Prediction of intradialytic hypotension by machine learning: A systematic review.

Journal: Journal of nephrology
Published Date: May 3, 2025

Abstract

BACKGROUND: Intradialytic hypotension is associated with increased morbidity, and mortality. Several machine learning (ML) algorithms have been recently developed to predict intradialytic hypotension. We systematically reviewed ML models employed to predict intradialytic hypotension, their performance, methodological integrity, and clinical applicability.

Authors

  • Jacob Ninan
    Department of Nephrology and Critical Care Medicine, MultiCare Capital Medical Center, Olympia, WA, USA. jacob.ninan@multicare.org.
  • Nasrin Nikravangolsefid
    Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
  • Hong Hieu Truong
    Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
  • Mariam Charkviani
    Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
  • Larry J Prokop
    Mayo Clinic Libraries, Mayo Clinic, Rochester, MN, USA.
  • Raghavan Murugan
    Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
  • Gilles Clermont
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Kianoush B Kashani
    Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Juan Pablo Domecq Garces
    Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA.

Keywords

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