A Novel Machine-Learning Algorithm to Predict the Early Termination of Nutrition Support Team Follow-Up in Hospitalized Adults: A Retrospective Cohort Study.

Journal: Nutrients
PMID: 39125373

Abstract

BACKGROUND: For hospitalized adults, it is important to initiate the early reintroduction of oral food in accordance with nutrition support team guidelines. The aim of this study was to develop and validate a machine learning-based algorithm that predicts the early termination of medical nutritional therapy (the transition to oral feeding).

Authors

  • Nadir Yalçın
    Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, 06100 Ankara, Türkiye.
  • Merve Kaşıkcı
    Department of Biostatistics, Faculty of Medicine, Hacettepe University, 06100 Ankara, Türkiye.
  • Burcu Kelleci-Çakır
    Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, 06100 Ankara, Türkiye.
  • Karel Allegaert
    Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium.
  • Merve Güner-Oytun
    Department of Internal Medicine, Division of Geriatrics, Faculty of Medicine, Hacettepe University, 06100 Ankara, Türkiye.
  • Serdar Ceylan
    Department of Internal Medicine, Division of Geriatrics, Faculty of Medicine, Hacettepe University, 06100 Ankara, Türkiye.
  • Cafer Balcı
    Department of Internal Medicine, Division of Geriatrics, Faculty of Medicine, Hacettepe University, 06100 Ankara, Türkiye.
  • Kutay Demirkan
    Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, 06100 Ankara, Türkiye.
  • Meltem Halil
    Division of Geriatric Medicine, Department of Internal Medicine, Hacettepe University Faculty of Medicine, Ankara, Turkey.
  • Osman Abbasoğlu
    Clinical Nutrition Master's Program, Hacettepe University, 06100 Ankara, Türkiye.

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