High early cardiovascular mortality after liver transplantation.
High early cardiovascular mortality after liver transplantation.
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DOI:
10.1002/lt.23950
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发表时间:
2014-11
影响因子:
4.6
通讯作者:
Lloyd-Jones, Donald M.
中科院分区:
文献类型:
--
作者:
VanWagner, Lisa B.;Lapin, Brittany;Levitsky, Josh;Wilkins, John T.;Abecassis, Michael M.;Skaro, Anton I.;Lloyd-Jones, Donald M.
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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影响因子:
37.8
作者:
Go AS;Mozaffarian D;Roger VL;Benjamin EJ;Berry JD;Blaha MJ;Dai S;Ford ES;Fox CS;Franco S;Fullerton HJ;Gillespie C;Hailpern SM;Heit JA;Howard VJ;Huffman MD;Judd SE;Kissela BM;Kittner SJ;Lackland DT;Lichtman JH;Lisabeth LD;Mackey RH;Magid DJ;Marcus GM;Marelli A;Matchar DB;McGuire DK;Mohler ER 3rd;Moy CS;Mussolino ME;Neumar RW;Nichol G;Pandey DK;Paynter NP;Reeves MJ;Sorlie PD;Stein J;Towfighi A;Turan TN;Virani SS;Wong ND;Woo D;Turner MB;American Heart Association Statistics Committee and Stroke Statistics Subcommittee
通讯作者:
American Heart Association Statistics Committee and Stroke Statistics Subcommittee
影响因子:
24
作者:
Lentine, Krista L.;Costa, Salvatore P.;Eagle, Kim A.
通讯作者:
Eagle, Kim A.
影响因子:
6.2
作者:
Gaynor, Jeffrey J.;Moon, Jang I.;Tzakis, Andreas G.
通讯作者:
Tzakis, Andreas G.
影响因子:
120.7
作者:
LEGALL, JR;LEMESHOW, S;SAULNIER, F
通讯作者:
SAULNIER, F
DOI:
10.1016/j.annfar.2011.06.014
发表时间:
2011-12-01
影响因子:
--
作者:
Jung, B.;Cisse, M.;Jaber, S.
通讯作者:
Jaber, S.