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This study evaluates the screening accuracy of a device (OAK) in assessing fall risk in the elderly, compared to the assessment provided by the Algorithm for Fall Risk Assessment of the Centers for Disease Control and Prevention (CDC).
The OAK device is a technologic system, based on virtual reality. It allows to quickly perform a fall risk assessment integrating clinical indexes of the Brief-BESTest (The Balance Evaluation System Test), and kinematic and posturgraphic indexes. The participants interact with the OAK device through simple exercises, then the device provides an assessment of their functional mobility, equilibrium and postural reactions.
Falls are a serious problem among the elderly. Most falls do not cause death, but 20%-30% of falls result in serious injuries representing a significant source of morbidity and mortality. Good evidence shows that many falls can be prevented. Thus, identifying people with risk of falling is crucial. The aim of this study is the evaluation of the screening accuracy of a device (OAK) in assessing fall risk in the elderly.
Participants are recruited at IRCCS Galeazzi Orthopedic Hospital in Milan, among outpatients and healthy volunteers. A brief questionnaire is administered in order to collect data relevant to the CDC Algorithm for Fall Risk Assessment. Then, participants are assessed through the OAK device. The OAK assessment is evaluated in terms of performance, accuracy (in comparison to the CDC Algorithm for Fall Risk Assessment) and safety.
Allocation: Non-Randomized, Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Screening
IRCCS Galeazzi Orthopedic Hospital
Istituto Ortopedico Galeazzi
Published on BioPortfolio: 2016-01-15T13:38:23-0500
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