Cognitive Impairment Research Articles

Using a Device-Free Wi-Fi Sensing System to Assess Daily Activities and Mobility in Low-Income Older Adults: Protocol for a Feasibility Study.

Older adults belonging to racial or ethnic minorities with low socioeconomic status are at an elevated risk of developing dementia, but resources for assessing functional decline and detecting cognitive impairment are limited. Cognitive impairment affects the ability to perform daily activities and mobility behaviors. Traditional assessment methods have drawbacks, so smart home technologies (SmHT) have emerged to offer objective, high-frequency, and remote monitoring. However, these technologies usually rely on motion sensors that cannot identify specific activity types. This group often lacks access to these technologies due to limited resources and technology experience. There is a need to develop new sensing technology that is discreet, affordable, and requires minimal user engagement to characterize and quantify various in-home activities. Furthermore, it is essential to explore the feasibility of developing machine learning (ML) algorithms for SmHT through collaborations between clinical researchers and engineers and involving minority, low-income older adults for novel sensor development. This study aims to examine the feasibility of developing a novel channel state information-based device-free, low-cost Wi-Fi sensing system, and associated ML algorithms for localizing and recognizing different patterns of in-home activities and mobility in residents of low-income senior housing with and without mild cognitive impairment. This feasibility study was conducted in collaboration with a wellness care group, which serves the healthy aging needs of low-income housing residents. Prior to this feasibility study, we conducted a pilot study to collect channel state information data from several activity scenarios (eg, sitting, walking, and preparing meals) using the proposed Wi-Fi sensing system continuously over a week in apartments of low-income housing residents. These activities were videotaped to generate ground truth annotations to test the accuracy of the ML algorithms derived from the proposed system. Using qualitative individual interviews, we explored the acceptability of the Wi-Fi sensing system and implementation barriers in the low-income housing setting. We use the same study protocol for the proposed feasibility study. The Wi-Fi sensing system deployment began in November 2022, with participant recruitment starting in July 2023. Preliminary results will be available in the summer of 2025. Preliminary results are focused on the feasibility of developing ML models for Wi-Fi sensing-based activity and mobility assessment, community-based recruitment and data collection, ground truth, and older adults' Wi-Fi sensing technology acceptance. This feasibility study can make a contribution to SmHT science and ML capabilities for early detection of cognitive decline among socially vulnerable older adults. Currently, sensing devices are not readily available to this population due to cost and information barriers. Our sensing device has the potential to identify individuals at risk for cognitive decline by assessing their level of physical function by tracking their in-home activities and mobility behaviors, at a low cost. DERR1-10.2196/53447.

Somatic and psychiatric symptoms of brain tumors - a review of the literature

Introduction and Purpose Brain tumors cause a variety of somatic and psychiatric symptoms, which vary depending on the age of the patient and the location and type of tumor. Symptomatology includes both physical symptoms, such as headache, nausea, seizures and weakness, and psychiatric symptoms, including mood, personality and cognitive dysfunction. In children, the clinical picture is more complex and includes specific developmental difficulties. The purpose of this paper is to analyze the various symptoms accompanying brain tumors in order to detect them early and enable faster diagnosis. Material and Methods A comprehensive literature review was conducted using the PubMed database, focusing on articles published until the end of 2023.The search included the keywords: "brain tumors" "symptoms" "headache" and "psychiatric" in various combinations. Relevant studies were selected based on criteria such as somatic and psychiatric symptoms and early diagnosis of brain tumors. Results Accumulating data show the diversity of symptoms associated with brain tumors. Somatic symptoms such as headache, optic disc swelling, nausea, and seizures depend on intracranial pressure and tumor location. Psychiatric symptoms, including personality changes, mood disorders, and cognitive impairment, pose a significant diagnostic challenge in adult patients. In children, brain tumors can cause developmental delay and atypical neurological symptoms. Conclusions The symptoms of brain tumors are highly variable and difficult to diagnose, which significantly delays proper diagnosis of the disease. Its early detection is crucial as it improves the prognosis of patients, significantly improves their quality of life, and allows for the introduction of effective therapeutic interventions.

