Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT05944601 |
| Other study ID # |
03A203 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
March 1, 2023 |
| Est. completion date |
June 30, 2024 |
Study information
| Verified date |
May 2024 |
| Source |
Istituto Auxologico Italiano |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Spatial navigation (SN) has been reported to be one of the first cognitive domains to be
affected in Alzheimer's disease (AD), which occurs as a result of progressive neuropathology
involving specific brain areas. Moreover, the epsilon 4 isoform of Apolipoprotein-E (APOE-ε4)
has been associated with both sporadic and familial late-onset AD and patients with Mild
Cognitive Impairment (MCI) due to AD are more likely to progressively deteriorate. It will be
investigated (i) whether amyloid-positive MCI patients and APOE-ε4 carriers show subtle
changes of SN prior to the overt symptoms of AD disorientation, both in virtual and in
naturalistic open-space tasks, and (ii) the effect of a combined treatment of computer-based
and virtual reality tasks in those presenting such an impairment. Finally, (iii) threshold
algorithms based on physiological parameters and gait analysis will be set up to support
senior citizens at increased risk in maintaining their ability to independently navigate
urban environments. Different types of navigational guidance will be examined on a sample of
76 older adults by the AppleGame, and the Detour Navigation Test-modified version. It is
expected that patients with MCI due to AD and APOE-ε4 carriers show reduced SN performances
than individuals with subjective cognitive impairment and healthy controls in the
experimental tasks, with potential improvements after cognitive rehabilitation. Altered SN
performances of individuals at increased risk to develop AD may inform future advanced
technological applications in providing valuable information on threshold algorithms based on
physiological parameters and gait analysis during elders' traveling to unfamiliar locations.
Description:
Alzheimer's disease (AD) is characterized by a progressive deterioration of cognitive
functions with episodic memory loss and spatial disorientation (SD) as main features. Getting
lost in community due to AD is associated with a wide range of negative consequences, such as
a strong decrease in patients' quality of life. Episodes of SD in the elderly can increase
the possibility of being recovered in a nursing home, caused by a loss of the sense of
autonomy as well as an increase in potential injuries and, in the worst cases, even death.
Additionally, caregiver burden and increased stress, as well as scarce community resources
represent other significant problems related to patients' SD. New technological solutions,
such as virtual reality (VR), represent promising means for AD assessment and intervention,
especially when they can reveal poor ecological performances. In addition to the advanced
age, the ε4 allele of Apolipoprotein-E (APO-E) represents the most important risk factor for
AD, providing the opportunity to evaluate subclinical behavioral alterations in individuals
with subjective cognitive decline (SCD), and Mild Cognitive Impairment (MCI) due to AD, which
represents the prodromic phase of dementia. Deterioration of spatial navigation (SN)
abilities is often present early in the course of AD. Therefore, a better understanding the
neural mechanisms related to SN impairment in patients at high risk of developing AD can help
timely diagnosis and intervention. The present study, adopting a technological apparatus for
the detection and the rehabilitation of SN deficits, aims to: (i) investigate the
performances obtained on SN tasks in a sample of community-dwelling older adults grouped into
three levels (healthy controls, individuals with SCD and patients with MCI due to AD),
undergoing virtual (The AppeGame) and naturalistic open-space tests (Detour Navigation
Test-modified version); (ii) correct SN deficits by computer-based cognitive remediation
sessions and VR sessions; (iii) educate participants at high risk of developing dementia
about the opportunity offered by technology in supporting SN in exploring urban circuits.
We will analyze results of the virtual and ecological tasks of SN as a function of age, ApoE
genotype and belonging of one the three groups, using a multiple linear regression model. The
subgroups of participants at highest risk of developing AD will be administered the
aforementioned combined cognitive rehabilitation sessions, with a test/retest analysis.
Finally, through an online technological monitoring system, participants will be provided
personalized feedbacks via smartphone digital health applications connected to a wearable
equipped with sensors, in order to self-manage during their journeys alone in urban
environments thanks to the use of threshold algorithms capable of supporting their SN.
