Delayed graft function

延迟移植功能
  • 文章类型: Journal Article
    背景:我们的目标是使用无监督的机器学习方法将具有延长的冷缺血时间(CIT)的已故供体肾移植受者聚集在一起。
    方法:我们使用2015年至2019年的OPTN/UNOS数据,对CIT超过24小时的11.615例死亡供体肾移植患者进行了共识聚类分析。确定了具有临床意义的聚类特征,并比较移植后结果.
    结果:共识聚类分析确定了两个临床上不同的簇。集群1的特点是年轻,接受肾脏移植的非糖尿病患者,非高血压,KDPI评分较低的非ECD死亡捐赠者。相比之下,第2组患者年龄较大,更有可能患糖尿病.第2组接受者更有可能从KDPI较高的较老捐赠者那里接受移植。集群1中机器灌注的使用较低,集群2中CIT的使用逐渐延长。第2组移植功能延迟的发生率较高(42%vs.29%),和较低的1年患者(95%与98%)和死亡审查(95%与97%)移植物存活率比拟Cluster1。
    结论:无监督机器学习将具有延长CIT的已故供体肾移植受者分为两组,结果不同。尽管第1组具有更有利的受体和供体特征以及更好的存活率,第2组中观察到的结果也令人满意.总的来说,两个集群都显示出良好的存活率,这表明移植中心有机会逐步增加CIT。
    We aimed to cluster deceased donor kidney transplant recipients with prolonged cold ischemia time (CIT) using an unsupervised machine learning approach.
    We performed consensus cluster analysis on 11 615 deceased donor kidney transplant patients with CIT exceeding 24 h using OPTN/UNOS data from 2015 to 2019. Cluster characteristics of clinical significance were identified, and post-transplant outcomes were compared.
    Consensus cluster analysis identified two clinically distinct clusters. Cluster 1 was characterized by young, non-diabetic patients who received kidney transplants from young, non-hypertensive, non-ECD deceased donors with lower KDPI scores. In contrast, the patients in cluster 2 were older and more likely to have diabetes. Cluster 2 recipients were more likely to receive transplants from older donors with a higher KDPI. There was lower use of machine perfusion in Cluster 1 and incrementally longer CIT in Cluster 2. Cluster 2 had a higher incidence of delayed graft function (42% vs. 29%), and lower 1-year patient (95% vs. 98%) and death-censored (95% vs. 97%) graft survival compared to Cluster 1.
    Unsupervised machine learning characterized deceased donor kidney transplant recipients with prolonged CIT into two clusters with differing outcomes. Although Cluster 1 had more favorable recipient and donor characteristics and better survival, the outcomes observed in Cluster 2 were also satisfactory. Overall, both clusters demonstrated good survival suggesting opportunities for transplant centers to incrementally increase CIT.
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

    求助全文

  • 文章类型: Journal Article
    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.
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

       PDF(Pubmed)

  • 文章类型: Editorial
    暂无摘要。
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

       PDF(Sci-hub)

  • 文章类型: Editorial
    暂无摘要。
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

       PDF(Sci-hub)

公众号