Abstract 4137155: Relationship between Subclinical Myocardial Injury and Global Cognitive Performance: The Multi-Ethnic Study of Atherosclerosis (MESA)

Background: With demographic trends transitioning towards older adults, dementia and cognitive impairment are predicted to increase dramatically. We aim to elucidate the relationship between subclinical myocardial injury, as indicated by asymptomatic increased levels of high-sensitivity cardiac Troponin (hs-cTnT), and cognitive performance. Methods: We studied MESA participants from Exam 1 (2000-02) to Exam 6 (2016-18), categorizing them based on baseline hs-cTnT at Exam 1. Cognitive decline was defined as a decrease of ≥5 units in CASI between Exam 5&6. We used Pearson correlation and linear regression to analyze the association of hs-cTnT levels with CASI scores, and logistic regression to examine the association with cognitive decline. We also explored the relationship between different hs-cTnT categories and cognitive measures. Models were adjusted for demographics, lifestyle, APOE status, comorbidities, and medication use ( Figure ). Results: 4445 participants had both baseline hs-cTnT and valid Exam 5 CASI scores while only 1776 participants had valid Exam 6 CASI scores. Cohort was predominantly female (53%), mean age of 60 years, and 27% had at least one APOE e4 allele. Median hs-cTnT was 6.32 ng/L, and median CASI scores were 89 at Exam 5 and 91.5 at Exam 6. We found a negative correlation between the log-hs-cTnT at Exam 1 and Exam 5 with CASI scores at Exam 5. An increase of one unit in log-hs-cTnT level was associated with a decrease of 0.67 (CI -1.17, -0.17) in CASI and corresponded to higher odds (OR: 1.44; CI 1.05-1.95) of cognitive decline, after adjusting for covariates. When comparing various categories of hs-cTnT with category 1, we observe that the odd of cognitive decline increases as the category increases. However, this trend does not hold for category 5 with significantly lower sample size ( Figure ). Conclusion: Our findings indicate an inverse relationship between hs-cTnT and cognitive function years later, which is significantly attenuated by known risk factors for cognitive decline. Further research is needed to determine hs-cTnT as a predictor of future global cognitive functions.

Anchor-Based and Distributional Responsiveness of the Spanish Version of the Edinburgh Feeding Evaluation in Dementia Scale in Older People with Dementia: A Longitudinal Study

Background/Objectives: Patients with dementia present with feeding difficulties (FDs) since diagnosis, conditioning their progression. Early identification is vital for preventing deterioration due to nutritional problems. The Edinburgh Feeding Evaluation in Dementia Scale (EdFED) identifies the FDs of patients with dementia by studying their behaviours while eating or being fed. The aim of this study was to assess the responsiveness of the EdFED over time in older people with cognitive impairment and to compare its effectiveness in identifying malnutrition and risk with that of the gold standard Mini Nutritional Assessment (MNA) method. Methods: This was a multicentre, prospective, observational, longitudinal, analytic study with a follow-up period of 18 months (with patients participating in nursing homes and in the community). Sociodemographic and nutritional data (body mass index (BMI), MNA, forearm circumference (FC), calf circumference (CC), and a nutritional blood test) were collected; EdFED score was reported by nurses, nursing assistants, and family caregivers. Results: The total sample consisted of 359 individuals—60.7% residential participants and 39.3% community participants. In the last follow-up there were 149 remaining (41.5%). Malnutrition was more than 30%, and the risk was 40% at the three follow-ups. The results suggest that the EdFED scale is a useful tool for assessing feeding difficulties (FDs) in older persons with dementia. It demonstrated good sensitivity and specificity in detecting malnutrition, similar to the MNA, and, more importantly, detecting risk and also identifying changes in nutritional status over time. Conclusions: The EdFED scale provides a means of evaluating nutritional problems, making it possible to work on prevention.

Care Refusal by Older Adults With Dementia Receiving Professional Care: A Scoping Review.

