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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Moderate/High Risk | Experimental | Participants assessed as moderate/high risk of falling according to the CDC Algorithm for Fall Risk Assessment |
|
| Low Risk | Experimental | Participants assessed as low risk of falling according to the CDC Algorithm for Fall Risk Assessment |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| OAK | Device | The OAK device evaluates the fall risk through exercises assessing mobility, equilibrium and postural reaction. |
|
| Measure | Description | Time Frame |
|---|---|---|
| OAK failures in the fall risk assessment | Proportion of participants for which the OAK device is not able to provide a fall risk assessment | Baseline |
| OAK sensitivity in the fall risk assessment | Proportion of participants assessed by the OAK device as moderate/high risk of falling among those at moderate/high risk according to the CDC Algorithm for Fall Risk Assessment | Baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Adverse events | Adverse events occurring during the assessment | Baseline |
| Serious adverse events | Serious adverse events occurring during the assessment |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Giuseppe Banfi, MD | banfi.giuseppe@fondazionesanraffaele.it | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| IRCCS Galeazzi Orthopedic Hospital | Milan | 20161 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31574809 | Derived | Castellini G, Gianola S, Stucovitz E, Tramacere I, Banfi G, Moja L. Diagnostic test accuracy of an automated device as a screening tool for fall risk assessment in community-residing elderly: A STARD compliant study. Medicine (Baltimore). 2019 Sep;98(39):e17105. doi: 10.1097/MD.0000000000017105. |
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| ID | Term |
|---|---|
| D020233 | Gait Disorders, Neurologic |
| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| Baseline |
| Rate of falls | Number of falls during the prevoius 6 months | During the previous 6 months |