A combination of clinical balance measures and FRAX® to improve identification of high-risk fallers
(2016) In BMC Geriatrics 16(1).- Abstract
Background: The FRAX® algorithm quantifies a patient's 10-year probability of a hip or major osteoporotic fracture without taking an individual's balance into account. Balance measures assess the functional ability of an individual and the FRAX® algorithm is a model that integrates the individual patients clinical risk factors [not balance] and bone mineral density. Thus, clinical balance measures capture aspects that the FRAX® algorithm does not, and vice versa. It is therefore possible that combining FRAX® and clinical balance measures can improve the identification of patients at high fall risk and thereby high fracture risk. Our study aim was to explore whether there is an association between clinical balance measures and fracture... (More)
Background: The FRAX® algorithm quantifies a patient's 10-year probability of a hip or major osteoporotic fracture without taking an individual's balance into account. Balance measures assess the functional ability of an individual and the FRAX® algorithm is a model that integrates the individual patients clinical risk factors [not balance] and bone mineral density. Thus, clinical balance measures capture aspects that the FRAX® algorithm does not, and vice versa. It is therefore possible that combining FRAX® and clinical balance measures can improve the identification of patients at high fall risk and thereby high fracture risk. Our study aim was to explore whether there is an association between clinical balance measures and fracture prediction obtained from FRAX®. Method: A cross-sectional study design was used where post hoc was performed on a dataset of 82 participants (54 to 89 years of age, mean age 71.4, 77 female), with a fall-related wrist-fracture between 2008 and 2012. Balance was measured by tandem stance, standing one leg, walking in the figure of eight, walking heel to toe on a line, walking as fast as possible for 30 m and five times sit to stand balance measures [tandem stance and standing one leg measured first with open and then with closed eyes] and each one analyzed for bivariate relations with the 10-year probability values for hip and major osteoporotic fractures as calculated by FRAX® using Spearman's rank correlation test. Results: Individuals with high FRAX® values had poor outcome in balance measures; however the significance level of the correlation differed between tests. Standing one leg eyes closed had strongest correlation to FRAX® (0.610 p = <0.01) and Five times sit to stand was the only test that did not correlate with FRAX® (0.013). Conclusion: This study showed that there is an association between clinical balance measures and FRAX®. Hence, the use of clinical balance measures and FRAX® in combination, might improve the identification of individuals with high risk of falls and thereby following fractures. Results enable healthcare providers to optimize treatment and prevention of fall-related fractures. Trial registration: The study has been registered in Clinical Trials.gov, registration number NCT00988572.
(Less)
- author
- Najafi, David A. ; Dahlberg, Leif E. LU and Hansson, Eva Ekvall LU
- organization
- publishing date
- 2016-05-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Balance, Falls, Fracture, FRAX®
- in
- BMC Geriatrics
- volume
- 16
- issue
- 1
- article number
- 94
- publisher
- BioMed Central (BMC)
- external identifiers
-
- wos:000375806100002
- pmid:27142632
- scopus:84978993739
- ISSN
- 1471-2318
- DOI
- 10.1186/s12877-016-0266-6
- language
- English
- LU publication?
- yes
- id
- 22371fe6-21dc-4ba6-b207-afcc3f3a5810
- date added to LUP
- 2016-09-08 15:18:26
- date last changed
- 2024-01-04 12:11:30
@article{22371fe6-21dc-4ba6-b207-afcc3f3a5810,
abstract = {{<p>Background: The FRAX® algorithm quantifies a patient's 10-year probability of a hip or major osteoporotic fracture without taking an individual's balance into account. Balance measures assess the functional ability of an individual and the FRAX® algorithm is a model that integrates the individual patients clinical risk factors [not balance] and bone mineral density. Thus, clinical balance measures capture aspects that the FRAX® algorithm does not, and vice versa. It is therefore possible that combining FRAX® and clinical balance measures can improve the identification of patients at high fall risk and thereby high fracture risk. Our study aim was to explore whether there is an association between clinical balance measures and fracture prediction obtained from FRAX®. Method: A cross-sectional study design was used where post hoc was performed on a dataset of 82 participants (54 to 89 years of age, mean age 71.4, 77 female), with a fall-related wrist-fracture between 2008 and 2012. Balance was measured by tandem stance, standing one leg, walking in the figure of eight, walking heel to toe on a line, walking as fast as possible for 30 m and five times sit to stand balance measures [tandem stance and standing one leg measured first with open and then with closed eyes] and each one analyzed for bivariate relations with the 10-year probability values for hip and major osteoporotic fractures as calculated by FRAX® using Spearman's rank correlation test. Results: Individuals with high FRAX® values had poor outcome in balance measures; however the significance level of the correlation differed between tests. Standing one leg eyes closed had strongest correlation to FRAX® (0.610 p = <0.01) and Five times sit to stand was the only test that did not correlate with FRAX® (0.013). Conclusion: This study showed that there is an association between clinical balance measures and FRAX®. Hence, the use of clinical balance measures and FRAX® in combination, might improve the identification of individuals with high risk of falls and thereby following fractures. Results enable healthcare providers to optimize treatment and prevention of fall-related fractures. Trial registration: The study has been registered in Clinical Trials.gov, registration number NCT00988572.</p>}},
author = {{Najafi, David A. and Dahlberg, Leif E. and Hansson, Eva Ekvall}},
issn = {{1471-2318}},
keywords = {{Balance; Falls; Fracture; FRAX®}},
language = {{eng}},
month = {{05}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Geriatrics}},
title = {{A combination of clinical balance measures and FRAX® to improve identification of high-risk fallers}},
url = {{http://dx.doi.org/10.1186/s12877-016-0266-6}},
doi = {{10.1186/s12877-016-0266-6}},
volume = {{16}},
year = {{2016}},
}