Care refusal behaviors by institutionalized older adults with dementia pose significant challenges for professional caregivers in residential care settings. This scoping review mapped the determinants and effects of care refusal in this population. A systematic search of five databases identified 19 studies published between 2013 and 2023. The findings indicated that personal, relational, environmental, and organizational factors influence care refusal behaviors in institutional settings. Cognitive impairment, communication difficulties, elderspeak, unfamiliar institutional environments, and task-oriented care were key determinants. Care refusal compromised health outcomes, disrupted care provision, and exacerbated neuropsychiatric symptoms in residential care facilities. Terminological inconsistencies and methodological limitations were identified as research gaps. Developing standardized terminology and person-centered strategies represents priority areas for coordinated action across policy, practice, and research to address the impact of refusal behaviors while upholding the rights of institutionalized older adults with dementia.

Serum High Mobility Group Box 1 (HMGB1) Protein Levels and Cognitive Function in Epilepsy Patients: A Cross-Sectional Study

Background: Epilepsy is a neurological disease with a high incidence rate. Cognitive decline is one of the consequences of recurrent seizures. Neuroinflammation is closely related to the development of epilepsy and cognitive impairment. An increase in the expression and translocation of High Mobility Group Box 1 (HMGB1) from the nucleus to the extracellular space has been observed in epilepsy patients and experimental animal models. This study aimed to investigate the relationship between serum HMGB1 levels and cognitive function in epilepsy patients. Methods: This cross-sectional observational study involved 45 epilepsy patients. Cognitive function was assessed using the Indonesian version of the Montreal Cognitive Assessment (MoCA-Ina), and serum HMGB1 levels were measured using the ELISA technique. The relationship between cognitive function and HMGB1 levels was analyzed using the Kruskal-Wallis test, with a significance level set at p < 0.05. Results: The mean age of the participants was 28.5 years, with a higher proportion of females. The mean serum HMGB1 level was 22.6 ng/ml. No significant relationship was found between serum HMGB1 levels and cognitive function in epilepsy patients (p = 0.188). Conclusion: Serum HMGB1 protein levels were not associated with cognitive function in this sample of epilepsy patients.

From immune response to mental health: neutrophils in schizophrenia

Schizophrenia is a multifaceted psychiatric disorder with a complex etiology that includes genetic, environmental, and immunological factors. Emerging research has increasingly focused on the role of the immune system, particularly neutrophils, in the pathogenesis of schizophrenia. Neutrophils, the most abundant type of white blood cells, are crucial in the body’s defense mechanisms against infections and in the regulation of inflammation. This review explores the evolving evidence that implicates neutrophils in schizophrenia, highlighting their potential contribution to the disorder’s onset and progression through mechanisms such as neuroinflammation and oxidative stress. Recent studies have demonstrated elevated neutrophil counts and neutrophil-to-lymphocyte ratios (NLR) in individuals with schizophrenia, correlating with the severity of psychotic symptoms and cognitive impairments. Furthermore, genetic and molecular analyses have revealed abnormalities in neutrophil function and immune-related gene expression in schizophrenia patients. These findings suggest that neutrophil dysfunction and the resulting chronic inflammation could play a significant role in the disorder’s pathophysiology, affecting neuronal function and contributing to the clinical manifestations of schizophrenia. Neutrophil-related biomarkers, such as NLR, could aid in the diagnosis and monitoring of disease progression. Additionally, targeting neutrophil activity and associated inflammatory pathways presents a promising avenue for developing new therapeutic interventions. This review underscores the need for further research to elucidate the precise mechanisms by which neutrophils influence schizophrenia and to explore potential treatments that could improve outcomes for patients.

