ArticleJournal of the American Geriatrics Society2026
Association Between Large Language Model-Derived Mobility Functional Status Assessment and Clinical Outcomes.
Article in Journal of the American Geriatrics Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundMobility functional status is inconsistently recorded in electronic health records. Recent advances in Large Language Models (LLMs) enable automated extraction of functional information from unstructured clinical notes. Leveraging a validated functional LLM with high performance in mobility extraction, we aimed to study the association between LLM-derived mobility functional status and clinical outcomes, including emergency department (ED) visits, hospitalizations, and mortality.
methodsIndividuals aged 60 years and older enrolled in the Mayo Clinic Study of Aging, with documented clinical notes in 2022 were included. Individuals without any identifiable functional information were excluded. The LLM-derived mobility functional status categorized mobility as impaired or unimpaired, across the five mobility domains as classified by International Classification of Functioning, Disability, and Health. Clinical outcomes in 2023 were extracted from the Rochester Epidemiology Project database. Logistic regression models assessed associations between mobility impairment and outcomes, adjusted for age, sex, Elixhauser comorbidity index, and education.
resultsThree thousand three hundred thirty-seven individuals were screened, of whom three hundred forty-three had no functional information. Two thousand nine hundred ninety-four individuals were analyzed. 79.4% had at least one mobility impairment. Higher mobility impairment is associated with older age and greater Elixhauser comorbidity. Individuals with 3 or more impairments had an increased adjusted odds of ED visits (Adjusted Odds Ratio (aOR): 2.18 (1.64, 2.90)) and hospitalizations (aOR: 2.35 (1.51, 3.65)) compared to unimpaired individuals (p < 0.001), while mortality did not demonstrate a significant association with mobility impairment.
conclusionLLM-derived mobility functional status assessment was associated with ED visits and hospitalization, but not with all-cause mortality after adjustment. Prospective validation and evaluation of incremental discrimination, calibration, and clinical utility are needed before clinical implementation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.