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      Subtypes of physical frailty and their long‐term outcomes: a longitudinal cohort study

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          Abstract

          Background

          Components of physical frailty cluster into subtypes, but it remains unknown how these might be associated with age‐related functional declines and multimorbidities. This study aims to investigated associations of physical frailty subtypes with functional declines and multimorbidity in a 10 year longitudinal cohort survey.

          Methods

          Complementary longitudinal cohort study used group‐based multitrajectory modelling to verify whether frailty subtypes discovered in Taiwan are presented in another aging cohort, then investigated associations of these subtypes with cognitive decline and multimorbidity. Participants aged ≥50 years were recruited from the third to sixth waves (May 2002 to July 2010) of the National Institute for Longevity Sciences‐Longitudinal Study of Aging, in Japan. People with incomplete data, pre‐frail/frail status before their index wave, and those with incomplete data or who died during follow‐up, were excluded. Group‐based trajectory analysis denoted five established physical frailty criteria as time‐varying binary variables in each wave during follow‐up. Incident frailty was classified as mobility subtype (weakness/slowness), non‐mobility subtype (weight loss/exhaustion), or low physical activity subtype. General linear modelling investigated associations of these frailty subtypes with activities of daily living, digit symbol substitution test (DSST) and Charlson Comorbidity Index (CCI) at 2 year follow‐up.

          Results

          We identified four longitudinal trajectories of physical frailty, which corroborated the distinct subtypes we discovered previously. Among 940 eligible participants, 38.0% were robust, 18.4% had mobility subtype frailty, 20.7% non‐mobility subtype, and 20.1% low physical activity subtype. People with mobility subtype frailty were older than those with other frailty subtypes or robust status and had higher prevalence of hypertension, diabetes, and heart failure. In the multivariable‐adjusted general linear models, mobility‐subtype frailty was associated with a significantly lower DSST score (point estimate −2.28, P = 0.03) and higher CCI (point estimate 0.82, P < 0.01) than the other groups.

          Conclusions

          Mobility‐subtype frailty was associated with functional declines and progression of multimorbidity; the long‐term effects of physical frailty subtypes deserve further investigation.

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          Most cited references41

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            Frailty in elderly people

            Frailty is the most problematic expression of population ageing. It is a state of vulnerability to poor resolution of homoeostasis after a stressor event and is a consequence of cumulative decline in many physiological systems during a lifetime. This cumulative decline depletes homoeostatic reserves until minor stressor events trigger disproportionate changes in health status. In landmark studies, investigators have developed valid models of frailty and these models have allowed epidemiological investigations that show the association between frailty and adverse health outcomes. We need to develop more efficient methods to detect frailty and measure its severity in routine clinical practice, especially methods that are useful for primary care. Such progress would greatly inform the appropriate selection of elderly people for invasive procedures or drug treatments and would be the basis for a shift in the care of frail elderly people towards more appropriate goal-directed care. Copyright © 2013 Elsevier Ltd. All rights reserved.
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              A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

              The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
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                Author and article information

                Contributors
                harai@ncgg.go.jp
                lkchen2@vghtpe.gov.tw
                Journal
                J Cachexia Sarcopenia Muscle
                J Cachexia Sarcopenia Muscle
                10.1007/13539.2190-6009
                JCSM
                Journal of Cachexia, Sarcopenia and Muscle
                John Wiley and Sons Inc. (Hoboken )
                2190-5991
                2190-6009
                18 June 2020
                October 2020
                : 11
                : 5 ( doiID: 10.1002/jcsm.v11.5 )
                : 1223-1231
                Affiliations
                [ 1 ] Graduate Institute of Clinical Pharmacy National Taiwan University College of Medicine Taipei Taiwan
                [ 2 ] Section of NILS‐LSA, National Center for Geriatrics and Gerontology Obu Japan
                [ 3 ] Department of Epidemiology of Aging National Center for Geriatrics and Gerontology Obu Japan
                [ 4 ] Department of Geriatrics, School of Medicine National Yang‐Ming University Taipei Taiwan
                [ 5 ] Aging and Health Research Center National Yang‐Ming University Taipei Taiwan
                [ 6 ] Center for Geriatrics and Gerontology Taipei Veterans General Hospital Taipei Taiwan
                [ 7 ] School of Pharmacy National Taiwan University College of Medicine Taipei Taiwan
                [ 8 ] Department of Pharmacy National Taiwan University Hospital Taipei Taiwan
                [ 9 ] Graduate School of Nutritional Sciences Nagoya University of Arts and Sciences Nisshin Japan
                [ 10 ] National Center for Geriatrics and Gerontology Obu Japan
                Author notes
                [*] [* ] Correspondence to: Prof Liang‐Kung Chen, Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, No. 201, Sec. 2, Shih‐Pai Road, Taipei 11217, Taiwan.

                Tel: +886‐2‐28757830, Email: lkchen2@ 123456vghtpe.gov.tw ; Prof Hidenori Arai, National Center for Geriatrics and Gerontology, 7‐430, Morioka‐cho, Obu 474‐8511, Japan.

                Tel: +81‐562‐46‐2311, Email: harai@ 123456ncgg.go.jp

                Article
                JCSM12577 JCSM-D-19-00537
                10.1002/jcsm.12577
                7567152
                32558267
                f014064c-b6e5-41d2-8df5-618484d6013a
                © 2020 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 2, Tables: 2, Pages: 9, Words: 3224
                Product
                Funding
                Funded by: Ministry of Science and Technology, Executive Yuan of Taiwan
                Award ID: MOST 107‐2634‐F‐010‐001
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                October 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.2 mode:remove_FC converted:16.10.2020

                Orthopedics
                aging,subtypes of physical frailty,mobility subtype frailty,long‐term outcome,group‐based multitrajectory model

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