Depression and the risk of fibromyalgia syndrome: a two-sample Mendelian randomization study

BackgroundFibromyalgia (FM) is a common illness with a wide range of symptoms, mainly manifested by unexplained chronic systemic musculoskeletal pain, sleep disorders and fatigue, sometimes accompanied by cognitive impairment, psychiatric symptoms and autonomic dysfunction. Previous studies have indicated a correlation between depression and the risk of FM; however, it remains uncertain whether this association reflects a causal relationship.MethodsWe evaluated the etiological association between the genetically predicted depression and the risk of developing FM by conducting a two-sample Mendelian Randomization (MR) study. The data on single nucleotide polymorphisms (SNPs) related to depression were obtained from the UK Biobank (UKB) and the Psychiatric Genomics Consortium (PGC) of White British European ancestry, and the data for FM were from the 5th release of the FinnGen study. We adopted the Inverse Variance Weighted (IVW) approach as the principal standard. In order to detect the existence of horizontal pleiotropy and heterogeneity, we adopted the MR-Egger approach as the sensitivity analysis.ResultsIn our MR analysis, 42 depression-related variants were identified as valid instrumental variables (IVs). The IVW approach’s results manifest that there is no etiologic causality between genetically predicted depression and the risk of FM (odds ratio [OR]: 1.673, 95% confidence interval [CI]: 0.852—3.287, P = 0.135). The study did not find any significant heterogeneities or horizontal pleiotropies (P > 0.05).ConclusionsOur results suggest that there is no significant genetic evidence linking depression to an increased risk of FM. However, further research is necessary to investigate the potential relationship and underlying mechanisms between depression and the risk of FM.

Abstract 4126628: Worse Cardiac Structure and Function is Associated with Decline in Multiple Domains of Cognitive Function: the Atherosclerosis Risk in Communities (ARIC) Study

Background: Cognitive impairment is cross-sectionally associated with worse cardiac structure/function. However, limited data exist regarding cardiac structure/function and longitudinal changes in cognitive function. Objective: Determine the association of cardiac structure and function with longitudinal changes in cognitive performance in late life. Methods: Among HF- and dementia-free participants in the community-based ARIC study who attended the 5th study visit (V5; 2011-2013), underwent protocol echocardiography, and completed a neurocognitive test battery at both V5 and study Visit 6 (V6; 2015-17), we assessed associations of cardiac structure and function measures with changes in both domain-specific and global cognitive scores between V5 and V6 using multivariable linear regression. Models were initially adjusted for demographics and education level, with additional models further adjusting for cardiovascular risk factors and disease at both V5 and V6. The neuropsychological test battery consisted of 10 neuropsychological tests that covered 3 domains of cognitive function: memory, executive functioning, and language. Factor scores were constructed for each cognitive domain, and their average represented a global composite score. Results: Among 2,988 included participants, mean age was 74±5 years, 60% were female, 20% reported Black race, and mean LVEF was 66±6%. Over a mean of 4.9±0.6 years (the V5 to V6 interval), raw scores declined for all neuropsychological tests. In fully adjusted models, worse diastolic function (larger LAVi) and LV remodeling (greater LV mass index) were associated with decline in executive function. Lower LVEF was associated with decline in language function, while worse LV longitudinal strain – a more sensitive measure of systolic dysfunction – was associated with decline in executive function, language function, and global cognition performance (all p<0.05; Table). Conclusion: Subclinical LV remodeling and dysfunction is associated with greater declines in cognitive function over 5 years in late life. Differential associations were observed by cognitive domains, with executive function decline most uniformly associated with impairments in cardiac structure/function.

Abstract Sa1108: The Aberrant Autophagy-Apoptosis regulation Mediates the Severe Neurological Dysfunction after Cardiac Arrest in Diabetic Mice

