Higher Risk Of Cognitive Impairment Research Articles

Association of Seizure Control With Cognition in People With Normal Cognition and Mild Cognitive Impairment.

Seizures are common in dementia and associated with accelerated cognitive decline. However, the impact of active vs remote seizures on cognition remains understudied. This study aimed to investigate the impact of active vs remote seizures on cognition in people with normal cognition and mild cognitive impairment (MCI). This longitudinal, multicenter cohort is based on National Alzheimer's Coordinating Center data of participants recruited from 39 Alzheimer's Disease Centers in the United States from September 2005 to December 2021. All participants with normal cognition and MCI and at least 2 visits were included. Primary outcome, that is, cognitive decline, was determined using Clinical Dementia Rating (CDR) from (1) normal-to-impaired (CDR ≥0.5) and (2) MCI-to-dementia (CDR ≥1) groups. The effect of active seizures (over the preceding 12 months), remote seizures (previous seizures but none over the preceding 12 months), and no seizures (controls) on cognition was assessed. Subgroups of chronic seizures at enrollment and new-onset seizures were further analyzed. Cox regression models assessed the risk of all-cause MCI and/or dementia. All models were adjusted for age, sex, education, race, hypertension, and diabetes. Of the 13,726 participants with normal cognition at enrollment (9,002 [66%] female; median age 71 years), 118 had active seizures and 226 had remote seizures. Of the 11,372 participants with MCI at enrollment (5,605 [49%] female; median age 73 years), 197 had active seizures and 226 had remote seizures. Active seizures were associated with 2.1 times higher risk of cognitive impairment (adjusted hazard ratio [aHR] 2.13, 95% CI 1.60-2.84, p < 0.001) in cognitively healthy adults (median years to decline: active seizures = ∼1, remote seizures = ∼3, no seizures = ∼3) and 1.6 times higher risk of dementia (aHR 1.58, 95% CI 1.24-2.01, p < 0.001) in those with MCI (median years to decline: active seizures = ∼1, remote seizures = ∼2, controls = ∼2). This risk was not observed with remote seizures. In this study, active seizures but not remote seizures were associated with earlier cognitive decline in both cognitively normal adults and those with MCI, independent of other dementia risk factors. Therefore, early identification and management of seizures may present a path to mitigation of cognitive decline in the aging epileptic population. A limitation is that causality cannot be confirmed in our observational longitudinal study.

Traumatic Brain Injury, Seizures, and Cognitive Impairment Among Older Adults

Traumatic brain injury (TBI), seizures, and dementia increase with age. There is a gap in understanding the associations of TBI, seizures, and medications such as antiseizure and antipsychotics with the progression of cognitive impairment across racial and ethnic groups. To investigate the association of TBI and seizures with the risk of cognitive impairment among cognitively normal older adults and the role of medications in moderating the association. This multicenter cohort study was a secondary analysis of the Uniform Data Set collected between June 1, 2005, and June 30, 2020, from the National Alzheimer's Coordination Center. Statistical analysis was performed from February 1 to April 3, 2024. Data were collected from participants from 36 Alzheimer's Disease Research Centers in the US who were 65 years or older at baseline, cognitively normal at baseline (Clinical Dementia Rating of 0 and no impairment based on a presumptive etiologic diagnosis of AD), and had complete information on race and ethnicity, age, sex, educational level, and apolipoprotein E genotype. Health history of TBI, seizures, or both conditions. Progression to cognitive impairment measured by a Clinical Dementia Rating greater than 0. Among the cohort of 7180 older adults (median age, 74 years [range, 65-102 years]; 4729 women [65.9%]), 1036 were African American or Black (14.4%), 21 were American Indian or Alaska Native (0.3%), 143 were Asian (2.0%), 332 were Hispanic (4.6%), and 5648 were non-Hispanic White (78.7%); the median educational level was 16.0 years (range, 1.0-29.0 years). After adjustment for selection basis using propensity score weighting, seizure was associated with a 40% higher risk of cognitive impairment (hazard ratio [HR], 1.40; 95% CI, 1.19-1.65), TBI with a 25% higher risk of cognitive impairment (HR, 1.25; 95% CI, 1.17-1.34), and both seizure and TBI were associated with a 57% higher risk (HR, 1.57; 95% CI, 1.23-2.01). The interaction models indicated that Hispanic participants with TBI and seizures had a higher risk of cognitive impairment compared with other racial and ethnic groups. The use of antiseizure medications (HR, 1.23; 95% CI, 0.99-1.53), antidepressants (HR, 1.32; 95% CI, 1.17-1.50), and antipsychotics (HR, 2.15; 95% CI, 1.18-3.89) was associated with a higher risk of cognitive impairment, while anxiolytic, sedative, or hypnotic use (HR, 0.88; 95% CI, 0.83-0.94) was associated with a lower risk. This study highlights the importance of addressing TBI and seizures as risk factors for cognitive impairment among older adults. Addressing the broader social determinants of health and bridging the health divide across various racial and ethnic groups are essential for the comprehensive management and prevention of dementia.

