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Journal Article

Citation

Morris R, Harwood RH, Baker R, Sahota O, Armstrong S, Masud T. Age Ageing 2007; 36(1): 78-83.

Affiliation

Nottingham City Hospital, UK.

Copyright

(Copyright © 2007, Oxford University Press)

DOI

10.1093/ageing/afl147

PMID

17264139

Abstract

BACKGROUND: people with vertebral fractures are at high risk of developing hip fractures. Falls risk is important in the pathogenesis of hip fractures. AIM: to investigate if balance tests, in conjunction with a falls history, can predict falls in older women with vertebral fractures. METHODS: a cohort study of community-dwelling women aged over 60 years, with vertebral fractures. Balance tests investigated were: 5 m-timed-up-and-go-test (5 m-TUG), timed 10 m walk, TURN180 test (number of steps to turn 180 degrees ), tandem walk, ability to stand from chair with arms folded. Leg extensor power was also measured. Outcome measure: fallers (at least one fall in a 12 month follow-up period) versus non-fallers. RESULTS: one hundred and four women aged 63-91 years [mean = 78 +/- 7], were recruited. Eighty-six (83%) completed the study. Four variables were significantly associated with fallers: previous recurrent faller (2+ falls) [OR = 6.52; 95% CI = 1.69-25.22], 5 m-TUG test [OR = 1.03; 1.00-1.06], timed 10 m walk [OR = 1.07; 1.01-1.13] and the TURN180 test [OR = 1.22; 1.00-1.49] [P <0.05]. Multi-variable analysis showed that only two variables, previous recurrent faller [OR = 5.60; 1.40-22.45] and the 5 m-TUG test [OR = 1.04; 1.00-1.08], were independently significantly associated with fallers. The optimal cut-off time for performing the 5 m-TUG test in predicting fallers was 30 s (area under ROC = 60%). Combining previous recurrent faller with the 5 m-TUG improved prediction of fallers [OR = 16.79, specificity = 100%, sensitivity = 13%]. CONCLUSIONS: a previous history of recurrent falls and the inability to perform the 5 m-TUG test within 30 s predicted falls in older women with vertebral fractures. Combining these two measures can predict fallers with a high degree of specificity (although a low sensitivity), allowing the identification of a group of patients suitable for fall and fracture prevention measures.

Language: en

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