Literature DB >> 24411225

Functional heterogeneity and outcomes in community-dwelling women with osteoporosis, with and without a history of falls.

Yong-Hao Pua1, Peck-Hoon Ong2, Edwin Choon-Wyn Lim2, Katherin Shilin Huang2, Ross A Clark3, Manju Chandran4.   

Abstract

Falls leading to osteoporotic fracture is a substantial issue clinically. By inference from the literature, women with osteoporosis who are classified as having a history of falls may not represent a distinct homogeneous population. However, studies exploring the potential heterogeneity within fallers in women with osteoporosis are scarce. The objective of this study was to better understand the physical function characteristics of women with osteoporosis, with and without a previous history of falls, by further stratifying them based on their single-leg stance (SLS) performance. Eighty-seven consecutive, community-dwelling women with osteoporosis were recruited from the Endocrinology Clinic at Singapore General Hospital. Laboratory-based and clinic-based standing balance tests, a lower limb strength test, and the 6-min walk test (6MWT) were measured. Fallers and non-fallers did not differ in standing balance, lower limb strength nor the 6MWT (P's>0.08). SLS performance was an independent predictor of the various functional measures, after adjusting for age and body mass index. Specifically, an increase in SLS time was associated with lower standing center-of-pressure velocities, greater lower limb strength, and greater 6-min walking distance. When the two groups were stratified based on their recent history of falls and clinic-based standing balance performance (SLS time), fallers with good SLS time (>30 s) showed better functional outcomes than did non-fallers with poor SLS time (≤30 s) (P's<0.08) and comparable functional outcomes with non-fallers with good SLS time (P's>0.11). The results indicate an important heterogeneity within fallers and non-fallers with osteoporosis and they argue for a individualized approach to rehabilitation.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Balance; Falls; Muscle strength; Osteoporosis; Posture

Mesh:

Year:  2013        PMID: 24411225     DOI: 10.1016/j.gaitpost.2013.12.009

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  1 in total

1.  Comparing Machine Learning Methods to Improve Fall Risk Detection in Elderly with Osteoporosis from Balance Data.

Authors:  German Cuaya-Simbro; Alberto-I Perez-Sanpablo; Eduardo-F Morales; Ivett Quiñones Uriostegui; Lidia Nuñez-Carrera
Journal:  J Healthc Eng       Date:  2021-09-09       Impact factor: 2.682

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.