Validation and performance of three scoring systems for predicting primary non-function and early allograft failure after liver transplantation

被引:0
|
作者
Nie, Yu [1 ]
Huang, Jin-Bo [2 ,3 ,4 ]
He, Shu-Jiao [1 ]
Chen, Hua-Di [2 ,3 ,4 ]
Jia, Jun-Jun [5 ]
Li, Jing-Jing [2 ,3 ,4 ]
He, Xiao-Shun [2 ,3 ,4 ]
Zhao, Qiang [2 ,3 ,4 ]
机构
[1] Southern Med Univ, Zhujiang Hosp, Inst Regenerat Med, Gen Surg Ctr,Dept Hepatobiliary Surg 2,Guangzhou C, Guangzhou 510515, Peoples R China
[2] Sun Yat Sen Univ, Affiliated Hosp 1, Organ Transplant Ctr, Guangzhou 510080, Peoples R China
[3] Guangdong Prov Key Lab Organ Donat & Transplant Im, Guangzhou 510080, Peoples R China
[4] Guangdong Prov Int Cooperat Base Sci & Technol, Guangzhou 510080, Peoples R China
[5] Zhejiang Univ, Affiliated Hosp 1, Div Hepatobiliary Pancreat Surg, Sch Med, Hangzhou 310003, Peoples R China
基金
中国国家自然科学基金;
关键词
Primary non-function; Early allograft failure; Risk predicting model; Liver transplantation; PRIMARY GRAFT DYSFUNCTION; PRIMARY NONFUNCTION; CRITERIA; LACTATE; ABILITY; MODEL;
D O I
10.1016/j.hbpd.2023.08.0151499-3872
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Background: Primary non-function (PNF) and early allograft failure (EAF) after liver transplantation (LT) seriously affect patient outcomes. In clinical practice, effective prognostic tools for early identifying recipients at high risk of PNF and EAF were urgently needed. Recently, the Model for Early Allograft Function (MEAF), PNF score by King's College (King-PNF) and Balance-and-Risk-Lactate (BAR-Lac) score were developed to assess the risks of PNF and EAF. This study aimed to externally validate and compare the prognostic performance of these three scores for predicting PNF and EAF. Methods: A retrospective study included 720 patients with primary LT between January 2015 and December 2020. MEAF, King-PNF and BAR-Lac scores were compared using receiver operating characteristic (ROC) and the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses. Results: Of all 720 patients, 28 (3.9%) developed PNF and 67 (9.3%) developed EAF in 3 months. The overall early allograft dysfunction (EAD) rate was 39.0%. The 3-month patient mortality was 8.6% while 1-year graft-failure-free survival was 89.2%. The median MEAF, King-PNF and BAR-Lac scores were 5.0 (3.5-6.3),-2.1 (-2.6 to-1.2), and 5.0 (2.0-11.0), respectively. For predicting PNF, MEAF and King-PNF scores had excellent area under curves (AUCs) of 0.872 and 0.891, superior to BAR-Lac (AUC = 0.830). The NRI and IDI analyses confirmed that King-PNF score had the best performance in predicting PNF while MEAF served as a better predictor of EAD. The EAF risk curve and 1-year graft-failure-free survival curve showed that King-PNF was superior to MEAF and BAR-Lac scores for stratifying the risk of EAF. Conclusions: MEAF, King-PNF and BAR-Lac were validated as practical and effective risk assessment tools of PNF. King-PNF score outperformed MEAF and BAR-Lac in predicting PNF and EAF within 6 months. BAR-Lac score had a huge advantage in the prediction for PNF without post-transplant variables. Proper use of these scores will help early identify PNF, standardize grading of EAF and reasonably select clinical endpoints in relative studies. (c) 2023 First Affiliated Hospital, Zhejiang University School of Medicine in China. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:463 / 471
页数:9
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