Exercise and Cognitive Function Chronic Kidney Disease: A Systematic Review and Meta-Analysis of Efficacy and Harms.

People living with chronic kidney disease (CKD) are at higher risk of cognitive impairment. Exercise may improve cognitive function. This systematic review and meta-analysis of randomized controlled trials (RCTs) was completed to determine the efficacy and harms of exercise in improving cognitive function in people living with CKD. A systematic literature review identified RCTs of people with any stage of CKD, with an intervention that exercised large-muscle groups, and with a validated outcome measure of cognitive function. First, harms were analyzed. Then a random-effects meta-analysis was completed with subsequent planned subgroup analyses to investigate heterogeneity between CKD stages and treatments, between different exercise types, durations and intensities, and between different outcome methodologies. Finally, quality of evidence was rated. Nineteen trials randomized 1160 participants. Harms were reported on 94 occasions in intervention groups vs. 83 in control. The primary analysis found that exercise had a small but statistically significant effect on cognition in CKD (effect size (ES) = 0.22; 95% confidence intervals (CI95) = 0.00, 0.44; P = 0.05). However, the quality of evidence was rated as low. Subgroup analyses found that type of exercise moderated the effect on cognition (χ2 = 7.62; P = 0.02), with positive effects only observed following aerobic exercise (ES = 0.57; CI95 = 0.21, 0.93; P = 0.002). Across the spectrum of CKD, exercise had a small but positive and clinically meaningful effect on cognitive function and did not appear to be harmful. Aerobic exercise was particularly beneficial. However, results must be interpreted cautiously due to the low quality of evidence. Nevertheless, care teams may choose to recommend aerobic exercise interventions to prevent cognitive decline. Researchers should design unbiased studies to clarify what intensity and duration of exercise is required to maximize efficiency of such exercise interventions.

Relationship between triglyceride-glucose index and cognitive function among community-dwelling older adults: a population-based cohort study.

The global increase in the aging population presents considerable challenges, particularly regarding cognitive impairment, a major concern for public health. This study investigates the association between the triglyceride-glucose (TyG) index, a measure of insulin resistance, and the risk of cognitive impairment in the elderly. This prospective cohort study enrolled 2,959 participants aged 65 and above from the 2015 and 2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). The analysis employed a logistic regression model to assess the correlation between the TyG index and cognitive impairment. The study included 2,959 participants, with a mean age of 71.2 ± 5.4 years, 49.8% of whom were female. The follow-up in 2020 showed a decrease in average cognitive function scores from 8.63 ± 4.61 in 2015 to 6.86 ± 5.45. After adjusting for confounding factors, a significant association was observed between TyG index quartiles and cognitive impairment. Participants in the highest quartile (Q4) of baseline TyG had a higher risk of cognitive impairment compared to those in the lowest quartile (Q1) (odds ratio [OR]: 1.97, 95% confidence intervals [CI]: 1.28-2.62, P<0.001). The study highlights a significant connection between elevated TyG index levels and cognitive impairment among older adults in China. These findings suggest that targeted interventions to reduce the TyG index could mitigate cognitive impairment and potentially lower the incidence of dementia.

Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method

BackgroundCognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of cognitive diseases such as Alzheimer’s and Lewy body dementia. Large-scale screening relies heavily on cognitive assessment scales as primary tools, with some low sensitivity and others expensive. Despite significant progress in machine learning for cognitive function assessment, its application in this particular screening domain remains underexplored, often requiring labor-intensive expert annotations. AimsThis paper introduces a semi-supervised learning algorithm based on pseudo-label with putback (SS-PP), aiming to enhance model efficiency in predicting the high risk of cognitive impairment (HR-CI) by utilizing the distribution of unlabeled samples. DataThe study involved 189 labeled samples and 215,078 unlabeled samples from real world. A semi-supervised classification algorithm was designed and evaluated by comparison with supervised methods composed by 14 traditional machine-learning methods and other advanced semi-supervised algorithms. ResultsThe optimal SS-PP model, based on GBDT, achieved an AUC of 0.947. Comparative analysis with supervised learning models and semi-supervised methods demonstrated an average AUC improvement of 8% and state-of-art performance, repectively. ConclusionThis study pioneers the exploration of utilizing limited labeled data for HR-CI predictions and evaluates the benefits of incorporating physical examination data, holding significant implications for the development of cost-effective strategies in relevant healthcare domains.

Very high high-density lipoprotein cholesterol may be associated with higher risk of cognitive impairment in older adults

BackgroundPrevious studies have shown that high-density lipoprotein cholesterol (HDL-C) levels are positively associated with cognitive function across a range of concentrations. However, recent studies have suggested that very high HDL-C levels may lead to poorer outcomes. Therefore, we aimed to investigate the relationship between different concentrations of HDL-C and cognitive impairment risk.MethodsWe collected data from 3632 participants aged over 60 years from the U.S. National Health and Nutrition Examination Survey (NHANES) between 2011 and 2014 to assess the relationship between HDL-C and cognitive function. Cognitive function was evaluated with the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) test, the animal fluency test (AFT), and the digit symbol substitution test (DSST). We used restricted cubic spline models and logistic regression to examine the association between HDL-C and cognitive function.ResultsA U-shaped was observed between HDL-C and cognitive outcomes, individuals with higher risk in those with both low and very high HDL-C levels compared with those with midrange values. Very high HDL-C levels (≥ 2.50 mmol/L) were associated with increased risk of cognitive impairment (OR = 2.19; 95% CI, 1.12–4.28) compared with those with HDL-C levels in the range of 1.50 to 1.99 mmol/L in older adults after adjustment for confounding factors. Interaction test demonstrated that relationship between very high HDL-C and the risk of cognitive impairment was not changed in different sex and race group (P for interaction > 0.05).ConclusionsVery high HDL-C levels were associated with an increased risk of cognitive impairment. HDL-C may not be a protective factor for maintaining brain health in older adults at very high levels.

Association of modified dementia risk score with cerebrospinal fluid biomarkers and cognition in adults without dementia.

This study aimed to investigate the cognitive profile and prospective cognitive changes in non-demented adults with elevated Modified Dementia Risk Scores (MDRS), while also exploring the potential relationship between these associations and cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathology and neuroinflammation. Within the Chinese Alzheimer's Biomarker and LifestylE (CABLE) database, 994 participants without dementia were assessed on MDRS, CSF biomarkers and cognition. We examined the associations of the MDRS with CSF biomarkers and cognitive scores using linear regressions. Causal mediation analyses were conducted to analyze the associations among MDRS, brain pathologies, and cognition. The Alzheimer's Disease Neuroimaging Initiative (ADNI) study was used to validate the mediation effects and to investigate the longitudinal association between MDRS and cognitive decline. The results revealed that higher MDRS were linked to poorer cognitive performance (Model 1: PFDR < 0.001; Model 2: PFDR < 0.001) and increases in CSF levels of phosphorylated tau (P-tau, Model 1: PFDR < 0.001; Model 2: PFDR < 0.001), total tau (T-tau, Model 1: PFDR < 0.001; Model 2: PFDR < 0.001), P-tau/Aβ42 ratio (Model 1: PFDR = 0.023; Model 2: PFDR = 0.028), T-tau/Aβ42 ratio (Model 1: PFDR < 0.001; Model 2: PFDR < 0.001) and soluble triggering receptor expressed on myeloid cells 2 (sTrem2, Model 1: PFDR < 0.001; Model 2: PFDR < 0.001) in the CABLE study. The impact of MDRS on cognition was partially mediated by neuroinflammation and tau pathology. These mediation effects were replicated in the ADNI study. Baseline MDRS were significantly associated with future cognitive decline, as indicated by lower scores on the Mini-Mental State Examination (MMSE, Model 1: PFDR = 0.045; Model 2: PFDR < 0.001), ADNI composite memory score (ADNI-MEM, Model 1: PFDR = 0.005; Model 2: PFDR < 0.001), ADNI composite executive function score (ADNI-EF, Model 1: PFDR = 0.045; Model 2: PFDR < 0.001), and higher score on the Alzheimer's Disease Assessment Scale (ADAS13, Model 1: PFDR = 0.045; Model 2: PFDR < 0.001). The findings of this study revealed significant associations between MDRS and cognitive decline, suggesting a potential role of tau pathology and neuroinflammation in the link between MDRS and poorer cognitive performance in individuals without dementia. Consequently, the MDRS holds promise as a tool for targeted preventive interventions in individuals at high risk of cognitive impairment.

