Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.

Journal: Langenbeck's archives of surgery
PMID: 39753974

Abstract

BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the treatment of SSRCs. However, there are no clear indicators for selecting the NOTES approach for patients with SSRCs. We aimed to investigate the preoperative clinical determinants that influence the selection of the NOTES approach in patients with SSRCs and to construct a prediction model to assist the surgeons in selecting the NOTES approach.

Authors

  • Yuanbin Huang
    Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Xinmiao Ma
    Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Chen Shen
    Department of Foreign Languages, Xi'an Jiaotong University City College, Xi'an, China.
  • Fei Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.
  • Zhiqi Chen
    MOE Key Lab for Intelligent Networks and Network Security, School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
  • Aoyu Yang
    Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
  • Xiancheng Li
    Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China. lxc2620@163.com.

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