The DOI matches its Crossref record; 43 of the 44 references it cites were found in a registry or an index.
Transitions Between Frailty States Among Community-Living Older Persons
Open accessAbstract
BACKGROUND: Little is known about the natural course of frailty. We performed a prospective study to determine the transition rates between frailty states and to evaluate the effect of the preceding frailty state on subsequent frailty transitions. METHODS: We studied 754 community-living persons, aged 70 years or older, who were nondisabled in 4 essential activities of daily living. Frailty, assessed every 18 months for 54 months, was defined on the basis of weight loss, exhaustion, low physical activity, muscle weakness, and slow walking speed. Participants were classified as frail if they met 3 or more of these criteria, as prefrail if they met 1 or 2 of the criteria, and as nonfrail if they met none of the criteria. RESULTS: Of the 754 participants, 434 (57.6%) had at least 1 transition between any 2 of the 3 frailty states during 54 months. The rates were 36.8%, 21.5%, and 9.2% for 1, 2, and 3 transitions, respectively. During the 18-month intervals, transitions to states of greater frailty were more common (rates up to 43.3%) than transitions to states of lesser frailty (rates up to 23.0%), and the probability of transitioning from being frail to nonfrail was very low (rates, 0%-0.9%), even during an extended period. The likelihood of transitioning between frailty states was highly dependent on one's preceding frailty state. CONCLUSIONS: Frailty among older persons is a dynamic process, characterized by frequent transitions between frailty states over time. Our findings suggest ample opportunity for the prevention and remediation of frailty.
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“and moderate/severe frailty (RR 2.60, 95% CI 1.36-4.96) (95).”
From Frailty in elderly people (2013) · cites this paper as [95]
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“Risk of admission to long-term care is also increased in those with mild frailty (adjusted risk ratio (RR) 2.54, 95% CI 1.67-3.86)”
From Frailty in elderly people (2013) · cites this paper as [95]
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“The Yale Precipitating Events Project (PEP) is a cohort study based in New Haven CT that enrolled individuals aged 70 years or older.”
From A standard procedure for creating a frailty index (2008) · cites this paper as [15]
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Metadata
- Authors
- Gill, T. M., Gahbauer, E. A., Allore, H. G., & Han, L.
- Affiliations
- Yale University (US)
- Venue
- Archives of Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2006-02-27
- Volume
- 166
- Issue
- 4
- Pages
- 418
- ISSN
- 0003-9926 (ISSN-L)
- OpenAlex
- W2022181538
- Cited by
- 1,141
- References
- 44
- Citations by year
- 2026: 76 · 2025: 67 · 2024: 84 · 2023: 56 · 2022: 91 · 2021: 85 · 2020: 82 · 2019: 82 · 2018: 81 · 2017: 73 · 2016: 66 · 2015: 53 · 2014: 43 · 2013: 39 · 2012: 37
- FWCI
- 10.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Archives of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Patrick and Catherine Weldon Donaghue Medical Research Foundation
- Yale University (P30AG21342)
- National Institute on Aging (R01AG022993, R37AG017560, K24AG021507, R37AG17560, P30 AG21342, P30AG021342)
- Topics
- Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
- Health Sciences › Medicine › Physiology (medical) › Nutrition and Health in Aging
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Keywords
- frailty, pre-frailty, frailty transitions, community-dwelling older adults, frailty prevention, activities of daily living, weight loss, muscle weakness, physical activity, walking speed, exhaustion
- MeSH terms
- Aged, Aged, 80 and over, Female, Geriatrics, Humans, Male, Prospective Studies, Severity of Illness Index, Time Factors, Frail Elderly
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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