Language and sensory characteristics are reflected in voice-evoked responses in low birth weight children.

Children born with very low birth weight (VLBW) are at higher risk for cognitive impairment, including language deficits and sensorimotor difficulties. Voice-evoked response (P1m), which has been suggested as a language development biomarker in young children, remains unexplored for its efficacy in VLBW children. Furthermore, the relation between P1m and sensory difficulties in VLBW children remains unclear. 40 children with VLBW were recruited at 5-to-6 years old (26 male, 14 female, mean age of months ± SD, 80.0 ± 4.9). We measured their voice-evoked brain response using child-customized magnetoencephalography (MEG) and examined the relation between P1m and language conceptual inference ability and sensory characteristics. The final sample comprised 36 children (23 boys, 13 girls; ages 61-86 months; gestational ages 24-36 weeks). As a result of multiple regression analysis, voice-evoked P1m in the left hemisphere was correlated significantly with language ability (β = 0.414 P = 0.015) and sensory hypersensitivity (β = 0.471 P = 0.005). Our findings indicate that the relation between P1m and language conceptual inference ability observed in term children in earlier studies is replicated in VLBW children, and suggests P1m intensity as a biomarker of sensory sensitivity characteristics. We investigated brain functions related to language development and sensory problems in very low birth-weight children. In very low birth weight children at early school age, brain responses to human voices are associated with language conceptual inference ability and sensory hypersensitivity. These findings promote a physiological understanding of both language development and sensory characteristics in very low birth weight children.

Associations Between Ultra-Processed Food Consumption and Adverse Brain Health Outcomes.

Ultra-processed foods (UPFs) are linked to cardiometabolic diseases and neurologic outcomes, such as cognitive decline and stroke. However, it is unclear whether food processing confers neurologic risk independent of dietary pattern information. We aimed to (1) investigate associations between UPFs and incident cognitive impairment and stroke and (2) compare these associations with other commonly recommended dietary patterns in the REasons for Geographic and Racial Differences in Stroke study. This prospective, observational cohort study enrolled Black and White adults in the United States from 2003 to 2007. The NOVA system was used to categorize items from a baseline food frequency questionnaire according to the level of processing. Participants with incomplete or implausible self-reported dietary data were excluded. Consumption for each category (grams) was normalized to total grams consumed. Scores quantifying adherence to a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet were also calculated. Incident cognitive impairment was defined using performance relative to a normative sample on memory and fluency assessments. Incident stroke was identified through adjudicated review of medical records. The cognitive impairment cohort (n = 14,175) included participants without evidence of impairment at baseline who underwent follow-up testing. The stroke cohort (n = 20,243) included participants without a history of stroke. In multivariable Cox proportional hazards models, a 10% increase in relative intake of UPFs was associated with higher risk of cognitive impairment (hazard ratio [HR] = 1.16, 95% CI 1.09-1.24, p = 1.01 × 10-5) and intake of unprocessed or minimally processed foods with lower risk of cognitive impairment (HR = 0.88, 95% CI 0.83-0.94, p = 1.83 × 10-4). Greater intake of UPFs (HR = 1.08, 95% CI 1.02-1.14, p = 1.12 × 10-2) and unprocessed or minimally processed foods (HR = 0.91, 95% CI 0.86-0.95, p = 2.13 × 10-4) were also associated with risk of stroke in multivariable Cox models. The effect of UPFs on stroke risk was greater among Black than White participants (UPF-by-race interaction HR = 1.15, 95% CI 1.03-1.29, p = 1.50 × 10-2). Associations between UPFs and both cognitive impairment and stroke were independent of adherence to the Mediterranean, DASH, and MIND diets. Food processing may be important to brain health in older adults independent of known risk factors and adherence to recommended dietary patterns.