Background: Patients with diabetes have lower survival and worse neurological outcome after cardiopulmonary resuscitation (CPR) compared with non-diabetes. Previous studies have mentioned the aberrant autophagy in diabetic mice. However, whether this abnormal autophagy exacerbates neuronal apoptosis and neurological outcome in diabetic mice remains unclear. Methods: Patients were divided into non-diabetic cardiac arrest (CA) patients and diabetic CA patients, and the survival and neurological outcomes at discharge and day 28 after ROSC were compared between these two groups. Diabetic mice were fed with high fat diet (HFD), and CA model was established by inducing ventricular fibrillation electrically. The neurological prognosis was assessed by open field test (OPT), novel object recognition (NOR) and Y-maze. Neuronal apoptosis and autophagy were evaluated by immunofluorescence and western blotting, including TUNEL, cleaved caspase 3, LC3B, p62 and beclin1. Results: Compared with non-diabetic patients, the survival at discharge and at day 28 after ROSC are significantly lower in IHCA patients with diabetes. Meanwhile, the neurological deficits at discharge and at day 28 after ROSC are much severer in diabetic-CA patients. In addition, the lower survival and worse neurological function have been discovered, and the cognition impairment is more significant after ROSC in HFD mice. Neuronal apoptosis is severer in HFD mice. In ND mice, the activated autophagy has been revealed after CA-CPR-ROSC, however, autophagy can not be activated after ROSC in HFD mice since the baseline autophagy is at a higher level when compared with ND mice. Neuronal apoptosis is exacerbated after autophagy inhibition by 3-MA in ND mice, while after autophagy activation by rapamycin in HFD mice, apoptosis is attenuated after ROSC. Conclusion: Diabetes is the risk factor for neurological outcome in IHCA patients. The aberrant autophagy regulation in cortex neurons contributes to the severe apoptosis and neurological deficits after ROSC in diabetic mice.

Rasmussen Encephalitis: Clinical Features, Pathophysiology, and Management Strategies—A Comprehensive Literature Review

Rasmussen encephalitis (RE) is a rare and progressive form of chronic encephalitis that typically affects one hemisphere of the brain and primarily occurs in pediatric individuals. The current study aims to narratively review the literature about RE, including historical information, pathophysiology, and management of this condition. RE often occurs in individuals with normal development, and it is estimated that only a few new cases are identified each year in epilepsy centers. Approximately 10% of cases also occur in adolescents and adults. The hallmark feature of RE is drug-resistant focal seizures that can manifest as epilepsia partialis continua. Also, patients with RE usually develop motor and cognitive impairment throughout the years. Neuroimaging studies show progressive damage to the affected hemisphere, while histopathological examination reveals T-cell-dominated encephalitis with activated microglial cells and reactive astrogliosis. The current therapy guidelines suggest cerebral hemispherotomy is the most recommended treatment for seizures in RE, although significant neurological dysfunction can occur. Another option is pharmacological management with antiseizure medications and immunomodulatory agents. No significant progress has been made in understanding the pathophysiology of this condition in the last decades, especially regarding genetics. Notably, RE diagnosis still depends on the criteria established by Bien et al., and the accuracy can be limited and include genetically different individuals, leading to unexpected responses to management.

Diagnosis of Alzheimer's disease using plasma biomarkers adjusted to clinical probability.

Recently approved anti-amyloid immunotherapies for Alzheimer's disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing.

Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.

This study aims to (1) review machine learning (ML)-based models for early infection diagnostic and prognosis prediction in post-acute care (PAC) settings, (2) identify key risk predictors influencing infection-related outcomes, and (3) examine the quality and limitations of these models. PubMed, Web of Science, Scopus, IEEE Xplore, CINAHL, and ACM digital library were searched in February 2024. Eligible studies leveraged PAC data to develop and evaluate ML models for infection-related risks. Data extraction followed the CHARMS checklist. Quality appraisal followed the PROBAST tool. Data synthesis was guided by the socio-ecological conceptual framework. Thirteen studies were included, mainly focusing on respiratory infections and nursing homes. Most used regression models with structured electronic health record data. Since 2020, there has been a shift toward advanced ML algorithms and multimodal data, biosensors, and clinical notes being significant sources of unstructured data. Despite these advances, there is insufficient evidence to support performance improvements over traditional models. Individual-level risk predictors, like impaired cognition, declined function, and tachycardia, were commonly used, while contextual-level predictors were barely utilized, consequently limiting model fairness. Major sources of bias included lack of external validation, inadequate model calibration, and insufficient consideration of data complexity. Despite the growth of advanced modeling approaches in infection-related models in PAC settings, evidence supporting their superiority remains limited. Future research should leverage a socio-ecological lens for predictor selection and model construction, exploring optimal data modalities and ML model usage in PAC, while ensuring rigorous methodologies and fairness considerations.

