Investigating the relationship between specific executive functions and functional decline among community-dwelling older adults: results from a prospective pilot study.

BACKGROUND: As cognitive functions and, more specifically, executive functions (EF) seem to influence autonomy among the elderly, we investigated the role of each of the five EF sub-components (inhibition, spontaneous flexibility, reactive flexibility, planning, and updating in working memory) for the risk of functional decline. METHOD: A total of 137 community-dwelling participants over 75 years of age were included in a prospective cohort study and assigned to three groups: individuals with neuro-degenerative cognitive disorders, those having cognitive disorders with non-degenerative aetiology, and a control group without any cognitive problems. We measured each EF sub-component and assessed functional decline by evaluating basic (b-ADL) and instrumental activities of daily living (i-ADL) at baseline and 6 months later. We conducted three separate multiple logistic regression models to examine the extent to which the five EF facets predicted overall functional decline at the end of the follow-up period. RESULTS: We found that people who exhibited a decline in b-ADLs or/and i-ADLs over 6 months had worse performance on inhibition and two flexibility tasks than those who did not experience a decline. The results suggest that decliners have more difficulties in managing unforeseen events. Inhibition and updating in working memory predicted a decline in b-ADL while spontaneous and reactive flexibilities predicted a decline in i-ADL. CONCLUSION: In our sample, specific executive dysfunctions were associated with a decline in functional status. With respect to the risk of decline in b-ADL, deficits in inhibition may represent a risk factor, as it regulates over-learned activities. Bothtypes of flexibility, which allow the shifting and generating of adaptive responses, predicted decline in i-ADL. In sum, paying more attention to particular EF profiles would help clinicians to anticipate some aspects of functional decline.

Executive dysfunctions as a good predictor of misuse of respiratory inhalers among hospitalized patients: a prospective survey.

The objectives of the study are to determine the prevalence and potential risk factors of misuse of respiratory inhalers among hospitalized patients admitted at the CHU UcL Namur, site Godinne. Using a cross-sectional design, patients using respiratory inhalers since more than 7 days were recruited from a database established by the hospital pharmacy. Inhaler technique was assessed using a standardised check-list and graded misuse as major or minor errors using previously published criteria. Demographic and clinical data were prospectively collected using standardised tools. Among the 100 consecutive patients selected for the study (median of age: 68 years), the prevalence of misuse was 40%. According to univariate analysis, main risk factors of misuse were age, executive dysfunction, a low grip strength, a low level of manual dexterity and the type of inhaler used. The best predictor of misuse according to multivariate analysis was executive dysfunction as assessed by the BREF scale (batterie rapide d'efficience frontale) (adjusted odds ratio: 1.35 [CI95%: 1.11-1.64]; p: 0.002). A BREF score ≤ 12/18 was associated with a six-fold increase of respiratory inhaler misuse risk. We conclude that executive dysfunction is associated with a higher risk of respiratory inhalers misuse. A short screening of executive function, using the BREF scale, before starting respiratory inhaler may improve the selection of inhaler devices and therefore the compliance to treatment.

[The Get-up early test, elaboration process of a new screening tool for psychomotor disadaptation syndrome]. / Élaboration d'un test de dépistage du syndrome de désadaptation psychomotrice : le Get-up early test.

Major features of the psychomotor disadaptation syndrome (SDPM) include motor skill dysfunctions with alteration of postural capabilities, walking abilities and psychomotric automatisms. Mini motor test (TMM) is the gold standard used by skilled physiotherapists in order to assess the syndrome. The aim of this article is to present the elaboration process of a new SDPM screening tool, called the Get-up early test. The test was firstly elaborated through consensus of nine experts in the geriatric field. This first 5-items version had poor inter-rater reproducibility and was therefore modified in a new 4-item version. This new version had substantial inter-rater concordance. Compared to the TMM as gold standard, in two different settings (acute ward and nursing home), with a cut-off value≥1/4, diagnostic performance was good (sensibility: 0.73 and specificity 0.88; area under curve: 0.823). The last step was to implement the screening tool in three Mobile geriatric units and we report here their experience. The Get-up early test may be suggested as a new screening tool in order to detect SDPM before more in-depth comprehensive geriatric assessment, and to early adapt the care plan.

Feature extraction and selection for objective gait analysis and fall risk assessment by accelerometry.

BACKGROUND: Falls in the elderly is nowadays a major concern because of their consequences on elderly general health and moral states. Moreover, the aging of the population and the increasing life expectancy make the prediction of falls more and more important. The analysis presented in this article makes a first step in this direction providing a way to analyze gait and classify hospitalized elderly fallers and non-faller. This tool, based on an accelerometer network and signal processing, gives objective informations about the gait and does not need any special gait laboratory as optical analysis do. The tool is also simple to use by a non expert and can therefore be widely used on a large set of patients. METHOD: A population of 20 hospitalized elderlies was asked to execute several classical clinical tests evaluating their risk of falling. They were also asked if they experienced any fall in the last 12 months. The accelerations of the limbs were recorded during the clinical tests with an accelerometer network distributed on the body. A total of 67 features were extracted from the accelerometric signal recorded during a simple 25 m walking test at comfort speed. A feature selection algorithm was used to select those able to classify subjects at risk and not at risk for several classification algorithms types. RESULTS: The results showed that several classification algorithms were able to discriminate people from the two groups of interest: fallers and non-fallers hospitalized elderlies. The classification performances of the used algorithms were compared. Moreover a subset of the 67 features was considered to be significantly different between the two groups using a t-test. CONCLUSIONS: This study gives a method to classify a population of hospitalized elderlies in two groups: at risk of falling or not at risk based on accelerometric data. This is a first step to design a risk of falling assessment system that could be used to provide the right treatment as soon as possible before the fall and its consequences. This tool could also be used to evaluate the risk several times during the revalidation procedure.