{
  "abstract": "Background: Electronic frailty indices (eFIs) derived from structured electronic health record (EHR) data may incompletely capture functional deficits. Large language models (LLMs) can extract frailty-related information from clinical notes, but whether improved frailty ascertainment improves prognostic performance is uncertain. Objective: To compare frailty ascertainment and prognostic performance between standard and LLM-enhanced eFIs among hospitalized adults. Design: Retrospective cohort study Participants: Adults aged 50 years or older enrolled in two studies at an academic medical center and affiliated community hospital between February 2022 and April 2024. Main Measures: A validated 35-deficit diagnosis-based eFI and an LLM-enhanced eFI incorporating deficits extracted from physical therapy (PT) documentation using GPT-4o. Frailty was defined using an index threshold of 0.20 or more. The primary outcome was a composite of discharge to a facility, readmission, or death within 90 days. Multivariable logistic regression models assessed associations with the outcome, and discrimination was compared using area under the receiver operating characteristic curve (AUROC). Secondary analyses examined threshold-based classification and PT-documentation availability; prespecified sensitivity analyses evaluated population and outcome restrictions. Results: Among 616 hospitalizations, mean (SD) age was 70.9 (10.2) years, 329 (53.4%) had PT documentation, and 320 (51.9%) experienced the composite outcome. Standard and LLM-enhanced eFIs classified 216 (35.1%) and 362 (58.8%) hospitalizations as frail, respectively. Both were independently associated with the outcome (standard eFI: adjusted OR, 1.98 [95% CI, 1.39-2.83]; LLM-enhanced eFI: adjusted OR, 2.46 [95% CI, 1.75-3.47]). Discrimination did not differ significantly (AUROC, 0.636 vs 0.660; difference, 0.024 [95% CI, -0.006 to 0.053]; p=0.12). LLM enhancement increased sensitivity (42.5% to 69.4%) but decreased specificity (73.0% to 52.7%). Conclusions: LLM enhancement substantially increased frailty ascertainment and sensitivity for adverse outcomes but did not significantly improve prognostic discrimination. Thus, LLM-enhanced frailty assessment may depend on whether the intended use prioritizes broad identification of functional vulnerability or prediction of adverse post-hospital outcomes.",
  "abstract_shown": true,
  "affiliations": [
    "Brigham and Women's Hospital"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "A. K. Dalal"
    },
    {
      "name": "J. Lundstedt"
    },
    {
      "name": "N. Ernecoff"
    },
    {
      "name": "S. Plombon"
    },
    {
      "name": "S. Streiter"
    },
    {
      "name": "M. Leeson"
    },
    {
      "name": "J. Plasek"
    },
    {
      "name": "S. Mueller"
    },
    {
      "name": "J. Fiskio"
    },
    {
      "name": "L. Zhou"
    },
    {
      "name": "S. Lipsitz"
    },
    {
      "name": "A. Orkaby"
    },
    {
      "name": "J. Loewenthal"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/10h30dpcwpwb4.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.04.26367272",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26367272v1.full",
  "id": "10h30dpcwpwb4",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26367272v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health systems and quality improvement"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26367272v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/10h30dpcwpwb4.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T00:21:06Z",
      "native_id": "10.64898/2026.11.04.26367272",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26367272v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health systems and quality improvement",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Large Language Model-Enhanced Electronic Frailty Assessment and Prognostic Performance in Hospitalized Adults: A Retrospective Cohort Study",
  "title_text": "Large Language Model-Enhanced Electronic Frailty Assessment and Prognostic Performance in Hospitalized Adults: A Retrospective Cohort Study",
  "type": "preprint",
  "updated_at": "2026-11-06T12:20:47Z",
  "url": "https://research.draconitic.com/paper/10h30dpcwpwb4",
  "venue": "medRxiv",
  "versions": []
}