Types Of Cognitive Impairment Research Articles

Exploring the latent cognitive structure in schizophrenia: implications for antipsychotic treatment responses.

Individuals diagnosed with schizophrenia present diverse degrees and types of cognitive impairment, leading to variations in responses to antipsychotic treatments. Understanding the underlying cognitive structures is crucial for assessing this heterogeneity. Utilizing latent profile analysis (LPA) enables the delineation of latent categories of cognitive function. Integrating this approach with a dimensional perspective allows for the exploration of the relationship between cognitive function and treatment response. This study examined 647 patients from two distinct cohorts. Utilizing LPA within the discovery cohort (n = 333) and the replication cohort (n = 314), latent subtypes were identified categorically. The stability of cognitive structures was evaluated employing Latent Transition Analysis (LTA). The relationship between cognitive function and treatment response were investigated by comparing Positive and Negative Syndrome Scale (PANSS) reduction rates across diverse cognitive subtypes. Furthermore, dimensional insights were gained through correlation analyses between cognitive tests and PANSS reduction rates. In terms of categorical, individuals diagnosed with schizophrenia can be categorized into three distinct subtypes: those 'without cognitive deficit', those 'with mild-moderate cognitive 'eficit', and those 'with moderate-severe cognitive deficit'. There are significant differences in PANSS reduction rates among patients belonging to these subtypes following antipsychotic treatment (p < 0.05). Furthermore, from a dimensional perspective, processing speed at baseline is positively correlated with PANSS score reduction rates at week 8/week 10 (p < 0.01). Our findings have unveiled the latent subtypes of cognitive function in schizophrenia, illuminating the association between cognitive function and responses to antipsychotic treatment from both categorical and dimensional perspectives.

Role of fronto-limbic circuit in neuropsychiatric symptoms of dementia: clinical evidence from an exploratory study.

Neuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of fronto-limbic circuit with specific NPSs in patients with various types of cognitive impairment. Of 84 participants, 27 were diagnosed with mild cognitive impairment (MCI), 41 with Alzheimer's disease (AD) dementia and 16 with non-AD dementia. In all patients we assessed regional brain morphometry using a region of interest (ROI)-based analysis. The mean cortical thickness (CT) of 20 cortical regions and the volume (V) of 4 subcortical areas of the fronto-limbic system were extracted. NPSs were rated with the Neuropsychiatric Inventory (NPI). We used multiple linear regression models adjusted for age and disease duration to identify significant associations between scores of NPI sub-domains and MRI measures of brain morphometry. All significant associations found were negative, except those between irritability and the fronto-opercular regions in MCI patients (corresponding to a 40-50% increase in CT) and between delusions and hippocampus and anterior cingulate gyrus (with a 40-60% increase). Apathy showed predominant involvement of the inferior frontal regions in AD group (a 30% decrease in CT) and of the cingulate cortex in non-AD group (a 50-60% decrease in CT). Anxiety correlated in MCI patients with the cingulate gyrus and caudate, with a CT and V decrease of about 40%, while hallucinations were associated with left enthorinal gyrus and right amygdala and temporal pole. Agitation showed associations in the AD group with the frontal regions and the temporal pole, corresponding to a 30-40% decrease in CT. Euphoria, disinhibition and eating abnormalities were associated in the MCI group with the entorhinal, para-hippocampal and fusiform gyri, the temporal pole and the amygdala (with a 40-70% decrease in CT and V). Finally, aberrant motor behavior reported a significant association with frontal and cingulate regions with a 50% decrease in CT. Our findings indicate that specific NPSs are associated with the structural involvement of the fronto-limbic circuit across different types of neurocognitive disorders. Factors, such as age and disease duration, can partly account for the variability of the associations observed.

Complement Proteins in Serum Astrocyte-Derived Exosomes Are Associated with Poststroke Cognitive Impairment in Type 2 Diabetes Mellitus Patients.

