Evidence map›Paper›PMID 40474749›Full record

ArticleJournal of the American Geriatrics Society2025

Mapping the Final Journey: End-Of-Life Frailty Trajectories and Cause of Death.

Jianhong Xu, Jonathan Ka-Long Mak, Qian-Li Xue, Chenkai Wu

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jianhong XuGlobal Health Research Center, Duke Kunshan University, Kunshan, China.
Jonathan Ka-Long MakDepartment of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, China.ORCID 0000-0003-4454-8580
Qian-Li XueDepartment of Medicine Division of Geriatric Medicine and Gerontology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Chenkai WuGlobal Health Research Center, Duke Kunshan University, Kunshan, China.ORCID 0000-0002-2256-0653

Funding

Technological Assessment and Solutions Core - RC4P30AG021334 · NIA · JOHNS HOPKINS UNIVERSITY · PI Jeremy D Walston · 2003 to 2026
$33.2M
NIA NIH HHS P30 AG021334
6 · The paper itself

Abstract

backgroundFrailty changes associated with aging have been well-documented in existing research. However, there is limited evidence on how frailty progresses during the end-of-life stage. We aimed to explore trajectories of frailty in the last year of life and explore how the distribution of these trajectories differs according to the conditions leading to death.

methodsBased on national death registries linkage data in the UK Biobank, 37,465 decedents were included in the analytic sample. Monthly frailty scores were obtained for 1 year prior to death using the Hospital Frailty Risk Score (HFRS; a cumulative deficit measure of frailty). Latent class trajectory models were used to estimate trajectories of frailty. We further analyzed the distribution of these frailty trajectories across different conditions leading to death. Multinomial logistic regression models were applied to examine the associations between predictors and frailty trajectories.

resultsAmong 37,465 decedents, 2895 (7.7%) died from neurodegenerative diseases. Three distinct frailty trajectories were identified among these decedents: rapidly progressive frailty (6.9%), moderate progression of frailty (21.1%), and advanced and stable frailty (72.0%). These patterns differed significantly from those observed in decedents with other causes of death, who exhibited persistently low frailty (24.7%), intermediate and progressive frailty (46.5%), and advanced and progressive frailty (28.8%). Compared to cancer decedents, individuals with neurodegenerative diseases had higher baseline frailty and a dominant trajectory of advanced and stable frailty. Older age, lower education, and greater chronic disease burden were associated with the advanced and progressive frailty trajectory.

conclusionsFrailty trajectories at the end of life varied by cause of death, with neurodegenerative disease decedents exhibiting more severe frailty. These findings underscored the need for early identification of frailty and tailored end-of-life care strategies, particularly for individuals with neurodegenerative diseases who often experienced prolonged and severe frailty.

Indexed as

Frail ElderlyFrailtyTerminal CareAgedAged, 80 and overCause of DeathDisease ProgressionFemaleGeriatric AssessmentHumansMaleRegistriesUnited Kingdomcause of deathend‐of‐lifefrailtytrajectory

Identifiers

PMID40474749
PMCPMC13191412

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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.