关于移植物功能延迟(DGF)的数据和移植社区意见,以及它对结果的影响,仍然各不相同。应用无监督机器学习共识聚类方法使用OPTN/UNOS数据对具有DGF的肾移植(KT)受体的临床表型进行分类。在20.9%(n=17,073)的KT中观察到DGF,大多数肾脏的KDPI评分<85%。确定了四个不同的簇。第1组收件人很年轻,高PRA再移植。第2组接受者是年龄较大的糖尿病患者,更有可能接受较高的KDPI肾脏。第3组收件人很年轻,黑色,和非糖尿病;他们接受了较低的KDPI肾脏。第4组收件人是中年人,患有糖尿病或高血压,并接受了匹配的标准KDPI肾脏。按群集,患者一年生存率为95.7%,92.5%,97.2%和94.3%(p<0.001);一年移植物存活率为89.7%,87.1%,91.6%,和88.7%(p<0.001)。考虑到死亡审查的移植物损失后,集群之间没有差异(p=0.08)。在不同集群之间注意到受体特征的临床意义差异,然而,在考虑死亡并恢复透析后,死亡审查的移植物丢失没有差异.更多地强调受体合并症作为DGF的贡献者和结果可能有助于提高DGF高危肾脏的利用率。
Data and transplant community opinion on delayed graft function (DGF), and its impact on outcomes, remains varied. An unsupervised machine learning
consensus clustering approach was applied to categorize the clinical phenotypes of kidney transplant (KT) recipients with DGF using OPTN/UNOS data. DGF was observed in 20.9% (n = 17,073) of KT and most kidneys had a KDPI score <85%. Four distinct clusters were identified. Cluster 1 recipients were young, high PRA re-transplants. Cluster 2 recipients were older diabetics and more likely to receive higher KDPI kidneys. Cluster 3 recipients were young, black, and non-diabetic; they received lower KDPI kidneys. Cluster 4 recipients were middle-aged, had diabetes or hypertension and received well-matched standard KDPI kidneys. By cluster, one-year patient survival was 95.7%, 92.5%, 97.2% and 94.3% (p < 0.001); one-year graft survival was 89.7%, 87.1%, 91.6%, and 88.7% (p < 0.001). There were no differences between clusters after accounting for death-censored graft loss (p = 0.08). Clinically meaningful differences in recipient characteristics were noted between clusters, however, after accounting for death and return to dialysis, there were no differences in death-censored graft loss. Greater emphasis on recipient comorbidities as contributors to DGF and outcomes may help improve utilization of DGF at-risk kidneys.