ArticleJournal of general internal medicine2025
Novel Electronic Health Record Strategies to Identify Frailty Among Hospitalized Older Adults with Multiple Chronic Conditions.
Article in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Hearing Aid Use Attenuates the Association Between Hearing Loss and Frailty: A 2003-2018 NHANES Cross Sectional Analysis.Journal of the American Geriatrics Society · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
A growing number of aging adults are living with multiple chronic conditions (MCC). Older adults living with MCC are predisposed to developing frailty, a state of decreased physiologic reserve that increases risk for geriatric syndromes and associated morbidity and mortality. The electronic frailty index (eFI) is computed passively using structured EHR data and can aid in prospective screening. Unfortunately, certain diagnoses, such as functional status assessments in unstructured documentation, are less likely captured by eFI, potentially underestimating the degree of frailty. Here, we discuss current gaps for using eFI to identify frail older adults living with MCC, and artificial intelligence (AI) approaches to enhance eFI accuracy. Accurate and routine frailty assessment can aid the generalist providing care to older adults living with MCC across multiple care settings to optimize physiologic reserve for these vulnerable patients.
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Registered trials
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