Department of Kidney Transplantation, Nephropathy Hospital, The First Affiliated Hospital of Xi'an Jiaotong University; Institute of Organ Transplantation, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Chin Med J (Engl). 2018 Nov 20;131(22):2651-2657. doi: 10.4103/0366-6999.245278.
Hypothermic machine perfusion (HMP) is being used more often in cardiac death kidney transplantation; however, the significance of assessing organ quality and predicting delayed graft function (DGF) by HMP parameters is still controversial. Therefore, we used a readily available HMP variable to design a scoring model that can identify the highest risk of DGF and provide the guidance and advice for organ allocation and DCD kidney assessment.
From September 1, 2012 to August 31, 2016, 366 qualified kidneys were randomly assigned to the development and validation cohorts in a 2:1 distribution. The HMP variables of the development cohort served as candidate univariate predictors for DGF. The independent predictors of DGF were identified by multivariate logistic regression analysis with a P < 0.05. According to the odds ratios (ORs) value, each HMP variable was assigned a weighted integer, and the sum of the integers indicated the total risk score for each kidney. The validation cohort was used to verify the accuracy and reliability of the scoring model.
HMP duration (OR = 1.165, 95% confidence interval [CI]: 1.008-1.360, P = 0.043), resistance (OR = 2.190, 95% CI: 1.032-10.20, P < 0.001), and flow rate (OR = 0.931, 95% CI: 0.894-0.967, P = 0.011) were the independent predictors of identified DGF. The HMP predictive score ranged from 0 to 14, and there was a clear increase in the incidence of DGF, from the low predictive score group to the very high predictive score group. We formed four increasingly serious risk categories (scores 0-3, 4-7, 8-11, and 12-14) according to the frequency associated with the different risk scores of DGF. The HMP predictive score indicates good discriminative power with a c-statistic of 0.706 in the validation cohort, and it had significantly better prediction value for DGF compared to both terminal flow (P = 0.012) and resistance (P = 0.006).
The HMP predictive score is a good noninvasive tool for assessing the quality of DCD kidneys, and it is potentially useful for physicians in making optimal decisions about the organs donated.
低温机器灌注(HMP)在心脏死亡供体肾移植中应用越来越多;然而,通过 HMP 参数评估器官质量和预测延迟移植物功能障碍(DGF)的意义仍存在争议。因此,我们使用一种现成的 HMP 变量来设计一个评分模型,该模型可以识别出 DGF 的最高风险,并为器官分配和 DCD 肾脏评估提供指导和建议。
2012 年 9 月 1 日至 2016 年 8 月 31 日,将 366 个合格的肾脏随机分配到发展和验证队列中,比例为 2:1。发展队列的 HMP 变量作为 DGF 的候选单变量预测因子。通过多元逻辑回归分析确定 DGF 的独立预测因子,P<0.05。根据比值比(OR)值,为每个 HMP 变量分配一个加权整数,每个肾脏的整数总和表示总风险评分。验证队列用于验证评分模型的准确性和可靠性。
HMP 持续时间(OR=1.165,95%置信区间[CI]:1.008-1.360,P=0.043)、阻力(OR=2.190,95%CI:1.032-10.20,P<0.001)和流量(OR=0.931,95%CI:0.894-0.967,P=0.011)是 DGF 的独立预测因子。HMP 预测评分范围为 0 至 14,DGF 的发生率从低预测评分组到高预测评分组明显增加。我们根据与不同 DGF 风险评分相关的频率形成了四个风险等级(评分 0-3、4-7、8-11 和 12-14)。在验证队列中,HMP 预测评分具有良好的判别能力,C 统计量为 0.706,与终末流量(P=0.012)和阻力(P=0.006)相比,对 DGF 具有更好的预测价值。
HMP 预测评分是评估 DCD 肾脏质量的一种很好的非侵入性工具,它可能对医生做出关于供体器官的最佳决策有用。