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A prediction model of delayed graft function in deceased donor for renal transplant: a multi-center study from China

  • Wujun Xue
  • , Changxi Wang
  • , Jianghua Chen
  • , Xuyong Sun
  • , Xiaotong Wu
  • , Longkai Peng
  • , Zhishui Chen
  • , Qingshan Qu
  • , Xiaodong Zhang
  • , Yaowen Fu
  • , Zhen Dong
  • , Zheng Chen
  • , Guiwen Feng
  • , Tao Lin
  • , Tongyi Men
  • , Lixin Yu
  • , Qiquan Sun
  • , Yongheng Zhao
  • , Jiangqiao Zhou
  • , Li Zeng
  • Ming Zhao, Jianming Tan, Qifa Ye, Bingyi Shi, Yingzi Ming, Tongyu Zhu, Weiguo Sui, Chibing Huang, Yingxin Fu
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • First Affiliated Hospital of Sun Yat sen University
  • Zhejiang University School of Medicine
  • The Chinese People’s Liberation Army 923 Hospital
  • Second People’s Hospital of Shanxi Province
  • Central South University
  • Wuhan Tongji Hospital of Huazhong University of Science and Technology
  • Central Hospital of Zhengzhou
  • Capital Medical University
  • Jilin University
  • Qingdao University
  • Guangzhou Medical College
  • First Affiliated Hospital of Zhengzhou University
  • Sichuan University
  • Shandong University
  • Nanfang Hospital
  • Sun Yat-Sen University
  • Kunming City First People’s Hospital
  • Renmin Hospital of Wuhan University
  • Naval Medical University
  • Southern Medical University
  • The 900 Hospital of Joint Logistic Support Department of PLA
  • Zhongnan Hospital of Wuhan University
  • The Eighth Medical Center of People’s Liberation Army General Hospital
  • Zhongshan Hospital
  • The 924 Hospital of Joint Logistic Support Department of PLA
  • Chongqing Medical University
  • Tianjin First Central Hospital

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Background: Kidneys obtained from deceased donors increase the incidence of delayed graft function (DGF) after renal transplantation. Here we investigated the influence of the risk factors of donors with DGF, and developed a donor risk scoring system for DGF prediction. Methods: This retrospective study was conducted in 1807 deceased kidney donors and 3599 recipients who received donor kidneys via transplants in 29 centers in China. We quantified DGF associations with donor clinical characteristics. A donor risk scoring system was developed and validated using an independent sample set. Results: The incidence of DGF from donors was 19.0%. Six of the donor characteristics analyzed, i.e., age, cause of death, history of hypertension, terminal serum creatinine, persistence of hypotension, and cardiopulmonary resuscitation (CPR) time were risk factors for DGF. A 49-point scoring system of donor risk was established for DGF prediction and exhibited a superior degree of discrimination. External validation of DGF prediction revealed area under the receiver-operating characteristic (AUC) curves of 0.7552. Conclusions: Our study determined the deceased donor risk factors related to DGF after renal transplantation pertinent to the Chinese cohort. The scoring system developed here had superior diagnostic significance and consistency and can be used by clinicians to make evidence-based decisions on the quality of kidneys from deceased donors and guide renal transplantation therapy.

Original languageEnglish
Pages (from-to)520-529
Number of pages10
JournalRenal Failure
Volume43
Issue number1
DOIs
StatePublished - 2021

Keywords

  • Renal transplantation
  • deceased donor
  • delayed graft function
  • risk factors

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