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10.1002/lt.23950

http://scihub22266oqcxt.onion/10.1002/lt.23950
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C4213202!4213202!25044256
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suck abstract from ncbi


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pmid25044256      Liver+Transpl 2014 ; 20 (11): 1306-16
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  • High early cardiovascular mortality following 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 PMID25044256show ga
  • Cardiovascular disease (CVD) contributes to excess long-term mortality after liver transplantation (LT), however little is known about early post-operative CVD mortality in the current era. In addition, there is no model to predict early post-operative 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 prevalence and predictors of early (30-day) CVD mortality, 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 using bootstrapping techniques. Among 54,697 LT recipients, there were 1576 (2.9%) deaths within 30 days. CVD death was the leading cause of 30-day mortality (42.1%), followed by infection (27.9%) and graft failure (12.2%). In multivariate analysis, 9 (6 recipient, 2 donor, 1 operative) significant covariates were identified: age, pre-operative hospitalization, ICU and ventilator status, calculated MELD score, portal vein thrombosis, national organ sharing, donor BMI and cold ischemia time. The model showed moderate discrimination (c-statistic 0.66, 95% CI: 0.63?0.68). 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, evaluation of additional CVD-related variables not collected by the OPTN are needed in order to improve model accuracy and potential clinical utility.
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