Introducing a machine learning algorithm for delirium prediction-the Supporting SURgery with GEriatric Co-Management and AI project (SURGE-Ahead).

Journal: Age and ageing
Published Date: May 1, 2024

Abstract

INTRODUCTION: Post-operative delirium (POD) is a common complication in older patients, with an incidence of 14-56%. To implement preventative procedures, it is necessary to identify patients at risk for POD. In the present study, we aimed to develop a machine learning (ML) model for POD prediction in older patients, in close cooperation with the PAWEL (patient safety, cost-effectiveness and quality of life in elective surgery) project.

Authors

  • Samuel Benovic
    Institute of Geriatric Research, Ulm University Medical Center, Ulm, Germany.
  • Anna H Ajlani
    Institute of the History, Philosophy and Ethics of Medicine, Ulm University, Ulm, Germany.
  • Christoph Leinert
    Institute for Geriatric Research at AGAPLESION Bethesda Ulm, Ulm University Medical Center, Ulm, Germany.
  • Marina Fotteler
    DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany.
  • Dennis Wolf
    Institute for Medical Systems Biology, Ulm University, Ulm, Germany.
  • Florian Steger
    Institute of the History, Philosophy and Ethics of Medicine, Ulm University, Ulm, Germany.
  • Hans Kestler
    Institute of Medical Systems Biology, Ulm University, Ulm, Germany.
  • Dhayana Dallmeier
    Institute for Geriatric Research at AGAPLESION Bethesda Ulm, Ulm University Medical Center, Ulm, Germany.
  • Michael Denkinger
    Institute for Geriatric Research at AGAPLESION Bethesda Ulm, Ulm University Medical Center, Ulm, Germany.
  • Gerhard W Eschweiler
    Geriatric Center, University Hospital Tübingen, Tubingen, Germany.
  • Christine Thomas
    Department of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany.
  • Thomas D Kocar
    Institute of Geriatric Research, Ulm University Medical Center, Ulm, Germany.

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