Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Key Laboratory of Combined Multi-organ Transplantation, Ministry of Public Health, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
Transplantation. 2020 Jan;104(1):79-89. doi: 10.1097/TP.0000000000002787.
Predicting the development of early allograft dysfunction (EAD) following liver transplantation (LT) remains challenging for transplant clinicians. The objectives of this study are to investigate the potential relationship between the protein profiles of pretransplant grafts and the onset of EAD, and then combine with clinical parameters to construct a mathematically predictive model.
Clinical data of 121 LT procedures from donation after circulatory death at the authors' center were analyzed. The expression levels of 7 studied proteins were determined by immunohistochemistry. Another independent cohort of 37 subjects was designed for further validation of the predictive model.
With an incidence of 43.0% (52/121), EAD was linked to significantly increased risk of acute kidney injury and renal replacement therapy, as well as reduced 6-month patient and liver graft survival. Allograft weight and high intrahepatic vascular endothelial growth factor (VEGF) expression were identified as independent risk factors of EAD and survival outcomes. Liver grafts with high VEGF expression exhibited delayed functional recovery within the first postoperative week. The combination of VEGF overexpression and EAD yielded the highest frequency of renal dysfunction and the worst survival. Based on allograft weight and intrahepatic VEGF expression, an EAD risk assessment model was developed. The incidence of EAD differed significantly between grafts with risk scores ≥-1.72 and <-1.72. The model functioned well in the validation cohort.
Pretransplant intrahepatic protein profiling contributes to the estimation of early graft performance and recipient outcomes following LT. The predictive model could allow for an accurate prediction of EAD.
对于移植临床医生来说,预测肝移植(LT)后早期移植物功能障碍(EAD)的发展仍然具有挑战性。本研究的目的是探讨移植前供体组织的蛋白质谱与 EAD 发病之间的潜在关系,然后结合临床参数构建数学预测模型。
分析了作者中心 121 例来自循环死亡供体的 LT 手术的临床数据。通过免疫组织化学测定 7 种研究蛋白的表达水平。还设计了另一个独立的 37 例队列,以进一步验证预测模型。
EAD 的发生率为 43.0%(52/121),与急性肾损伤和肾脏替代治疗的风险显著增加以及 6 个月患者和肝移植物存活率降低相关。供体重量和肝内血管内皮生长因子(VEGF)高表达被确定为 EAD 和生存结果的独立危险因素。高 VEGF 表达的移植物表现为术后第一周内功能恢复延迟。VEGF 过表达和 EAD 的组合导致肾功能障碍的频率最高,且生存最差。基于供体重量和肝内 VEGF 表达,建立了 EAD 风险评估模型。风险评分≥-1.72 和<-1.72 的移植物的 EAD 发生率有显著差异。该模型在验证队列中表现良好。
移植前肝内蛋白质谱有助于估计 LT 后早期移植物功能和受体结局。预测模型可以准确预测 EAD。