The complement system plays crucial roles in cognitive impairment and acute ischemic stroke (AIS). High levels of complement proteins in plasma astrocyte-derived exosomes (ADEs) were proven to be associated with Alzheimer's disease. We aimed to investigate the relationship of complement proteins in serum ADEs with poststroke cognitive impairment in type 2 diabetes mellitus (T2DM) patients. This study analyzed 197 T2DM patients who suffered AIS. The Beijing version of the Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. Complement proteins in serum ADEs were quantified using ELISA kits. Mediation analyses showed that C5b-9 and C3b in serum ADEs partially mediate the impact of obstructive sleep apnea (OSA), depression, small vessel disease (SVD), and infarct volume on cognitive function at the acute phase of AIS in T2DM patients. After adjusting for age, sex, time, and interaction between time and complement proteins in serum ADEs, the mixed linear regression showed that C3b and complement protein Factor B in serum ADEs were associated with MoCA scores at three-, six-, and twelve-months after AIS in T2DM patients. Our study suggested that the impact of OSA, depression, SVD, and infarct volume on cognitive impairment in the acute stage of AIS may partially mediate through the complement proteins in serum ADEs. Additionally, the complement proteins in serum ADEs at the acute phase of AIS associated with MoCA scores at three-, six-, twelve months after AIS in T2DM patients.REGISTRATION: URL: http://www.chictr.org.cn/,ChiCTR1900021544.

Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment

BACKGROUND The cognitive impairment in type 2 diabetes mellitus (T2DM) is a multifaceted and advancing state that requires further exploration to fully comprehend. Neuroinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease. AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment. METHODS To identify differentially expressed genes (DEGs) between T2DM and controls, we used data from the Gene Expression Omnibus database GSE125387. To identify T2DM module genes, we used Weighted Gene Co-Expression Network Analysis. All the genes were subject to Gene Set Enrichment Analysis. Protein-protein interaction network construction and machine learning were utilized to identify three hub genes. Immune cell infiltration analysis was performed. The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis. Validation experiments including reverse transcription quantitative real-time PCR, Western blotting and immunohistochemistry were conducted both in vivo and in vitro . To identify potential drugs associated with hub genes, we used the Comparative Toxicogenomics Database (CTD). RESULTS A total of 576 DEGs were identified using GSE125387. By taking the intersection of DEGs, T2DM module genes, and immune-related genes, a total of 59 genes associated with the immune system were identified. Afterward, machine learning was utilized to identify three hub genes (H2-T24 , Rac3 , and Tfrc ). The hub genes were associated with a variety of immune cells. The three hub genes were validated in GSE152539. Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro , consistent with the bioinformatics analysis. Additionally, 11 potential drugs associated with RAC3 and TFRC were identified based on the CTD. CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia. We validated the expression of three hub genes both in vivo and in vitro , consistent with our bioinformatics results. We discovered 11 compounds associated with RAC3 and TFRC . These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.

Association of glycogen synthase kinase-3β with cognitive impairment in type 2 diabetes patients: a six-year follow-up study.

Our previous multicenter case-control study showed that aging, up-regulation of platelet glycogen synthase kinase-3β (GSK-3β), impaired olfactory function, and ApoE ϵ4 genotype were associated with cognitive decline in type 2 diabetes mellitus (T2DM) patients. However, the causal relationship between these biomarkers and the development of cognitive decline in T2DM patients remains unclear. To further investigate this potential relationship, we designed a 6-year follow-up study in 273 T2DM patients with normal cognitive in our previous study. Baseline characteristics of the study population were compared between T2DM patients with and without incident mild cognitive impairment (MCI). We utilized Cox proportional hazard regression models to assess the risk of cognitive impairment associated with various baseline biomarkers. Receiver operating characteristic curves (ROC) were performed to evaluate the diagnostic accuracy of these biomarkers in predicting cognitive impairment. During a median follow-up time of 6 years (with a range of 4 to 9 years), 40 patients (16.13%) with T2DM developed MCI. Participants who developed incident MCI were more likely to be older, have a lower education level, have more diabetic complications, a higher percentage of ApoE ϵ4 allele and a higher level of platelet GSK-3β activity (rGSK-3β) at baseline (P<0.05). In the longitudinal follow-up, individuals with higher levels of rGSK-3β were more likely to develop incident MCI, with an adjusted hazard ratio (HR) of 1.60 (95% confidence interval [CI] 1.05, 2.46), even after controlling for potential confounders. The AUC of the combination of age, rGSK-3β and ApoEϵ4 allele predicted for incident MCI was 0.71. Platelet GSK-3β activity could be a useful biomarker to predict cognitive decline, suggesting the feasibility of identifying vulnerable population and implementing early prevention for dementia.

IDF23-0063 Association between Chinese visceral adiposity index and mild cognitive impairment in type 2 diabetic patients

IDF23-0063 Association between Chinese visceral adiposity index and mild cognitive impairment in type 2 diabetic patients

Analysis of white matter tract integrity using diffusion kurtosis imaging reveals the correlation of white matter microstructural abnormalities with cognitive impairment in type 2 diabetes mellitus.

