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High early cardiovascular mortality after liver transplantation

Liver Transplantation2014Vol. 20(11), pp. 1306–1316

Citations Over TimeTop 10% of 2014 papers

Lisa B. VanWagner, Brittany Lapin, Josh Levitsky, John T. Wilkins, Michaël Abécassis, Anton Skaro, Donald M. Lloyd‐Jones

Abstract

Cardiovascular disease (CVD) contributes to excessive long-term mortality after liver transplantation (LT); however, little is known about early postoperative CVD mortality in the current era. In addition, there is no model for predicting early postoperative CVD mortality across centers. We analyzed adult recipients of primary LT in the Organ Procurement and Transplantation Network (OPTN) database between February 2002 and December 2012 to assess the prevalence and predictors of early (30-day) CVD mortality, which was defined as death from arrhythmia, heart failure, myocardial infarction, cardiac arrest, thromboembolism, and/or stroke. We performed logistic regression with stepwise selection to develop a predictive model of early CVD mortality. Sex and center volume were forced into the final model, which was validated with bootstrapping techniques. Among 54,697 LT recipients, there were 1576 deaths (2.9%) within 30 days. CVD death was the leading cause of 30-day mortality (40.2%), and it was followed by infection (27.9%) and graft failure (12.2%). In a multivariate analysis, 9 significant covariates (6 recipient covariates, 2 donor covariates, and 1 operative covariate) were identified: age, preoperative hospitalization, intensive care unit status, ventilator status, calculated Model for End-Stage Liver Disease score, portal vein thrombosis, national organ sharing, donor body mass index, and cold ischemia time. The model showed moderate discrimination (C statistic = 0.66, 95% confidence interval = 0.63-0.68). In conclusion, we provide the first multicenter prognostic model for the prediction of early post-LT CVD death, the most common cause of early post-LT mortality in the current transplant era. However, evaluations of additional CVD-related variables not collected by the OPTN are needed in order to improve the model's accuracy and potential clinical utility.

Citations Over TimeTop 10% of 2014 papers

Abstract

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