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      Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

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          Abstract

          Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothesized that gait features should be the most relevant variables for predicting the first fall. Clinical baseline characteristics (e.g., gender, cognitive function) were assessed in 259 home-dwelling people aged 66 to 75 that had never fallen. Likewise, global kinetic behavior of gait was recorded from 22 variables in 1036 walking tests with an accelerometric gait analysis system. Afterward, monthly telephone monitoring reported the date of the first fall over 24 months. A principal components analysis was used to assess the relationship between gait variables and fall status in four groups: non-fallers, fallers from 0 to 6 months, fallers from 6 to 12 months and fallers from 12 to 24 months. The association of significant principal components (PC) with an increased risk of first fall was then evaluated using the area under the Receiver Operator Characteristic Curve (ROC). No effect of clinical confounding variables was shown as a function of groups. An eigenvalue decomposition of the correlation matrix identified a large statistical PC1 (termed “ Global kinetics of gait pattern”), which accounted for 36.7% of total variance. Principal component loadings also revealed a PC2 (12.6% of total variance), related to the “ Global gait regularity.” Subsequent ANOVAs showed that only PC1 discriminated the fall status during the first 6 months, while PC2 discriminated the first fall onset between 6 and 12 months. After one year, any PC was associated with falls. These results were bolstered by the ROC analyses, showing good predictive models of the first fall during the first six months or from 6 to 12 months. Overall, these findings suggest that the performance of a standardized walking test at least once a year is essential for fall prevention.

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          Risk factors for falls among elderly persons living in the community.

          To study risk factors for falling, we conducted a one-year prospective investigation, using a sample of 336 persons at least 75 years of age who were living in the community. All subjects underwent detailed clinical evaluation, including standardized measures of mental status, strength, reflexes, balance, and gait; in addition, we inspected their homes for environmental hazards. Falls and their circumstances were identified during bimonthly telephone calls. During one year of follow-up, 108 subjects (32 percent) fell at least once; 24 percent of those who fell had serious injuries and 6 percent had fractures. Predisposing factors for falls were identified in linear-logistic models. The adjusted odds ratio for sedative use was 28.3; for cognitive impairment, 5.0; for disability of the lower extremities, 3.8; for palmomental reflex, 3.0; for abnormalities of balance and gait, 1.9; and for foot problems, 1.8; the lower bounds of the 95 percent confidence intervals were 1 or more for all variables. The risk of falling increased linearly with the number of risk factors, from 8 percent with none to 78 percent with four or more risk factors (P less than 0.0001). About 10 percent of the falls occurred during acute illness, 5 percent during hazardous activity, and 44 percent in the presence of environmental hazards. We conclude that falls among older persons living in the community are common and that a simple clinical assessment can identify the elderly persons who are at the greatest risk of falling.
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              Interventions for preventing falls in older people living in the community

              Cochrane Database of Systematic Reviews
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                Author and article information

                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                29 September 2013
                25 February 2014
                2014
                : 6
                : 22
                Affiliations
                [1] 1Laboratory “Motricité, Interactions, Performance” (UPRES EA 4334), University of Nantes Nantes, France
                [2] 2Up-COURTINE Lab, Centre for Neuroprosthetics and Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
                [3] 3Unité de Biologie Intégrative des Adaptations à l'Exercice (Inserm U902) Genople, Université d'Evry Val d'Essonne Évry, France
                [4] 4GABI, UMR-1313, INRA Jouy-en-Josas, France
                [5] 5Service de Rhumatologie, Centre Hospitalier de Laval Laval, France
                [6] 6Gérontopôle des Pays de la Loire, CHU de Nantes Nantes, France
                [7] 7Geriatrics Department, Centre Hospitalier Universitaire de Tours Tours, France
                Author notes

                Edited by: Hari S. Sharma, Uppsala University, Sweden

                Reviewed by: Marcia Chaves, Federal University of Rio Grande do Sul, Brazil; Shin Murakami, Touro University-California, USA

                *Correspondence: Thibault Deschamps, Laboratory “Motricité, Interactions, Performance” (E.A. 4334), University of Nantes, 25 Bis Boulevard Guy Mollet, BP 72206, 44322 Nantes Cedex 3, France e-mail: thibault.deschamps@ 123456univ-nantes.fr

                This article was submitted to the journal Frontiers in Aging Neuroscience.

                Article
                10.3389/fnagi.2014.00022
                3933787
                24611048
                05dc4a30-1830-411d-9a8c-262ec2c53447
                Copyright © 2014 Mignardot, Deschamps, Barrey, Auvinet, Berrut, Cornu, Constans and de Decker.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 August 2013
                : 06 February 2014
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 89, Pages: 13, Words: 10219
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                risk of fall,gait analysis,gait variability,gait speed,accelerometric device,fall-related injuries,home-dwelling people,principal components analysis

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