This study aimed to identify disruptions in white matter integrity in type 2 diabetes mellitus (T2DM) patients by utilizing the white matter tract integrity (WMTI) model, which describes compartment-specific diffusivities in the intra- and extra-axonal spaces, and to investigate the relationship between WMTI metrics and clinical and cognitive measurements. A total of 73 patients with T2DM and 57 healthy controls (HCs) matched for age, sex, and education level were enrolled and underwent diffusional kurtosis imaging and cognitive assessments. Tract-based spatial statistics (TBSS) and atlas-based region of interest (ROI) analysis were performed to compare group differences in diffusional metrics, including fractional anisotropy (FA), mean diffusivity (MD), axonal water fraction (AWF), intra-axonal diffusivity (Daxon), axial extra-axonal space diffusivity (De,//), and radial extra-axonal space diffusivity (De,⊥) in multiple white matter (WM) regions. Relationships between diffusional metrics and clinical and cognitive functions were characterized. In the TBSS analysis, the T2DM group exhibited decreased FA and AWF and increased MD, De,∥, and De,⊥ in widespread WM regions in comparison with the HC group, which involved 56.28%, 32.07%, 73.77%, 50.47%, and 75.96% of the mean WM skeleton, respectively (P < 0.05, TFCE-corrected). De,⊥ detected most of the WM changes, which were mainly located in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiations, sagittal stratum, cingulum (cingulate gyrus), fornix (stria terminalis), superior longitudinal fasciculus, and uniform fasciculus. Additionally, De,⊥ in the genu of the corpus callosum was significantly correlated with worse performance in TMT-A (β = 0.433, P < 0.001) and a longer disease duration (β = 0.438, P < 0.001). WMTI is more sensitive than diffusion tensor imaging in detecting T2DM-related WM microstructure abnormalities and can provide novel insights into the possible pathological changes underlying WM degeneration in T2DM. De,⊥ could be a potential imaging marker in monitoring disease progression in the brain and early intervention treatment for the cognitive impairment in T2DM.

Effects of DPP4 Inhibitors as Neuroprotective Drug on Cognitive Impairment in Patients with Type 2 Diabetes Mellitus: A Meta-Analysis and Systematic Review.

Type 2 diabetes mellitus is considered as one of the risk factors for cognitive impairment. DPP4 inhibitors are effective drugs for the treatment of type 2 diabetes mellitus. However, the relationship between DPP4 inhibitors and cognitive dysfunction remains unclear. Therefore, we used a meta-analysis to determine the association between DPP4 inhibitors and cognitive impairment in type 2 diabetes mellitus. We systematically searched PubMed, CNKI, and the Cochrane Library at the time of establishment, 2022, and then made inclusion criteria and screened strategies to identify studies with more precise correlations. We included 10 studies with 5,583 participants. The data showed that DPP4 inhibitors significantly reduced the incidence rate of cognitive impairment in type 2 diabetes mellitus (SMD: 0.99; 95% CI [0.59, 1.38]). Furthermore, there was a linear correlation found between cognitive impairment in type 2 diabetes mellitus and fasting blood glucose, 2-hour postprandial blood glucose, and glycosylated hemoglobin. DPP4 inhibitors decreased fasting blood glucose (FPG) (SMD: 0.52; 95% CI [-0.68, -0.37]), blood glucose (2hPPG) at 2 hours after the meal (SMD: 0.82; 95% CI, [-1.2, -0.43]), and HbA1c (SMD: 0.34; 95% CI [-0.48, -0.21]). All data were statistically significant (P < 0.0001). Furthermore, we conducted subgroup analyses of the following measures at various treatment durations and ages: cognitive scores, fasting blood glucose, glycosylated hemoglobin, and two-hour postprandial blood glucose. DPP4 inhibitors significantly improved type 2 diabetic mellitus individuals' cognitive impairment and reduced fasting blood glucose, 2-hour postprandial blood glucose, and glycosylated hemoglobin. Subgroup analysis showed that people aged 60 to 70 years had better treatment effects at 0-180 days. This trial is registered with CRD42023399473.

Mini-ACE: Validation Study Among Older People in Long-Term Care.