Abstract 4119428: Monosialoganglioside-containing nanoliposomes protect against acute and chronic ischemic stroke injury

Background: Stroke remains a leading cause of mortality and disability. The narrow temporal window and limited availability of, and eligibility for thrombolytic therapy or endovascular thrombectomy are major therapeutic limitations in treating stroke. Neuroprotective therapies that could be given early to replace or augment these existing therapies are needed to improve stroke outcomes. We showed that monosialoganglioside (GM1) containing nanoliposomes composed of phosphatidylcholine, cholesterol and GM1 (70/25/5% molar ratios, NLGM1) protect against hypoxic injury likely through Nrf2-dependent upregulation of antoxidant enzymes. Aims: To test if post-occlusion NLGM1 treatment could reduce 1) acute stroke injury following middle cerebral artery occlusion (MCAO) and 2) chronic injury following photothrombotic (PT) stroke injury. Methods: 20 week old C57BL/6 mice underwent MCAO for 60 minutes and then injected with saline or NLGM1 (1 or 2 mg IV) prior to reperfusion. Neurologic deficit score and brain infarct % area were measured the next day. Separately, mice underwent PT injury followed by injection of saline or NLGM1 (1 or 2 mg immediately and 2 hours post-injury) and cognitive/behavior tests done 1-90 days post injury. Results: Following MCAO, there was reduced neurologic impairment, infarct volume and brain edema with NLGM1 versus saline control (Fig. 1). Following PT injury, there was reduced neurologic, cognitive and motor impairment from Day 2-90 post-injury with NLGM1 versus saline control (Fig. 2). In both stroke models, there was no difference in efficacy between 1 and 2 mg NLGM1 doses. Conclusions: Treatment of mice with NLGM1 following MCAO or PT stroke injury resulted in improved structural (infarct size, edema) and functional (cognitive, behavior, motor) outcomes in the acute (MCAO) and chronic (PT) timeframes. NLGM1 is a potential novel therapeutic agent for stroke.

The phospho-tau cascade, basal forebrain neurodegeneration, and dementia in Alzheimer's disease: Anti-neurodegenerative benefits of acetylcholinesterase inhibitors.

A conundrum in Alzheimer's disease (AD) is why the long-term use of acetylcholinesterase (AChE) inhibitors, intended for treatment of dementia, results in slowing neurodegeneration in the cholinergic basal forebrain, hippocampus, and cortex. The phospho-tau cascade hypothesis presented here attempts to answer that question by unifying three hallmark features of AD into a specific sequence of events. It is proposed that the hyperphosphorylation of tau protein leads to the AD-associated deficit of nerve growth factor (NGF), then to atrophy of the cholinergic basal forebrain and dementia. Because the release of pro-nerve growth factor (pro-NGF) is activity-dependent and is controlled by basal forebrain projections to the hippocampus and cortex, our hypothesis is that AChE inhibitors act by increasing acetylcholine-dependent pro-NGF release and, thus, augmenting the availability of mature NGF and improving basal forebrain survival. If correct, improved central nervous system-selective AChE inhibitor therapy started prophylactically, before AD-associated basal forebrain atrophy and cognitive impairment onset, has the potential to delay not only the onset of dementia but also its rate of advancement. The phospho-tau hypothesis thus suggests that preventing hyperphosphorylation of tau protein, early should be a high priority as a strategy to help reduce dementia and its associated widespread social and economic suffering.

The association between precuneus cortex thickness and mild behavioral impairment in patients with mild stroke.

