Literature DB >> 33397495

Portals to frailty? Data-driven analyses detect early frailty profiles.

Linzy Bohn1, Yao Zheng2, G Peggy McFall2,3, Roger A Dixon2,3.   

Abstract

BACKGROUND: Frailty is an aging condition that reflects multisystem decline and an increased risk for adverse outcomes, including differential cognitive decline and impairment. Two prominent approaches for measuring frailty are the frailty phenotype and the frailty index. We explored a complementary data-driven approach for frailty assessment that could detect early frailty profiles (or subtypes) in relatively healthy older adults. Specifically, we tested whether (1) modalities of early frailty profiles could be empirically determined, (2) the extracted profiles were differentially related to longitudinal cognitive decline, and (3) the profile and prediction patterns were robust for males and females.
METHODS: Participants (n = 649; M age = 70.61, range 53-95) were community-dwelling older adults from the Victoria Longitudinal Study who contributed data for baseline multi-morbidity assessment and longitudinal cognitive trajectory analyses. An exploratory factor analysis on 50 multi-morbidity items produced 7 separable health domains. The proportion of deficits in each domain was calculated and used as continuous indicators in a data-driven latent profile analysis (LPA). We subsequently examined how frailty profiles related to the level and rate of change in a latent neurocognitive speed variable.
RESULTS: LPA results distinguished three profiles: not-clinically-frail (NCF; characterized by limited impairment across indicators; 84%), mobility-type frailty (MTF; characterized by impaired mobility function; 9%), and respiratory-type frailty (RTF; characterized by impaired respiratory function; 7%). These profiles showed differential neurocognitive slowing, such that MTF was associated with the steepest decline, followed by RTF, and then NCF. The baseline frailty index scores were the highest for MTF and RTF and increased over time. All observations were robust across sex.
CONCLUSIONS: A data-driven approach to early frailty assessment detected differentiable profiles that may be characterized as morbidity-intensive portals into broader and chronic frailty. Early inventions targeting mobility or respiratory deficits may have positive downstream effects on frailty progression and cognitive decline.

Entities:  

Keywords:  Frailty; Latent profile analysis; Neurocognitive speed; Trajectories; Victoria longitudinal study

Mesh:

Year:  2021        PMID: 33397495      PMCID: PMC7780374          DOI: 10.1186/s13195-020-00736-w

Source DB:  PubMed          Journal:  Alzheimers Res Ther            Impact factor:   6.982


  63 in total

1.  Fitness and frailty: opposite ends of a challenging continuum! Will the end of age discrimination make frailty assessments an imperative?

Authors:  Roman Romero-Ortuno; Diarmuid O'Shea
Journal:  Age Ageing       Date:  2013-01-24       Impact factor: 10.668

2.  An assessment of neurocognitive speed in relation to frailty.

Authors:  Darryl B Rolfson; Gordon Wilcock; Arnold Mitnitski; Elizabeth King; Celeste A de Jager; Kenneth Rockwood; Nader Fallah; Samuel D Searle
Journal:  Age Ageing       Date:  2013-01-07       Impact factor: 10.668

3.  Body mass index predicts cognitive aging trajectories selectively for females: Evidence from the Victoria Longitudinal Study.

Authors:  Linzy Bohn; G Peggy McFall; Sandra A Wiebe; Roger A Dixon
Journal:  Neuropsychology       Date:  2020-01-30       Impact factor: 3.295

4.  Physical frailty in older persons is associated with Alzheimer disease pathology.

Authors:  Aron S Buchman; Julie A Schneider; Sue Leurgans; David A Bennett
Journal:  Neurology       Date:  2008-08-12       Impact factor: 9.910

5.  Cognitive Function in Individuals With Physical Frailty but Without Dementia or Cognitive Complaints: Results From the I-Lan Longitudinal Aging Study.

Authors:  Yi-Hui Wu; Li-Kuo Liu; Wei-Ta Chen; Wei-Ju Lee; Li-Ning Peng; Pei-Ning Wang; Liang-Kung Chen
Journal:  J Am Med Dir Assoc       Date:  2015-08-28       Impact factor: 4.669

Review 6.  Frailty in elderly people.

Authors:  Andrew Clegg; John Young; Steve Iliffe; Marcel Olde Rikkert; Kenneth Rockwood
Journal:  Lancet       Date:  2013-02-08       Impact factor: 79.321

7.  Gait Speed and Grip Strength Reflect Cognitive Impairment and Are Modestly Related to Incident Cognitive Decline in Memory Clinic Patients With Subjective Cognitive Decline and Mild Cognitive Impairment: Findings From the 4C Study.

Authors:  Astrid M Hooghiemstra; Inez H G B Ramakers; Nicole Sistermans; Yolande A L Pijnenburg; Pauline Aalten; Renske E G Hamel; René J F Melis; Frans R J Verhey; Marcel G M Olde Rikkert; Philip Scheltens; Wiesje M van der Flier
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2017-06-01       Impact factor: 6.053

8.  Lung disease as a determinant of cognitive decline and dementia.

Authors:  James W Dodd
Journal:  Alzheimers Res Ther       Date:  2015-03-21       Impact factor: 6.982

9.  Subtypes of physical frailty: Latent class analysis and associations with clinical characteristics and outcomes.

Authors:  Li-Kuo Liu; Chao-Yu Guo; Wei-Ju Lee; Liang-Yu Chen; An-Chun Hwang; Ming-Hsien Lin; Li-Ning Peng; Liang-Kung Chen; Kung-Yee Liang
Journal:  Sci Rep       Date:  2017-04-11       Impact factor: 4.379

10.  Frailty as a Predictor of Cognitive Disorders: A Systematic Review and Meta-Analysis.

Authors:  Marcus Kiiti Borges; Marco Canevelli; Matteo Cesari; Ivan Aprahamian
Journal:  Front Med (Lausanne)       Date:  2019-02-19
View more
  1 in total

1.  The Flexibility of Physio-Cognitive Decline Syndrome: A Longitudinal Cohort Study.

Authors:  Yi-Cheng Lin; Chih-Ping Chung; Pei-Lin Lee; Kun-Hsien Chou; Li-Hung Chang; Szu-Ying Lin; Yi-Jung Lee; Ching-Po Lin; Pei-Ning Wang
Journal:  Front Public Health       Date:  2022-06-06
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.