The Mini-Addenbrooke's Cognitive Examination (M-ACE) is a valid and reliable tool that accurately differentiates various types of cognitive impairment from Normal-cognition assessed in multiple settings. However, its validity among older individuals in long-term care (LTC) was not yet established. Therefore, we sought to assess the Portuguese M-ACE's validity, reliability, and accuracy in detecting cognitive impairment no-dementia (CIND) in LTC users. A comprehensive assessment was performed on 196 LTC Portuguese users aged ≥ 60 years, among whom 71 had Normal-cognition, and 125 had CIND. The M-ACE was found to be reliable (McDonald's ω = .86, Cronbach's α = .85) and consistent over time (r = .72; ICC = .83) and between raters (k = .92). Strong correlations with related measures supported construct validity (both r = .67). The M-ACE accurately distinguished CIND from Normal-cognition with a cut-off of 17 points (AUC = 0.81, Sensitivity = 81.7%, Specificity = 74.4%). Our findings suggest that the Portuguese M-ACE is a valid and reliable cognitive assessment tool for LTC users, allowing for accurate differentiation between CIND and Normal-cognition. Thus, the M-ACE's use could contribute to the early detection and intervention of cognitive disorders, especially among older adults in LTC.

The association between blood lipids and cognitive impairment in type 2 diabetes mellitus.

The study was performed to explore the association between blood lipids and cognitive impairment in patients with type 2 diabetes mellitus (T2DM). This study included 336 patients with T2DM. Relevant clinical data including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), apolipoprotein A1, apolipoprotein B were collected, and the Mini-Mental State Examination (MMSE) score and Montreal Cognitive Assessment (MoCA) score were used to assess the cognitive function in patients with T2DM. Serum apolipoprotein A1 levels were significantly increased in T2DM patients with cognitive impairment compared with T2DM patients without cognitive impairment (p = 0.017). Serum apolipoprotein A1 levels were significantly negatively correlated with MoCA score (r = - 0.143, p = 0.009) and MMSE score (r = - 0.132, p = 0.016) in patients with T2DM. In multivariable-adjusted regression model, serum apolipoprotein A1 was independently associated with cognitive impairmentin patients with T2DM (OR = 5.201, p = 0.024). Serum apolipoprotein A1 is associated with cognitive impairment in patientswith T2DM, but not TC, TG, HDL-C, LDL-C, and apolipoprotein B, indicating that increased serum apolipoprotein A1 may be a risk factor of cognitive impairment in patients with T2DM.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus.

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Vitamin D Deficiency as a Factor Associated with Cognitive Impairment in Patients with Type 2 Diabetes Mellitus

Objective: Vitamin D as an essential nutrient is increasingly being studied and reported to have roles in diabetes and cognitive function through its antioxidant, anti-inflammatory, and neuroprotective functions. This study aimed to investigate vitamin D deficiency as a factor associated with cognitive impairment in Type 2 Diabetes Mellitus patients. Materials and Methods: This case-control study was conducted at the diabetic center and neurology outpatient clinic at Prof. Dr. I.G.N.G Ngoerah Hospital in Denpasar, Indonesia between September and December 2022. Cases had a score of &lt; 26 on the Montreal Cognitive Assessment questionnaire (Indonesian version) controls had a score ≥26. Vitamin D levels were assessed using serum 25-hydroxyvitamin D levels. The cut-off for vitamin D deficiency was obtained through the receiver operating curve characteristic. Results: In total 31 cases and 31 controls were included. The cut-off for vitamin D deficiency was &lt;24.6 ng/ml. Patients with T2DM and vitamin D deficiency had an increased association with cognitive impairment (OR 3.8; 95% CI [1.1 to 13.4]) compared to patients without vitamin D deficiency. Other independent factors associated with cognitive impairment in T2DM were low education levels (OR 5.4; 95% CI [1.3 to 22.2]) and diabetes duration of more than 5 years (OR 4.1; 95% CI [1.1 to 14.4]). Conclusion: Vitamin D deficiency is one of the factors associated with cognitive impairment in T2DM patients.

