Clinical trial NCT05754021: A Practical Platform for In-Home Remote Monitoring of Cognitive Frailty
Official title: Tele-CF: A Practical Platform for Remote Monitoring of Cognitive Frailty
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Frailty
Cognitive Impairment
Dementia
Cognitive Impairment, Mild
Alzheimer Disease
Alzheimer Disease, Early Onset
Keywords: frailty
remote patient monitoring
mild cognitive impairement
early diagnosis
Telemedicine
Lead sponsor: Baylor College of Medicine
Sponsor class: OTHER
Collaborators: name: BioSensics
First posted: 2023-03-03
Enrollment: 100
Sex: ALL
Minimum age (years): 50
Maximum age (years): 95
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Ambulatory older adults (over 50 years old) willing to participate

Brief summary: Cognitive frailty, characterized by the coexistence of physical frailty and cognitive impairment, is a robust indicator of cognitive decline. Recognizing its significance, the International Association of Gerontology and Geriatrics and the International Academy on Nutrition and Aging have advocated for the use of cognitive frailty assessment as a means of monitoring the progression of mild cognitive impairment towards debilitating conditions like dementia, Alzheimer's disease, and loss of independence. Despite the clear need, a practical and remotely accessible tool for measuring cognitive frailty is currently lacking, especially within the context of telehealth visits. With telehealth video-conferencing becoming increasingly popular, accepted by healthcare payers, and preferred by older adults who may face difficulties traveling to a clinic, there is a pressing need for a software-based solution for remote cognitive frailty assessment that can be easily integrated into existing telehealth systems. This study proposes designing and validating a video-based solution to remotely monitor cognitive-frailty in older adults.

Detailed description: The investigators are proposing to evaluate the feasibility and accuracy of the Frailty Meter (FM), a cutting-edge video-based solution for remotely assessing frailty. FM determines frailty phenotypes, such as weakness, slowness, reduced range-of-motion, and exhaustion, by quantifying the results of a 20-second rapid repetitive elbow flexion-extension task captured by a standard video camera. Image processing algorithms are then used to estimate the angular velocity of the elbow, and a previously validated model is employed to calculate frailty phenotypes from the speed of elbow rotation. Furthermore, FM can also be used to assess cognitive impairment when applied during dual-task conditions, such as while performing a working memory task. The objective of this study is to validate the effectiveness of this video-based solution in tracking longitudinal changes in cognitive-motor function among older adults.

Eligibility criteria: Inclusion Criteria:

* 50 years or older
* Ambulatory
* Able and willing to provide consent
* May have a diagnosis of mild dementia or pre-dementia or mild cognitive impairment (MCI), or MoCA score of 26 or lower.

Exclusion Criteria:

* Major bilateral upper-limb disorder
* Major hearing/visual impairment
* History of stroke in the last 90 days
* Receiving hospice care
* Immobility or major mobility disorder: We will exclude those who were bedbound or unable to stand or ambulate with or without walking assistance
* inability to use telemedicine (e.g. no internet at home, severe visual or hearing problem, lack of caregiver support, etc)
* inability or unwillingness to participate in bi-monthly tele-medicine assessments or in-clinic visit (e.g., living farther than 30 mills from the clinic, unavailability of caregivers).
* significant cognitive impairment (MoCA score\<16)
* severe dementia
* severe apathy
* severe depression
* in hospice care or palliative care
* history of drug or alcohol abuse over the last six months
* unable to communicate in English or Spanish

Primary outcomes:
measure: Change in cognitive function from baseline to 6 months and 12 months
timeFrame: baseline, every 2 months, up to 12 months
measure: Change in cognitive frailty performance every other month from baseline to 12 months
timeFrame: baseline, every 2 months, up to 12 months
Secondary outcomes:
measure: Change in Physical activity from baseline to 6 months and 12 months
timeFrame: baseline, 6 month, 12 month
measure: Change in Gait speed from baseline to 6 months and 12 months
timeFrame: baseline, 6 month, 12 month
measure: Change in Balance from baseline to 6 months and 12 months
timeFrame: baseline, 6 month, 12 month
measure: Change in physical frailty from baseline to 6 months and 12 months
timeFrame: baseline, 6 months, 12 months
Other outcomes:
measure: Acceptability of tele-cognitive frailty protocol from baseline to 6 months and 12 months
timeFrame: baseline, 6 month, 12 month
Locations:
city: Houston
country: United States
facility: Baylor College of Medicine
state: Texas
Study officials:
References:
citation: Zahiri M, Wang C, Gardea M, Nguyen H, Shahbazi M, Sharafkhaneh A, Ruiz IT, Nguyen CK, Bryant MS, Najafi B. Remote Physical Frailty Monitoring-The Application of Deep Learning-Based Image Processing in Tele-Health. IEEE Access. 2020;8:219391-219399. doi: 10.1109/access.2020.3042451. Epub 2020 Dec 4.
citation: Wang C, Zahiri M, Vaziri A, Najafi B. Dual-Task Upper Extremity Motor Performance Measured by Video Processing as Cognitive-Motor Markers for Older Adults. Gerontology. 2023;69(5):650-656. doi: 10.1159/000528853. Epub 2023 Jan 13.