Literature DB >> 29289543

Comparison of 3 Frailty Instruments in a Geriatric Acute Care Setting in a Low-Middle Income Country.

Sumika Mori Lin1, Márlon Juliano Romero Aliberti2, Sileno de Queiroz Fortes-Filho2, Juliana de Araújo Melo2, Ivan Aprahamian3, Claudia Kimie Suemoto2, Wilson Jacob Filho2.   

Abstract

OBJECTIVE: Comparison of frailty instruments in low-middle income countries, where the prevalence of frailty may be higher, is scarce. In addition, less complex diagnostic tools for frailty are important in these settings, especially in acutely ill patients, because of limited time and economic resources. We aimed to compare the performance of 3 frailty instruments for predicting adverse outcomes after 1 year of follow-up in older adults with an acute event or a chronic decompensated disease.
DESIGN: Prospective cohort study.
SETTING: Geriatric day hospital (GDH) specializing in acute care. PARTICIPANTS: A total of 534 patients (mean age 79.6 ± 8.4 years, 63% female, 64% white) admitted to the GDH. MEASUREMENTS: Frailty was assessed using the Cardiovascular Health Study (CHS) criteria, the Study of Osteoporotic Fracture (SOF) criteria, and the FRAIL (fatigue, resistance, ambulation, illnesses, and loss of weight) questionnaire. Monthly phone contacts were performed over the course of the first year to detect the following outcomes: incident disability, hospitalization, fall, and death. Multivariable Cox proportional hazard regression models were performed to evaluate the association of the outcomes with frailty as defined by the 3 instruments. In addition, we compared the accuracy of these instruments for predicting the outcomes.
RESULTS: Prevalence of frailty ranged from 37% (using FRAIL) to 51% (using CHS). After 1 year of follow-up, disability occurred in 33% of the sample, hospitalization in 40%, fall in 44%, and death in 16%. Frailty, as defined by the 3 instruments was associated with all outcomes, whereas prefrailty was associated with disability, using the SOF and FRAIL instruments, and with hospitalization using the CHS and SOF instruments. The accuracy of frailty to predict different outcomes was poor to moderate with area under the curve varying from 0.57 (for fall, with frailty defined by SOF and FRAIL) to 0.69 (for disability, with frailty defined by CHS).
CONCLUSIONS: In acutely ill patients from a low-middle income country GDH acute care unit, the CHS, SOF, and FRAIL instruments showed similar performance in predicting adverse outcomes.
Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Frailty; acute care; adverse outcomes; elderly; predictive accuracy

Mesh:

Year:  2017        PMID: 29289543     DOI: 10.1016/j.jamda.2017.10.017

Source DB:  PubMed          Journal:  J Am Med Dir Assoc        ISSN: 1525-8610            Impact factor:   4.669


  9 in total

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Authors:  H Si; Y Jin; X Qiao; X Tian; X Liu; C Wang
Journal:  J Nutr Health Aging       Date:  2020       Impact factor: 4.075

2.  Longitudinal Association between Late-Life Depression (LLD) and Frailty: Findings from a Prospective Cohort Study (MiMiCS-FRAIL).

Authors:  M K Borges; C V Romanini; N A Lima; M Petrella; D L da Costa; V N An; B N Aguirre; J R Galdeano; I C Fernandes; J F Cecato; E C Robello; R C Oude Voshaar; I Aprahamian
Journal:  J Nutr Health Aging       Date:  2021       Impact factor: 4.075

3.  Validation of the Kihon Checklist and the frailty screening index for frailty defined by the phenotype model in older Japanese adults.

Authors:  Daiki Watanabe; Tsukasa Yoshida; Yuya Watanabe; Yosuke Yamada; Motohiko Miyachi; Misaka Kimura
Journal:  BMC Geriatr       Date:  2022-06-03       Impact factor: 4.070

4.  Frailty as a Predictor of Poor Rehabilitation Outcomes among Older Patients Attending a Geriatric Day Hospital Program: An Observational Study.

Authors:  Daniel Andres; Caroline Imhoof; Markus Bürge; Gabi Jakob; Andreas Limacher; Anna K Stuck
Journal:  Int J Environ Res Public Health       Date:  2022-05-21       Impact factor: 4.614

5.  The role of frailty in predicting mortality and readmission in older adults in acute care wards: a prospective study.

Authors:  Qiukui Hao; Lixing Zhou; Biao Dong; Ming Yang; Birong Dong; Yuquan Weil
Journal:  Sci Rep       Date:  2019-02-04       Impact factor: 4.379

6.  Protein-Related Dietary Parameters and Frailty Status in Older Community-Dwellers across Different Frailty Instruments.

Authors:  Hélio J Coelho-Júnior; Riccardo Calvani; Anna Picca; Ivan O Gonçalves; Francesco Landi; Roberto Bernabei; Matteo Cesari; Marco C Uchida; Emanuele Marzetti
Journal:  Nutrients       Date:  2020-02-17       Impact factor: 5.717

7.  Design and protocol of the multimorbidity and mental health cohort study in frailty and aging (MiMiCS-FRAIL): unraveling the clinical and molecular associations between frailty, somatic disease burden and late life depression.

Authors:  Ivan Aprahamian; Ronei Luciano Mamoni; Nilva Karla Cervigne; Taize Machado Augusto; Carla Vasconcelos Romanini; Marina Petrella; Daniele Lima da Costa; Natalia Almeida Lima; Marcus K Borges; Richard C Oude Voshaar
Journal:  BMC Psychiatry       Date:  2020-12-01       Impact factor: 3.630

8.  Combined use of two frailty tools in predicting mortality in older adults.

Authors:  Daiki Watanabe; Tsukasa Yoshida; Yosuke Yamada; Yuya Watanabe; Minoru Yamada; Hiroyuki Fujita; Motohiko Miyachi; Hidenori Arai; Misaka Kimura
Journal:  Sci Rep       Date:  2022-09-03       Impact factor: 4.996

9.  Prospective GERiatric Observational (ProGERO) study: cohort design and preliminary results.

Authors:  Marcos Daniel Saraiva; Luís Fernando Rangel; Julia Lusis Lassance Cunha; Thereza Cristina Ariza Rotta; Christian Douradinho; Eugênia Jatene Bou Khazaal; Márlon Juliano Romero Aliberti; Thiago Junqueira Avelino-Silva; Daniel Apolinario; Claudia Kimie Suemoto; Wilson Jacob-Filho
Journal:  BMC Geriatr       Date:  2020-10-27       Impact factor: 3.921

  9 in total

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