Multimodal and Longitudinal Assessment of MOBility Disorders in Patients With Mild COGnitive Disorders
Multimodal and Longitudinal Assessment of MOBility Disorders in Patients With Mild COGnitive Disorders
Mild cognitive impairment (MCI) is defined by lower performance in one or more cognitive domains with preservation of independence in functional abilities. Sixteen percent of community-dwelling older people (over 65 years) live with MCI. They are both cognitively and physically vulnerable. From a cognitive perspective, they are susceptible to converting to the dementia stage at an annual rate of 10%. From a physical perspective, the proportion of slow gait or neurological gait abnormalities can reach 46% in the population with MCI. Falls in turn increase the risk of accelerated cognitive decline and the risk of institutionalization. In the absence of a curative treatment for dementia, it is essential to have an effective and personalized prevention strategy by identifying the predictive factors for falls in this at-risk population with MCI.
The research goals of this project are 1) to identify specific predictors for falls in clinic attendees with MCI in preparation for a definitive, fully powered study across France, and 2) to demonstrate the feasibility of a pragmatic fall risk assessment in MCs, whatever its setting and location.
We aim to prospectively follow-up people diagnosed with MCI and aged above 65 years old in four MCs in France (three in the North (one community-based MC), and one in the Centre) for one year.
We will identify predictors of at least one fall; of more than two falls, and of serious falls (e.g. with injuries).
Our hypotheses are that: 1) A combination of variables will predict falls, but the most important will be gait speed, the double task test and orthostatic hypotension; 2) A specific pattern of risks will exist in different subgroups. For example, in the subgroup of cerebral vascular lesions, executive functions could be the most preponderant risk factors; whereas in the absence of any lesions, the type of MCI could be the most preponderant risk factor; 3) There might be other undiscovered causes of falls, such as cardiac arrhythmia or epileptic seizures; 4) We might show some unexpected risk factors for falls such as hearing impairment and loneliness, leading to a more robust prevention strategy; 5) With the incorporation of relevant predictors, we could propose a more efficient and specific decision tree for fall risk in people with MCI.
Participants People will be recruited from the electronic medical record of MCs in three sites in France, Lille, Saint Quentin, and Tours. Lille and Tours are tertiary MCs, whereas Saint Quentin is a community-based MC. For this pilot project, we aim to recruit 417 people over two years.
The inclusion criteria are people diagnosed with MCI1, aged over 65 years and capable of walking at least 4 meters with or without aid. They are not necessarily newly diagnosed in the MC. But if they have already been followed up with in the MC, their last diagnosis should remain MCI.
The exclusion criteria are few: as any medical or psychiatric condition that precludes undertaking the study activities, and absence of informed consent from participants or their proxies. Because the final objective is to implement a feasible plan in MCs, we aim to record data as close as possible to "real world data".
The means and timing of data collection are outlined in Table 1. During the first visit after inclusion, we will record baseline variables, separated into five categories: 1) demographic characteristics, such as age, sex, education level, dwelling place, social support, any human help if relevant; 2) medical history, such as previous falls, vascular risk factors, medication, ongoing pharmacological and non-pharmacological treatment, nutrition state, sexual reproductive history, (age of menopause, hormone replacement therapy); 3) comprehensive neuropsychological assessment: global scales, verbal and non-verbal memory, executive function, visuospatial function, language, and orientation; 4) gait assessment and clinical standardized test, such as orthostatic hypotension, dual task, Short Physical Performance Battery, grip test, Timed-up and go, fear of falling (Modified Falls Efficacy Scale), hearing loss scale, mini Geriatric Depression Scale (GDS) and loneliness (UCLA Loneliness Scale); 5) complementary tests, such as EKG, 3T brain MRI (or CT if contraindication) and blood sample (Vitamin D, vitamin B1, B6, B9, B12, albumin and prealbumin). With the exception of the 4th category, all other data are already collected as part of routine practice for a new patient with MCI diagnosis. With the data collection from the 4th category, the whole evaluation will be 20 to 30 minutes longer, as compared to routine practice.
People and/or their proxies will then be asked to fill out a falls diary during the whole study. For each fall, the following items will be collected: Date; Time; Duration on the ground; Triggers; Preceding symptoms; loss of consciousness (yes/no/unsure from point of view of participants; yes/no/unwitnessed from point of view of proxies); Hospitalization or Emergency; and Injuries.
They will be contacted via a monthly phone call. The purpose of this monthly call is to remind them to fill out the falls diary and to ask about any new event(s) during the last month (new medications for instance).
In the second visit at 6 months, they will be invited to return to the MC for a short consultation. We will perform a clinical examination with gait assessment with clinical standardized tests, as detailed in the 4th category during the first visit. The clinical examination at 6 months is the usual framework in the MC for people with MCI.
The last visit at one year will include a comprehensive neuropsychological assessment, gait assessment with clinical standardized tests and blood sample. We will also collect the adherence of people and clinicians to this study, information about screen failure or lost to follow-up.
Inclusion Criteria:
Exclusion Criteria:
Yaohua.chen@chru-lille.fr0320445962