Can we predict the future of respiratory failure prediction?

Journal: Critical care (London, England)
Published Date: Jun 19, 2025

Abstract

BACKGROUND: Mortality in patients with acute respiratory failure remains high. Predicting progression of acute respiratory failure may be critical to improving patient outcomes. Machine learning, a subset of artificial intelligence is a rapidly expanding area, which is being integrated into several areas of clinical medicine. This manuscript will address the knowledge gap in predicting the onset and progression of respiratory failure, provide a review of existing prognostic strategies, and provide a clinical perspective on the implementation and future integration of machine learning into clinical care.

Authors

  • Alex K Pearce
    Division of Pulmonary, Critical Care, Sleep Medicine, and Physiology, University of California San Diego, La Jolla, CA, USA. apearce@health.ucsd.edu.
  • Shamim Nemati
    Department of Biomedical Informatics, Emory School of Medicine, Atlanta, GA, USA.
  • Ewan C Goligher
    Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
  • Catherine L Hough
    Department of Medicine, Oregon Health & Science University, Portland, OR, USA.
  • Andre L Holder
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Gabriel Wardi
    Emergency Medicine, University of California San Diego, La Jolla, California, USA.
  • Philip Yang
    Department of Medicine, Loyola University Medical Center, Maywood, IL.
  • Aaron Boussina
    Division of Biomedical Informatics, University of California San Diego, La Jolla, CA, 92093, USA.
  • Patrick G Lyons
    Department of Medicine, Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine in St Louis, 660 South Euclid Avenue, MSC 8052-43-14, St. Louis, MO 63110-1010, USA; Healthcare Innovation Lab, BJC HealthCare, St Louis, MO, USA.
  • Sarina Sahetya
    Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Atul Malhotra
    Division of Pulmonary, Critical Care, and Sleep Medicine, University of California, San Diego, La Jolla, CA. Electronic address: amalhotra@health.ucsd.edu.
  • Angela Rogers
    Division of Pulmonary, Allergy, and Critical Care Medicine, Stanford University, Stanford, CA, USA.

Keywords

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