A Large Language Model Approach to Identifying Preoperative Frailty Among Older Adults From Clinical Notes.

Journal: Journal of the American Geriatrics Society
Published Date: May 15, 2025

Abstract

BACKGROUND: Patients with frailty have a higher risk of major postoperative mortality and morbidity. Identifying frailty from the medical record, however, is not straightforward since it is a multifactorial state based on multiple organ systems and a sum of factors accumulated over time. The objective of this study was to develop a large language model-based binary classifier using accurately phenotyped datasets to identify preoperative frailty from clinical notes.

Authors

  • Ying Qiu Zhou
    Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, California, USA.
  • Onkar Litake
    Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037, United States.
  • Minhthy N Meineke
    Departments of Anesthesiology.
  • Jeffrey L Tully
    Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, California.
  • Nicole Xu
    School of Medicine, University of California, San Diego, La Jolla, California, USA.
  • Waseem Abdou
    School of Medicine, University of California, San Diego, La Jolla, California, USA.
  • Rodney A Gabriel
    Department of Medicine, Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, USA.

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