Prediction of dialysis adequacy using data-driven machine learning algorithms.

Journal: Renal failure
PMID: 39526333

Abstract

BACKGROUND: Adequate delivery of hemodialysis (HD), measured by the spKt/V derived from urea reduction, is an important determinant of clinical outcomes in chronic hemodialysis patients. However, the need for pre- and postdialysis blood samples prevented the assessment of spKt/V in every session.

Authors

  • Yi-Chen Liu
    Department of Nephrology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences (Xinhua Hospital Chongming Branch), Shanghai, China.
  • Ji-Ping Qing
    Department of Nephrology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai Municipality, China.
  • Rong Li
    Department of Neurology, People's Hospital of Longhua, Shenzhen, China.
  • Juan Chang
    Department of Nephrology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai Municipality, China.
  • Li-Xia Xu
    Department of Nephrology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai Municipality, China.

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