Assessment of the significance of dilated perivascular spaces and nocture arterial hypertension in the development of Alzheimer's disease

To study the severity and localization of dilated perivascular spaces (DPVS), the levels of protein markers of amyloidosis and neurodegeneration in the cerebrospinal fluid (CSF) at different daily blood pressure (BP) profiles in patients with Alzheimer's disease (AD) and other types of cognitive impairment. A total of 119 people, aged 53 to 92 years, including 55 patients with AD, 27 patients with vascular cognitive disorders (VCD), 19 patients with frontotemporal degeneration (FTD). All patients underwent BP monitoring for 24 hours using a standard oscillometric measurement method, lumbar puncture to assess Aβ-42 and Aβ-40 amyloid protein, total and phosphorylated tau protein in the CSF, magnetic resonance imaging tomography of the brain with subsequent assessment of the severity of expansion and localization of DPVS according to the G.M. Potter scale. In 58.3% of patients with AD, there is no adequate reduction in BP at night in comparison with patients with VCD (p<0.05). A significant degree of expansion of the DPVS turned out to be most typical for patients with AD: grade 3 was detected in 45.7% of patients, and the maximum, grade 4, was detected in 13.4%. At the same time, DPVSs were significantly more often detected in the group of subjects with insufficient reduction in diastolic BP (DBP) at night. A strong inverse correlation was established between the level of Aβ-42 in the CSF and the variability of DBP at night (r= -0.92; p<0.05). The decrease in the level of Aβ-42 in AD, especially at the prodromal stage, is directly related to the low variability of DBP at night, which is more characteristic of an insufficient decrease or increase in BP during night sleep. Patients with AD were characterized by an insufficient decrease in BP at night, which is associated with the severity and degree of maximum expansion of the DPVS. A decrease in the level of Aβ-42 amyloid protein in the CSF strongly correlates with the variability of DBP at night.

High glucose impairs cognitive function through inducing mitochondrial calcium overload in Treg cells

High glucose has been proved to impair cognitive function in type 2 diabetes, but the underlying mechanisms remain elusive. Here, we found that high glucose increased transcription factors' SP1 O-GlcNAcylation in regulatory T (Treg) cells. Glycosylated SP1 further enhanced HDAC2 recruitment and histone deacetylation on Na+/Ca2+/Li+ exchanger (NCLX) promoter, which downregulated NCLX expression and led to mitochondrial calcium overload and oxidative damage, thereby promoting Treg cell dysfunction, M1 microglia polarization, and diabetes-associated cognitive impairment. Importantly, GLP-1 receptor agonist alleviated these deleterious effects via GLP-1-receptor-mediated upregulation of OGA and inhibition of SP1 O-GlcNAcylation in Treg cells. Our study highlighted a link between high-glucose-mediated SP1 O-GlcNAcylation and HDAC2/NCLX signaling in control of mitochondrial calcium concentrations in Treg cells. It also revealed a mechanism for linking Treg cell dysfunction and cognitive impairment in type 2 diabetes and provides an insight into the mechanism underlying the neuroprotective effects of GLP-1 receptor agonist.

Exploring acceptance of monitoring technology in home‐based dementia care: A survey study among informal carers

AbstractBackgroundThere is growing interest to support home‐based dementia care via contactless monitoring technologies which do not require any body contact and allow informal carers to remotely monitor health and safety of people with dementia (PwD). However, sustainable implementation of such technologies requires a better understanding of informal carers’ acceptance. This study therefore aimed to explore 1) acceptance towards different use scenarios, 2) acceptance towards different contactless sensor types, and 3) differences between accepters and refusers of contactless monitoring technology for home‐based dementia care.MethodA cross‐sectional online survey was conducted among n = 304 informal carers of community‐dwelling PwD (Mage = 58.5±10.7; 71% female) in the Netherlands and Germany. Questions targeted informal carers’ general acceptance towards contactless monitoring technology, their acceptance towards 5 different use scenarios, their acceptance towards 7 different contactless sensor types, as well as their own and their care recipient’s personal characteristics. Data were examined using descriptive and bivariate analyses.ResultAcceptance towards different use scenarios for contactless monitoring technology varied significantly (p&lt;.001). The intention to use contactless monitoring technology was highest for detecting emergency situations (e.g., falls, wandering), and lowest for predicting acute situations (e.g., fall prediction). Acceptance towards different contactless sensor types varied significantly as well (p&lt;.001). RF‐based sensors (e.g radar) and light sensors were considered most acceptable, whereas camera‐based sensors and audio sensors were seen as least acceptable for home‐based dementia care. Lastly, accepters and refusers of contactless monitoring technology significantly differed regarding gender (p = .010), their relation with the PwD (p = .003), eHealth literacy (p = .025), personal innovativeness (p&lt;.001), experience with safety technology (GPS trackers, alarm buttons) (p = .002), and the PwD’s type of cognitive impairment (p = .035) and housing situation (p = .023).ConclusionOur findings can help to make better‐informed decisions during development and implementation of contactless monitoring technology to support home‐based dementia care, thereby increasing the chance of achieving a fit between technology, user, and use context.