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development

Introduction: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention. Methods: This study included 2,288 participants with normal cognitive function from the Ma’anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level. Results: The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773–0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults. Conclusion: The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Prediction Model for Cognitive Impairment among Disabled Older Adults: A Development and Validation Study.

Disabled older adults exhibited a higher risk for cognitive impairment. Early identification is crucial in alleviating the disease burden. This study aims to develop and validate a prediction model for identifying cognitive impairment among disabled older adults. A total of 2138, 501, and 746 participants were included in the development set and two external validation sets. Logistic regression, support vector machine, random forest, and XGBoost were introduced to develop the prediction model. A nomogram was further established to demonstrate the prediction model directly and vividly. Logistic regression exhibited better predictive performance on the test set with an area under the curve of 0.875. It maintained a high level of precision (0.808), specification (0.788), sensitivity (0.770), and F1-score (0.788) compared with the machine learning models. We further simplified and established a nomogram based on the logistic regression, comprising five variables: age, daily living activities, instrumental activity of daily living, hearing impairment, and visual impairment. The areas under the curve of the nomogram were 0.871, 0.825, and 0.863 in the internal and two external validation sets, respectively. This nomogram effectively identifies the risk of cognitive impairment in disabled older adults.

Data-driven clustering approach to identify novel clusters of high cognitive impairment risk among Chinese community-dwelling elderly people with normal cognition: A national cohort study.

Cognitive impairment is a highly heterogeneous disorder that necessitates further investigation into the distinct characteristics of populations at varying risk levels of cognitive impairment. Using a large-scale registry cohort of elderly individuals, we applied a data-driven approach to identify novel clusters based on diverse sociodemographic features. A prospective cohort of 6398 elderly people from the Chinese Longitudinal Healthy Longevity Survey, followed between 2008-14, was used to develop and validate the model. Participants were aged ≥60 years, community-dwelling, and the Chinese version of the Mini-Mental State Examination (MMSE) score ≥18 were included. Sixty-nine sociodemographic features were included in the analysis. The total population was divided into two-thirds for the derivation cohort (n = 4265) and one-third for the validation cohort (n = 2133). In the derivation cohort, an unsupervised Gaussian mixture model was applied to categorise participants into distinct clusters. A classifier was developed based on the most important 10 factors and was applied to categorise participants into their corresponding clusters in a validation cohort. The difference in the three-year risk of cognitive impairment was compared across the clusters. We identified four clusters with distinct features in the derivation cohort. Cluster 1 was associated with the worst life independence, longest sleep duration, and the oldest age. Cluster 2 demonstrated the highest loneliness, characterised by non-marital status and living alone. Cluster 3 was characterised by the lowest sense of loneliness and the highest proportions in marital status and family co-residence. Cluster 4 demonstrated heightened engagement in exercise and leisure activity, along with independent decision-making, hygiene, and a diverse diet. In comparison to Cluster 4, Cluster 1 exhibited the highest three-year cognitive impairment risk (adjusted odds ratio (aOR) = 3.31; 95% confidence interval (CI) = 1.81-6.05), followed by Cluster 2 and Cluster 3 after adjustment for baseline MMSE, residence, sex, age, years of education, drinking, smoking, hypertension, diabetes, heart disease and stroke or cardiovascular diseases. A data-driven approach can be instrumental in identifying individuals at high risk of cognitive impairment among cognitively normal elderly populations. Based on various sociodemographic features, these clusters can suggest individualised intervention plans.

Hemodynamic Reactivity to Mental Stress and Cognitive Function in Coronary Artery Disease.

