Evidence map›Paper›PMID 34252094›Full record

ArticlePloS one2021

Trajectories of frailty in aging: Prospective cohort study.

Joe Verghese, Emmeline Ayers, Sanish Sathyan, Richard B Lipton, Sofiya Milman, Nir Barzilai, Cuiling Wang

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  3. Frailty, polypharmacy, deprescribing, and 23-hour activity: insights from a mouse model.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Joe VergheseDepartment of Neurology, Albert Einstein College of Medicine, Bronx, New York, United States of America.ORCID 0000-0003-4252-2547
Emmeline AyersDepartment of Neurology, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Sanish SathyanDepartment of Neurology, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Richard B LiptonDepartment of Neurology, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Sofiya MilmanDepartment of Medicine, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Nir BarzilaiDepartment of Medicine, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Cuiling WangDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmerging evidence suggests that there is significant variability in the progression of frailty in aging. We aimed to identify latent subpopulations of frailty trajectories, and examine their clinical and biological correlates.

methodsWe characterized frailty using a 41-item cumulative deficit score at baseline and annual visits up to 12 years in 681 older adults (55% women, mean age 74·6 years). Clinical risk profile and walking while talking performance as a clinical marker of trajectories were examined. Mortality risk associated with trajectories was evaluated using Cox regression adjusted for established survival predictors, and reported as hazard ratios (HR). Proteome-wide analysis was done.

findingsLatent class modeling identified 4 distinct frailty trajectories: relatively stable (34·4%) as well as mild (36·1%), moderate (24·1%) and severely frail (5·4%). Four distinct classes of frailty trajectories were also shown in an independent sample of 515 older adults (60% women, 68% White, 26% Black). The stable group took a median of 31 months to accumulate one additional deficit compared to 20 months in the severely frail group. The worst trajectories were associated with modifiable risk factors such as low education, living alone, obesity, and physical inactivity as well as slower walking while talking speed. In the pooled sample, mild (HR 2·33, 95% CI 1·30-4·18), moderate (HR 2·49, 95% CI 1·33-4·66), and severely frail trajectories (HR 5·28, 95% CI 2·68-10·41) had higher mortality compared to the stable group. Proteomic analysis showed 11 proteins in lipid metabolism and growth factor pathways associated with frailty trajectories.

conclusionFrailty shows both stable and accelerated patterns in aging, which can be distinguished clinically and biologically.

Indexed as

AgedAgingConfidence IntervalsFemaleFrailtyHumansMaleProspective StudiesProteinsProteomicsRisk FactorsSurvival AnalysisProteins

Identifiers

PMID34252094
PMCPMC8274857

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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.