Literature DB >> 32006022

Development and Validation of Person-Centered Cut-Points for the Figure-of-8-Walk Test of Mobility in Community-Dwelling Older Adults.

Peter C Coyle1,2, Subashan Perera3, Valerie Shuman1, Jessie VanSwearingen1, Jennifer S Brach1.   

Abstract

BACKGROUND: The Figure-of-8-Walk test (F8WT) is a performance measure of the motor skill of walking. Unlike walking speed over a straight path, it captures curved path walking, which is essential to real-world activity, but meaningful cut-points have yet to be developed for the F8WT.
METHODS: A secondary analysis of 421 community-dwelling older adults (mean age 80.7 ± 7.8), who participated in a community-based exercise clinical trial, was performed. Area under receiver operating characteristic curves (AUROCC) were calculated using baseline data, with F8WT performance discriminating different self-reported global mobility and balance dichotomies. Cut-points for the F8WT were chosen to optimize sensitivity and specificity. For validation, F8WT cut-points were applied to postintervention F8WT data. Participants were called monthly for 12 months after intervention completion to record self-reported incident falls, emergency department visits, and hospitalizations; risks of the outcomes were compared between those who performed well and poorly on the F8WT.
RESULTS: F8WT performance times of ≤9.09 seconds and ≤9.27 seconds can discriminate those with excellent (sensitivity = 0.647; specificity = 0.654) and excellent/very good global mobility (sensitivity = 0.649; specificity = 0.648), respectively. A total number of steps ≤17 on the F8WT can discriminate those with excellent/very good/good global balance (sensitivity = 0.646; specificity = 0.608). Compared to those who performed poorly, those who performed well had a lower incidence of negative outcomes: F8WT time ≤9.09 seconds = 46%-59% lower; F8WT time ≤9.27 seconds = 46%-56% lower; F8WT steps ≤17 = 44%-50% lower.
CONCLUSIONS: Clinicians may consider these preliminary cut-points to aid in their clinical decision making, but further study is needed for definitive recommendations.
© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Curved path; Performance; Psychometric properties; Receiver operating characteristic curve; Walking

Mesh:

Year:  2020        PMID: 32006022      PMCID: PMC7662178          DOI: 10.1093/gerona/glaa035

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.053


  38 in total

1.  Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery.

Authors:  J M Guralnik; L Ferrucci; C F Pieper; S G Leveille; K S Markides; G V Ostir; S Studenski; L F Berkman; R B Wallace
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2000-04       Impact factor: 6.053

2.  Co-morbidity adjustment for functional outcomes in community-dwelling older adults.

Authors:  Sally K Rigler; Stephanie Studenski; Dennis Wallace; Dean M Reker; Pamela W Duncan
Journal:  Clin Rehabil       Date:  2002-06       Impact factor: 3.477

3.  White paper: "walking speed: the sixth vital sign".

Authors:  Stacy Fritz; Michelle Lusardi
Journal:  J Geriatr Phys Ther       Date:  2009       Impact factor: 3.381

4.  The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection.

Authors:  J E Ware; C D Sherbourne
Journal:  Med Care       Date:  1992-06       Impact factor: 2.983

5.  Measurement of health status. Ascertaining the minimal clinically important difference.

Authors:  R Jaeschke; J Singer; G H Guyatt
Journal:  Control Clin Trials       Date:  1989-12

6.  A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.

Authors:  J M Guralnik; E M Simonsick; L Ferrucci; R J Glynn; L F Berkman; D G Blazer; P A Scherr; R B Wallace
Journal:  J Gerontol       Date:  1994-03

7.  Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults.

Authors:  Addie Middleton; George D Fulk; Michael W Beets; Troy M Herter; Stacy L Fritz
Journal:  J Aging Phys Act       Date:  2015-09-15       Impact factor: 1.961

8.  Straight and Curved Path Walking Among Older Adults in Primary Care: Associations With Fall-Related Outcomes.

Authors:  Sarah A Welch; Rachel E Ward; Laura A Kurlinski; Dan K Kiely; Richard Goldstein; Jessie VanSwearingen; Jennifer S Brach; Jonathan F Bean
Journal:  PM R       Date:  2015-12-28       Impact factor: 2.298

9.  The reliability and validity of measures of gait variability in community-dwelling older adults.

Authors:  Jennifer S Brach; Subashan Perera; Stephanie Studenski; Anne B Newman
Journal:  Arch Phys Med Rehabil       Date:  2008-12       Impact factor: 3.966

10.  Gait speed predicts decline in attention and psychomotor speed in older adults: the health aging and body composition study.

Authors:  Marco Inzitari; Anne B Newman; Kristine Yaffe; Robert Boudreau; Nathalie de Rekeneire; Ronald Shorr; Tamara B Harris; Caterina Rosano
Journal:  Neuroepidemiology       Date:  2007-11-27       Impact factor: 3.282

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