View clinical trials related to Cognitive Dysfunction.
Filter by:Cognitive impairment is a common complication in diabetes for various reasons. Although glycemic control improves cognitive impairment, different antidiabetic medications' effects on cognitive functions are still being investigated. Brain-derived neurotrophic factor (BDNF) is a neuroinflammatory marker and a member of the neurotrophin family with growth factor properties. BDNF levels have been shown to decrease in mild cognitive dysfunction or in late-onset Alzheimer's disease. Our aim is to examine the effect of SGLT2 inhibitor use on cognitive functions and BDNF levels.
The purpose of the study is to examine the properties of the Automatic Story Recall Test (ASRT) and its parallel variants, as well as letter fluency and category fluency cognitive tests. Tests will be completed in crowdsourced populations, to derive normative data, and examine test properties in demographically diverse and cognitively impaired participants recruited and tested online.
This is a multi-center, double-blind, randomized, placebo-controlled study to determine the safety, tolerability, and pharmacodynamics of SDI-118 in a once daily (QD) dosing regimen on elderly male and female study participants with cognitive decline at screening.
The AMOR-Kentucky study will examine the impact of a pharmacist-physician patient-centered medication therapy management deprescribing intervention to address inappropriate medication use in patients with cognitive impairment in underserved, lower socioeconomic populations in rural Appalachian Kentucky. The results of this study will provide valuable insights on how to expand and implement deprescribing interventions using telemedicine to reduce the prevalence and the associated healthcare costs of medication-related problems in patients with mild cognitive impairment, Alzheimer's disease and other dementias in rural areas throughout the US. The investigators will assess the potential use of telemedicine in this population by performing an initial single arm, unblinded study of the medication therapy management (MTM) describing intervention in rural/underserved Kentucky Appalachian populations with cognitive impairment and/or dementia using potentially inappropriate medications (n=50). Following initial recruitment and clinical evaluation, engaged participants will have their medication list reviewed by a pharmacist-clinician team to identify targets for deprescribing intervention. The intervention will be engaged remotely with the participant and their caregiver, and the MTM team at 4 weeks post initial evaluation, and then reinforced at a 3-month timepoint. This approach will be carried forward through a telemedicine practice at University of Kentucky that is comprised of approximately 500 patient-caregiver dyads throughout rural areas of Appalachian Kentucky.
The primary objectives are to develop and validate a classifier using multimodal passive sensor data and metrics derived from normal iPhone and Apple Watch usage to distinguish individuals with normal cognition from those with mild cognitive impairment (MCI) and to develop and validate a cognitive wellness score that tracks fluctuations in cognitive performance over time using multimodal passive sensor data and metrics derived from normal iPhone and Apple Watch usage.
The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech, can predict change in Preclinical Alzheimer's Clinical Composite with semantic processing (PACC5) between baseline and +12 month follow up across all four Arms, as measured by the coefficient of individual agreement (CIA) between the change in PACC5 and the corresponding regression model, trained on baseline speech data to predict it. Secondary objectives include (1) evaluating whether similar algorithms can predict change in PACC5 between baseline and +12 month follow up in the cognitively normal (CN) and MCI populations separately; (2) evaluating whether similar algorithms trained to regress against PACC5 scores at baseline, still regress significantly against PACC5 scores at +12 month follow-up, as measured by the coefficient of individual agreement (CIA) between the PACC5 composite at +12 months and the regression model, trained on baseline speech data to predict PACC5 scores at baseline; (3) evaluating whether similar algorithms can classify converters vs non-converters in the cognitively normal Arms (Arm 3 + 4), and fast vs slow decliners in the MCI Arms (Arm 1 + 2), as measured by the Area Under the Curve (AUC) of the receiver operating characteristic curve, sensitivity, specificity and Cohen's kappa of the corresponding binary classifiers. Secondary objectives include the objectives above, but using time points of +24 months and +36 months; and finally to evaluate whether the model performance for the objectives and outcomes above improved if the model has access to speech data at 1 week, 1 month, and 3 month timepoints.
Many residents from establishments for dependent elderly people (EHPAD) have memory disorders with behavioural problems such as agitation, aggression and anxiety, which make it difficult to assist them on a daily basis. Studies have proven the beneficial effect of the therapeutic seal robot PARO® in behavioural disorders. The present project aims to complement these data with a medico-economic study. At present, the only study of this type has been carried out in Australia, and is not transposable to France.
The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech, can predict change in PACC5 between baseline and +12 month follow up across all four Arms, as measured by the coefficient of individual agreement (CIA) between the change in PACC5 and the corresponding regression model, trained on baseline speech data to predict it. Secondary objectives include (1) evaluating whether similar algorithms can predict change in PACC5 between baseline and +12 month follow up in the cognitively normal (CN) and MCI populations separately; (2) evaluating whether similar algorithms trained to regress against PACC5 scores at baseline, still regress significantly against PACC5 scores at +12 month follow-up, as measured by the coefficient of individual agreement (CIA) between the PACC5 composite at +12 months and the regression model, trained on baseline speech data to predict PACC5 scores at baseline; (3) evaluating whether similar algorithms can classify converters vs non-converters in the cognitively normal Arms (Arm 3 + 4), and fast vs slow decliners in the MCI Arms (Arm 1 + 2), as measured by the AUC, sensitivity, specificity and Cohen's kappa of the corresponding binary classifiers. Secondary objectives include the objectives above, but using time points of +24 months and +36 months; and finally to evaluate whether the model performance for the objectives and outcomes above improved if the model has access to speech data at 1 week, 1 month, and 3 month timepoints.
The purpose of this platform study is to evaluate the effect of anti-inflammatory agents on cognition in early Alzheimer's disease. Additionally, the safety and tolerability of these anti-inflammatory agents and the effects on central and peripheral inflammation will be evaluated.
The purpose of this prospective monocenter observational study is to assess the impact of the first introduction of formal home help (personalized autonomy allowance for seniors) on the quality of life of home caregivers of elderly patients with neurocognitive impairment.