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Development and validation of a novel nomogram model for predicting delayed graft function in deceased donor kidney transplantation based on pre-transplant biopsies.

Meihe LiXiaojun HuYang LiGuozhen ChenChen-Guang DingXiaohui TianPuxun TianHeli XiangXiaoming PanXiaoming DingWujun XueJin ZhengChenguang Ding
Published in: BMC nephrology (2024)
A DGF predicting nomogram was developed that incorporated donor characteristics, pre-transplantation biopsy results, and machine perfusion parameters. This nomogram can be conveniently used for preoperative individualized prediction of DGF in kidney transplant recipients.
Keyphrases
  • kidney transplantation
  • lymph node metastasis
  • ultrasound guided
  • patients undergoing
  • squamous cell carcinoma
  • deep learning
  • cell therapy
  • fine needle aspiration
  • stem cells
  • mesenchymal stem cells
  • machine learning