LifePort灌注参数联合灌注液生物标志物预测移植肾功能延迟的价值

Prognostic utility of LifePort parameters plus perfusate biomarkers during deceased donor kidney transplantation

目的分析LifePort灌注参数联合灌注液生物标志物对器官捐献供肾移植术后移植肾功能延迟(DGF)及肾功能恢复时间的预测效能。方法回顾性分析2019年1月1日至2019年8月31日期间西安交通大学第一附属医院113例接受器官捐献供肾移植的受者临床资料,根据受者随访3个月内是否发生DGF,分为DGF组(20例)和非DGF组(93例),对比两组应用LifePort进行灌注维护的参数指标、灌注液生物标志物浓度等指标,对DGF的发生率及肾功能恢复时间等情况进行总结和分析。结果本研究纳入的肾移植受者中DGF发生率为17.7%(20/113)。在以DGF为观察终点的研究中,多因素Logistic回归分析显示终末阻力[OR 1.879,95%置信区间(CI)1.145~3.56]和灌注液标志物谷胱甘肽S-转移酶(GST,OR 1.62,95%CI 1.23~2.46)分别是DGF的独立危险因素;比较GST联合终末阻力预测DGF[曲线下面积(AUC)=0.888,95%CI 0.842~0.933]与单独应用终末阻力(AUC=0.756,95%CI 0.693~0.818)或GST预测DGF(AUC=0.729,95%CI 0.591-0.806),预测准确性提高(P=0.023);在以肾功能恢复时间为观察终点的研究中,LifePort灌注参数及灌注液标志物均未表现出显著的预测效能。结论联合应用LifePort灌注参数或灌注液生物标志物可提高对DGF的预测效能。

Objective To explore the prognostic utility of LifePort perfusion parameters plus perfusate biomarkers for predicting delayed graft function(DGF)and recovery time during deceased donor kidney transplantation(KT).Methods From January 1,2019 to August 31,2019,retrospective analysis was performed for clinical data of 113 KT recipients.Based upon whether or not DGF occurred within 3 months,they were divided into two groups of DGF group(20 cases)and non-DGF(93 cases).Two groups were compared using LifePort perfusion parameters,biomarker concentrations,incidence of DGF and kidney recovery time.Statistical analysis was performed.Results The incidence of DGF was 17.7%(20/113);Multivariate Logistic regression results indicated that terminal resistance(OR 1.879,95%CI 1.145~3.56)and glutathione S-transferase(GST)(OR 1.62,95%CI 1.23~2.46)were independent risk factors for DGF;Cox hazard model revealed that terminal resistance was a risk factor for recovery time of renal function(HR=0.823,95%CI 0.735~0.981).The model combining terminal resistance and GST(AUC=0.888,95%CI 0.842~0.933)significantly improved the predictive efficacy for DGF as compared with using terminal resistance(AUC=0.756,95%CI 0.693~0.818)or GST alone(AUC=0.729,95%CI 0.591~0.806).Conclusions Combining LifePort perfusion parameters and fluid biomarkers can improve the predictive utility of DGF.