Characterization of various type of cognitive impairment using multiomics – a pilot imaging study from a local institution

AbstractBackgroundIn addition to clinical diagnosis, multi‐modal imaging has been employed for early detection of various types of dementia. Image features from various types of images provided information for accurate diagnosis. This study aimed to evaluate the role of multiple imaging, including MRI T1W, T2W, resting state functional MRI (rs‐fMRI) and 18‐F Flutemetamol PET image in diagnosis of various types of cognitive impairments.Methods56 participants (16 Alzheimer’s Disease (AD), 10 AD type Mild Cognitive impairment (A‐MCI), 18 vascular type MCI (V‐MCI), 12 Vascular dementia (VD) and 25 Healthy Control (HC) were recruited in an local memory clinic. All types of images were re‐orientated, segmentation and normalized to the whole brain mask template. 45 brain regional volumes (Vol) were calculated from T1w using Freesurfer. Brain regional white matter hyperintensities (WMH) were obtained from T2w images. Interhemispheric functional connectivity (IFC) of brain regions were measured from rs‐fMRI. Standard uptake value (SUV) were measured and calculated from the PET images. Also, patient demographics including age, sex and HK‐MoCa score (Demo) were recorded. 70% of each group of participants were assigned to the training group, whereas the rest 30% were assigned to test group. The neural network toolbox of MATLAB was employed to build four characterization models: Model 1 based Vol and WMH; Model 2 based on Vol, WMH and IFC; Model 3 based on Vol, WMH, IFC, and demo; Model 4 based on Vol, WMH, IFC, demo and SUV.ResultsThe receiver operating characteristics (ROC) curves showed that the Model 1, 2 and 3 achieved satisfactory accuracy, with 79%, 68% and 70% respectively. While Model 4 achieved excellent accuracy of 100%. The sensitivity and specificity of each model for each group was over 75% to 100%. The model with more image features attained higher accuracy in dementia diagnosis.ConclusionArtificial neural network model with multiomics can accurately differentiate AD, A‐MCI, V‐MCI, VD and HC. Further study is suggested with more participants for models verification.

Exploring acceptance of monitoring technology in home‐based dementia care: A survey study among informal carers

AbstractBackgroundThere is growing interest to support home‐based dementia care via contactless monitoring technologies which do not require any body contact and allow informal carers to remotely monitor health and safety of people with dementia (PwD). However, sustainable implementation of such technologies requires a better understanding of informal carers’ acceptance. This study therefore aimed to explore 1) acceptance towards different use scenarios, 2) acceptance towards different contactless sensor types, and 3) differences between accepters and refusers of contactless monitoring technology for home‐based dementia care.MethodA cross‐sectional online survey was conducted among n = 304 informal carers of community‐dwelling PwD (Mage = 58.5±10.7; 71% female) in the Netherlands and Germany. Questions targeted informal carers’ general acceptance towards contactless monitoring technology, their acceptance towards 5 different use scenarios, their acceptance towards 7 different contactless sensor types, as well as their own and their care recipient’s personal characteristics. Data were examined using descriptive and bivariate analyses.ResultAcceptance towards different use scenarios for contactless monitoring technology varied significantly (p&lt;.001). The intention to use contactless monitoring technology was highest for detecting emergency situations (e.g., falls, wandering), and lowest for predicting acute situations (e.g., fall prediction). Acceptance towards different contactless sensor types varied significantly as well (p&lt;.001). RF‐based sensors (e.g radar) and light sensors were considered most acceptable, whereas camera‐based sensors and audio sensors were seen as least acceptable for home‐based dementia care. Lastly, accepters and refusers of contactless monitoring technology significantly differed regarding gender (p = .010), their relation with the PwD (p = .003), eHealth literacy (p = .025), personal innovativeness (p&lt;.001), experience with safety technology (GPS trackers, alarm buttons) (p = .002), and the PwD’s type of cognitive impairment (p = .035) and housing situation (p = .023).ConclusionOur findings can help to make better‐informed decisions during development and implementation of contactless monitoring technology to support home‐based dementia care, thereby increasing the chance of achieving a fit between technology, user, and use context.

