Factors Associated with Mortality and Graft Failure in Liver Transplants: A Hierarchical Approach

被引:22
作者
Haddad, Luciana [1 ]
Flores Cassenote, Alex Jones [2 ,3 ]
Andraus, Wellington [1 ]
de Martino, Rodrigo Bronze [1 ]
de Siqueira Ortega, Neli Regina [3 ]
Abe, Jair Minoro [4 ]
Carneiro D'Albuquerque, Luiz Augusto [1 ]
机构
[1] Univ Sao Paulo, Dept Gastroenterol, Digest Transplant Unit, Sao Paulo, Brazil
[2] Univ Sao Paulo, Fac Med, Postgrad Program Infect & Parasit Dis, Sao Paulo, Brazil
[3] Univ Sao Paulo, Fac Med, Ctr Fuzzy Syst Hlth, Sao Paulo, Brazil
[4] Univ Sao Paulo, Inst Adv Studies, Sao Paulo, Brazil
基金
巴西圣保罗研究基金会;
关键词
MELD SCORE; SURVIVAL BENEFIT; DISEASE MELD; DONOR; MODEL; ALLOCATION; PREDICT;
D O I
10.1371/journal.pone.0134874
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Liver transplantation has received increased attention in the medical field since the 1980s following the introduction of new immunosuppressants and improved surgical techniques. Currently, transplantation is the treatment of choice for patients with end-stage liver disease, and it has been expanded for other indications. Liver transplantation outcomes depend on donor factors, operating conditions, and the disease stage of the recipient. A retrospective cohort was studied to identify mortality and graft failure rates and their associated factors. All adult liver transplants performed in the state of Sao Paulo, Brazil, between 2006 and 2012 were studied. Methods and Findings A hierarchical Poisson multiple regression model was used to analyze factors related to mortality and graft failure in liver transplants. A total of 2,666 patients, 18 years or older, (1,482 males; 1,184 females) were investigated. Outcome variables included mortality and graft failure rates, which were grouped into a single binary variable called negative outcome rate. Additionally, donor clinical, laboratory, intensive care, and organ characteristics and recipient clinical data were analyzed. The mortality rate was 16.2 per 100 person-years (py) (95% CI: 15.1-17.3), and the graft failure rate was 1.8 per 100 py (95% CI: 1.5-2.2). Thus, the negative outcome rate was 18.0 per 100 py (95% CI: 16.9-19.2). The best risk model demonstrated that recipient creatinine >= 2.11 mg/dl [RR = 1.80 (95% CI: 1.56-2.08)], total bilirubin >= 2.11 mg/dl [RR = 1.48 (95% CI: 1.27-1.72)], Na+ >= 141.01 mg/dl [RR = 1.70 (95% CI: 1.47-1.97)], RNI >= 2.71 [RR = 1.64 (95% CI: 1.41-1.90)], body surface >= 1.98 [RR = 0.81 (95% CI: 0.68-0.97)] and donor age >= 54 years [RR = 1.28 (95% CI: 1.11-1.48)], male gender [RR = 1.19(95% CI: 1.03-1.37)], dobutamine use [RR = 0.54 (95% CI: 0.36-0.82)] and intubation >= 6 days [RR = 1.16 (95% CI: 1.10-1.34)] affected the negative outcome rate. Conclusions The current study confirms that both donor and recipient characteristics must be considered in post-transplant outcomes and prognostic scores. Our data demonstrated that recipient characteristics have a greater impact on post-transplant outcomes than donor characteristics. This new concept makes liver transplant teams to rethink about the limits in a MELD allocation system, with many teams competing with each other. The results suggest that although we have some concerns about the donors features, the recipient factors were heaviest predictors for bad outcomes.
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页数:20
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