care unit (ICU) stay, age x body mass index, and calculated MELD. In model B, significant predictors are calculated MELD, age, age x pretransplant ICU stay, and donor age more than 40 as significant variables. In validation, only model A remained predictive of cost.
CONCLUSIONS: Although marginal donor factors are recognized to influence clinical outcome, they did not factor significantly in cost modeling. In addition to MELD, the recipient factors of pretransplant ICU stay, age, and body mass index are pretransplant variables correlated mostly with posttransplant cost across broad populations.

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Year:  2008        PMID: 18645485     DOI: 10.1097/TP.0b013e3181778d54

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  5 in total

1.  Comparable outcome of liver transplantation with histidine-tryptophan-ketoglutarate vs. University of Wisconsin preservation solution: a retrospective observational double-center trial.

Authors:  Alexander Kaltenborn; Jill Gwiasda; Volker Amelung; Christian Krauth; Frank Lehner; Felix Braun; Jürgen Klempnauer; Benedikt Reichert; Harald Schrem
Journal:  BMC Gastroenterol       Date:  2014-09-28       Impact factor: 3.067

2.  Predictors of micro-costing components in liver transplantation.

Authors:  Luciana Bertocco de Paiva Haddad; Liliana Ducatti; Luana Regina Baratelli Carelli Mendes; Wellington Andraus; Luiz Augusto Carneiro D'Albuquerque
Journal:  Clinics (Sao Paulo)       Date:  2017-06       Impact factor: 2.365

3.  High MELD score and extended operating time predict prolonged initial ICU stay after liver transplantation and influence the outcome.

Authors:  Panagiota Stratigopoulou; Andreas Paul; Dieter P Hoyer; Stylianos Kykalos; Fuat H Saner; Georgios C Sotiropoulos
Journal:  PLoS One       Date:  2017-03-20       Impact factor: 3.240

4.  Patients Benefit from Liver Transplantation for Hepatocellular Carcinoma beyond Milan Criteria without Harming the Health Care System.

Authors:  Jan-Paul Gundlach; Michael Linecker; Henrike Dobbermann; Felix Wadle; Thomas Becker; Felix Braun
Journal:  Cancers (Basel)       Date:  2022-02-23       Impact factor: 6.639

5.  Early Allograft Dysfunction Increases Hospital Associated Costs After Liver Transplantation-A Propensity Score-Matched Analysis.

Authors:  Simon Moosburner; Igor M Sauer; Frank Förster; Thomas Winklmann; Joseph Maria George Vernon Gassner; Paul V Ritschl; Robert Öllinger; Johann Pratschke; Nathanael Raschzok
Journal:  Hepatol Commun       Date:  2020-12-05
  5 in total

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