The objective of this research was to examine the association between precuneus cortex thickness and mild behavioral impairment (MBI) in patients with mild stroke. Seventy-two patients were evaluated by high-resolution 3T magnetic resonance and the mild behavioral impairment checklist (MBI-C). To determine the association between precuneus cortex thickness and MBI, we adjusted for demographics, vascular risk factors, and laboratory examination indicators in logistic regression analysis. In addition, we used mendelian randomization to further study the association through genetic databases. Of the 72 mild stroke patients in this study, 26 had MBI. We found a strong negative connection between precuneus cortex thickness and MBI after adjusting for any confounding variables. In patients with an initial mild stroke, the thinner the precuneus cortex, the higher the risk of MBI (OR: 0.02; 95% CI: 0.00-0.39; P < 0.05). Our study has uncovered a significant negative association between the thickness of the precuneus cortex and MBI. This finding provides a novel viewpoint for the radiological diagnosis of MBI, thereby augmenting the contribution of imaging to the diagnostic process of MBI and advancing the prediction of dementia. Specifically, in patients who have suffered mild stroke, a reduction in the cortical thickness of the precuneus has been pinpointed as crucial radiographic evidence of preclinical cognitive impairment. This insight could potentially facilitate earlier detection and intervention strategies for cognitive decline.

Detecting functional impairment with the Digital Clock and Recall.

Distinguishing between mild cognitive impairment (MCI) and early dementia requires both neuropsychological and functional assessment that often relies on caregivers' insights. Contacting a patient's caregiver can be time-consuming in a physician's already-filled workday. To assess the utility of a brief, machine learning (ML)-enabled digital cognitive assessment, the Digital Clock and Recall (DCR), for detecting functional dependence. We evaluated whether the DCR can help identify individuals at risk of functional deficits as measured by the informant-rated Functional Activities Questionnaire (FAQ) in older individuals including cognitively unimpaired, MCI, and dementia likely due to Alzheimer's disease. The DCR scaled well with FAQ scores, and ML classifiers trained on multimodal DCR features demonstrated strong performance in predicting functional impairment on a held-out test set. Differences in FAQ scores between DCR-predicted classes were comparable across key demographic groups. The DCR can streamline the clinical decision-making, triage, and intervention planning associated with functional impairment in primary care.

Explainable early detection of Alzheimer's disease using ROIs and an ensemble of 138 3D vision transformers.

Early detection and accurate diagnosis of brain morphological abnormalities are essential for the effective management and treatment of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural magnetic resonance imaging (MRI) is a powerful support tool to aid in disease diagnosis and prediction. In this research study, we present an innovative approach to predict Alzheimer's disease (AD) and mild cognitive impairment (MCI) using MRI data, which integrates regional interest (ROI)-based methodology and deep learning within a comprehensible framework. The proposed method involves dividing the brain into 138 predetermined sections based on anatomical information. Next, we apply three-dimensional vision transformers (3D-ViTs) to each ROI individually, harnessing the power of deep learning. To improve prediction accuracy, we employ a deep belief network (DBN) as an ensemble learning model. Evaluating our approach on the baseline structural MRI dataset obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, and comparing it against five other competing models, we demonstrate its performance across four binary classification tasks and a three-class classification test (AD vs MCI vs CN (Cognitively Normal)). The proposed system outperforms existing models and provides interpretable insights into the brain regions that significantly contribute to solving each classification problem. Our findings align with the existing body of literature and hold promise for guiding future research directions in this domain.

Patients' and clinicians' knowledge in cancer-related cognitive impairment and its implications: current perspective.

Health literacy is essential in cancer care. Low health literacy compromises the capacity to maintain one's health through self-management and collaboration with healthcare providers, especially when facing cognitive side effects related to cancer and its treatments. Cancer-related cognitive impairment (CRCI) is a common phenomenon among cancer patients and might determine a significant impact on their quality of life, yet it is still under identified by both clinicians and patients. This perspective aims to discuss the implications of patients' and healthcare professionals' lack of awareness on the matter and argues about the importance of improving the level of information on CRCI to mitigate difficulties in identifying and managing such manifestations on various levels.

Dietary patterns in people with mild cognitive impairment

Dietary patterns in people with mild cognitive impairment