Gotaro Kojima
Does the timed up and go test predict future falls among British community-dwelling older people? Prospective cohort study nested within a randomised controlled trial
Kojima, Gotaro; Masud, Tahir; Kendrick, Denise; Morris, Richard W.; Gawler, Sheena; Treml, Jonathan; Iliffe, Steve
Authors
Tahir Masud
DENISE KENDRICK DENISE.KENDRICK@NOTTINGHAM.AC.UK
Professor of Primary Care Research
Richard W. Morris
Sheena Gawler
Jonathan Treml
Steve Iliffe
Abstract
Background
Falling is common among older people. The Timed-Up-and-Go Test (TUG) is recommended as a screening tool for falls but its predictive value has been challenged. The objectives of this study were to examine the ability of TUG to predict future falls and to estimate the optimal cut-off point to identify those with higher risk for future falls.
Methods
This is a prospective cohort study nested within a randomised controlled trial including 259 British community-dwelling older people ≥65 years undergoing usual care. TUG was measured at baseline. Prospective diaries captured falls over 24 weeks. A Receiver Operating Characteristic curve analysis determined the optimal cut-off point to classify future falls risk with sensitivity, specificity, and predictive values of TUG times. Logistic regression models examined future falls risk by TUG time.
Results
Sixty participants (23%) fell during the 24 weeks. The area under the curve was 0.58 (95% confidence interval (95% CI) = 0.49-0.67, p = 0.06), suggesting limited predictive value. The optimal cut-off point was 12.6 seconds and the corresponding sensitivity, specificity, and positive and negative predictive values were 30.5%, 89.5%, 46.2%, and 81.4%. Logistic regression models showed each second increase in TUG time (adjusted for age, gender, comorbidities, medications and past history of two falls) was significantly associated with future falls (adjusted odds ratio (OR) = 1.09, 95% CI = 1.00-1.19, p = 0.05). A TUG time ≥12.6 seconds (adjusted OR = 3.94, 95% CI = 1.69-9.21, p = 0.002) was significantly associated with future falls, after the same adjustments.
Conclusions
TUG times were significantly and independently associated with future falls. The ability of TUG to predict future falls was limited but with high specificity and negative predictive value. TUG may be most useful in ruling in those with a high risk of falling rather than as a primary measure in the ascertainment of risk.
Citation
Kojima, G., Masud, T., Kendrick, D., Morris, R. W., Gawler, S., Treml, J., & Iliffe, S. (2015). Does the timed up and go test predict future falls among British community-dwelling older people? Prospective cohort study nested within a randomised controlled trial. BMC Geriatrics, 15(38), https://doi.org/10.1186/s12877-015-0039-7
Journal Article Type | Article |
---|---|
Publication Date | Apr 3, 2015 |
Deposit Date | Oct 23, 2015 |
Publicly Available Date | Oct 23, 2015 |
Journal | BMC Geriatrics |
Electronic ISSN | 1471-2318 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 15 |
Issue | 38 |
DOI | https://doi.org/10.1186/s12877-015-0039-7 |
Keywords | Timed up and go test; Falls; Older people |
Public URL | https://nottingham-repository.worktribe.com/output/750187 |
Publisher URL | http://www.biomedcentral.com/1471-2318/15/38 |
Related Public URLs | http://creativecommons.org/licenses/by/4.0/ |
Files
Kojima BMC Geriatrics 2015.pdf
(509 Kb)
PDF
Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
You might also like
Exercise for reducing fear of falling in older people living in the community
(2014)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search