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2014 ; 20
(11
): 1306-16
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High early cardiovascular mortality after liver transplantation
#MMPMID25044256
VanWagner LB
; Lapin B
; Levitsky J
; Wilkins JT
; Abecassis MM
; Skaro AI
; Lloyd-Jones DM
Liver Transpl
2014[Nov]; 20
(11
): 1306-16
PMID25044256
show ga
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.
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