A Device for Screening of Fall Risk in the Elderly

Evaluation of Screening Accuracy of a Device for Fall Risk Assessment in the Elderly: a Cross-sectional Study With a Futility Design

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.

Study Overview

• Status: Completed
• Conditions: Gait, Unsteady; Postural Imbalance
• Intervention / Treatment: Device: OAK

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Actual): 184
• Phase: Phase 2

Contacts and Locations

Study Locations

• Italy
  • Milan, Italy, 20161
    • IRCCS Galeazzi Orthopedic Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years to 80 years (Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Able to walk without walking aids.
• Signed informed consent.

Exclusion Criteria:

• Neurological, musculoskeletal and orthopaedic disorders limiting mobility function and equilibrium. Psychiatric disorders. Any other medical condition limiting mobility function, as diabetes, obesity, serious ocular disorders (e.g. glaucoma), vestibular disorders (e.g. labyrinthitis) and proprioceptive disorders (e.g. ataxia).
• Pacemaker.
• Surgical interventions for orthopaedic disorders (e.g. knee or hip prosthesis) during the previous 6 months.
• Drug intake altering coordination and equilibrium (e.g. anti-epileptic, sedative-hypnotic drugs).
• Pregnancy.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Screening
• Allocation: Non-Randomized
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Moderate/High Risk; Participants assessed as moderate/high risk of falling according to the CDC Algorithm for Fall Risk Assessment	Device: OAK; The OAK device evaluates the fall risk through exercises assessing mobility, equilibrium and postural reaction.
Experimental: Low Risk; Participants assessed as low risk of falling according to the CDC Algorithm for Fall Risk Assessment	Device: OAK; The OAK device evaluates the fall risk through exercises assessing mobility, equilibrium and postural reaction.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Adverse events	Adverse events occurring during the assessment	Baseline
Serious adverse events	Serious adverse events occurring during the assessment	Baseline
Rate of falls	Number of falls during the prevoius 6 months	During the previous 6 months

Collaborators and Investigators

• Sponsor: Istituto Ortopedico Galeazzi
• Investigators: Principal Investigator: Giuseppe Banfi, MD, banfi.giuseppe@fondazionesanraffaele.it

Publications and helpful links

General Publications

• 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.

Study record dates

Study Major Dates

• Study Start (Actual): November 1, 2015
• Primary Completion (Actual): December 1, 2016
• Study Completion (Actual): May 1, 2017

Study Registration Dates

• First Submitted: January 12, 2016
• First Submitted That Met QC Criteria: January 12, 2016
• First Posted (Estimate): January 14, 2016

Study Record Updates

• Last Update Posted (Actual): June 29, 2017
• Last Update Submitted That Met QC Criteria: June 28, 2017
• Last Verified: February 1, 2017

More Information

Terms related to this study

• Keywords: Risk Assessment; Accidental Falls; Frail Elderly
• Additional Relevant MeSH Terms: Nervous System Diseases; Neurologic Manifestations; Gait Disorders, Neurologic
• Other Study ID Numbers: OAK