Impact of insulin resistance on mild cognitive impairment in type 2 diabetes mellitus patients with non-alcoholic fatty liver disease

AimsInsulin resistance (IR) is a pivotal factor in the pathogenesis of type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD). Nevertheless, the impact of IR on cognitive dysfunction in T2DM patients with NAFLD remains inadequately understood. We aim to investigate the effect of IR on mild cognitive impairment (MCI) in T2DM individuals with NAFLD.Materials and methods143 T2DM individuals were categorized into Non-MCI and MCI groups, as well as Non-NAFLD and NAFLD groups. Clinical parameters and cognitive preference test outcomes were compared. Correlation and regression analyses were executed to explore the interconnections between IR and cognitive details across all T2DM patients, as well as within the subgroup of individuals with NAFLD.ResultsIn comparison to the Non-MCI group, the MCI group displayed elevated HOMA-IR levels. Similarly, the NAFLD group exhibited higher HOMA-IR levels compared to the Non-NAFLD group. Additionally, a higher prevalence of MCI was observed in the NAFLD group as opposed to the Non-NAFLD group. Notably, HOMA-IR levels were correlated with Verbal Fluency Test (VFT) and Trail Making Test-B (TMTB) scores, both related to executive functions. Elevated HOMA-IR emerged as a risk factor for MCI in the all patients. Intriguingly, increased HOMA-IR not only correlated with TMTB scores but also demonstrated an influence on TMTA scores, reflecting information processing speed function in patients with NAFLD.ConclusionIR emerges as a contributory factor to cognitive dysfunction in T2DM patients. Furthermore, it appears to underlie impaired executive function and information processing speed function in T2DM individuals with NAFLD.

Understanding acceptance of contactless monitoring technology in home-based dementia care: a cross-sectional survey study among informal caregivers.

There is a growing interest to support home-based dementia care via contactless monitoring (CM) technologies which do not require any body contact, and allow informal caregivers to remotely monitor the health and safety of people with dementia (PwD). However, sustainable implementation of CM technologies requires a better understanding of informal caregivers' acceptance. This study aimed to examine the (1) general acceptance of CM technology for home-based dementia care, (2) acceptance of different sensor types and use scenarios, and (3) differences between accepters and refusers of CM technology. A cross-sectional online survey was conducted among n = 304 informal caregivers of community-dwelling PwD [Mean(SD) age = 58.5 (10.7)] in the Netherlands and Germany. The survey contained a textual and graphical introduction to CM technologies, as well as questions targeting (1) general acceptance of CM technology, (2) acceptance of seven different contactless sensor types, (3) acceptance of five different use scenarios, and (4) caregivers' own and their care recipients' personal characteristics. Data were examined using descriptive and bivariate analyses. Participants' general acceptance of CM technology was slightly positive. We found significant differences in acceptability between contactless sensor types (p < .001). RF-based sensors (e.g., radar) and light sensors were considered most acceptable, whereas camera-based sensors and audio sensors (e.g., microphones, smart speakers) were seen as least acceptable for home-based dementia care. Furthermore, participants' acceptance of different use scenarios for CM technology varied significantly (p < .001). The intention to use CM technology was highest for detecting emergencies (e.g., falls, wandering), and lowest for predicting acute situations (e.g., fall prediction). Lastly, accepters and refusers of CM technology significantly differed regarding gender (p = .010), their relation with the PwD (p = .003), eHealth literacy (p = .025), personal innovativeness (p < .001), usage of safety technology (p = .002), and the PwD's type of cognitive impairment (p = .035) and housing situation (p = .023). Our findings can inform the development and implementation of acceptable CM technology to support home-based dementia care. Specifically, we show which sensor types and use scenarios should be prioritized from the informal caregiver's view. Additionally, our study highlights several personal characteristics associated with informal caregivers' acceptance of CM technology that should be taken into account during implementation.

Structural and Metabolic Retinal Changes Associated With Mild Cognitive Impairment in Type 2 Diabetes.

Type 2 diabetes is associated with mild cognitive impairment (MCI). Therefore, retinal and cerebral neurodegeneration may run in parallel. To assess whether there was a difference in retinal structure, vessel, and metabolic parameters in individuals with MCI. We found those with MCI had a thinner macular retinal nerve fiber layer, macular ganglion cell layer, and less venular oxygen saturation. We suggest noninvasive retinal markers may be useful to detect those at risk of cognitive dysfunction.