People with coronary artery disease (CAD) are at higher risk of cognitive impairment than those without CAD. Psychological stress is a risk factor for both conditions, and assessing the hemodynamic reactivity to mental stress could explain the link between stress and cognitive function. A total of 779 individuals with stable CAD from two prospective cohort studies were included. All individuals underwent acute mental stress testing, as well as conventional stress testing. Cognitive function was assessed both at baseline and at a 2-year follow-up. The rate-pressure product (RPP) was calculated as the mean systolic blood pressure times the mean heart rate at rest. RPP reactivity was defined as the maximum RPP during standardized mental stress test minus the RPP at rest. After multivariable adjustment, every standard deviation decrease in RPP reactivity with mental stress was associated with slower completion of Trail-A and Trail-B in both cohorts (13% and 11% in cohort 1, and 15% and 16% in cohort 2, respectively; p for all <.01). After a 2-year follow-up period, every standard deviation decrease in RPP reactivity with mental stress was associated with a 8% and 9% slower completion of Trail-A and Trail-B, respectively ( p for all <.01). There was no significant association between RPP reactivity with conventional stress testing and any of the cognitive tests. In the CAD population, a blunted hemodynamic response to mental stress is associated with slower visuomotor processing and worse executive function at baseline and with greater decline in these abilities over time.

White matter hyperintensities mediate the association between frailty and cognitive impairment in moyamoya disease

ObjectivesThe relationship between cognitive function and frailty in moyamoya disease (MMD) remains unclear, and the underlying mechanism is poorly understood. This study aims to investigate whether white matter hyperintensities (WMHs) mediate the association between frailty and cognitive impairment in MMD. MethodsPatients with MMD were consecutively enrolled in our study from January 2021 to May 2023. Pre-admission frailty and cognition were assessed using the Clinical Frailty Scale (CFS) and cognitive tests, respectively. Regional deep WMH (DWMH) and periventricular WMH (PWMH) volumes were calculated using the Brain Anatomical Analysis using Diffeomorphic deformation toolbox based on SPM 12 software. Multivariate logistic regression analysis was conducted to evaluate the association between frailty and cognitive function in MMD. Mediation analysis was performed to assess whether WMHs explained the association between frailty and cognition. ResultsA total of 85 patients with MMD were enrolled in this study. On the basis of the CFS scores, 24 patients were classified as frail, 38 as pre-frail, and 23 as robust. Significant differences were observed in learning, memory, processing speed, executive functions, and semantic memory among the three groups (p < 0.001). Frailty was independently associated with memory and executive functions (p < 0.05); even after controlling for WMH. Mediation analysis indicated that the associations of frailty with memory and executive functions were partially mediated by WMH, DWMH, and PWMH (p < 0.05). ConclusionFrailty is significantly correlated with a higher risk of cognitive impairment in MMD, even after adjusting for other covariates. WMHs partially mediate the association between frailty and cognitive impairment.

The impact of anticholinergics on cognitive function in patients with neurogenic lower urinary tract dysfunction: A narrative review.

This narrative review discusses the relationship between anticholinergic medications and cognitive change specifically in patients with neurogenic lower urinary tract dysfunction (NLUTD). NLUTD is prevalent in various conditions, including spinal cord injury (SCI), spina bifida (SB), multiple sclerosis (MS), Parkinson's, stroke, and dementia and often requires anticholinergic overactive bladder (OAB) medications. In the general population, and among those with OAB, several studies have found a significant association between this class of medications and cognitive side effects, mostly when used for > 90 days. These cognitive side effects may be particularly relevant to people with NLUTD due to their higher baseline risk of cognitive impairment. Two studies (one in people with SCI and another in MS) found evidence of cognitive impairment with the use of OAB anticholinergics (specifically oxybutynin and tolterodine). People with dementia commonly use OAB anticholinergics, and there is evidence that oxybutynin and tolterodine may impair cognition in this population. Two recent studies in children with SB studied 12 months of solifenacin and 6 months of fesoterodine/oxybutynin and found there was no significant change in neuropsychological testing. Clinical studies in people with Parkinson's disease and prior stroke have not shown that trospium, darifenacin, or fesoterodine have a significant impact on cognitive measures. In summary, oxybutynin and tolterodine may pose a higher risk of cognitive impairment than newer OAB anticholinergics in people with NLUTD; there is no evidence that children with SB experience cognitive impairment with OAB anticholinergics. Further study is necessary to confirm cognitive safety, particularly as the NLUTD population may have a high exposure to OAB anticholinergics. Advocating for potentially safer OAB medications is necessary if there is concern about cognitive risks.

Association between multimorbidity and cognitive decline in the elderly population of the Eastern Province, Saudi Arabia.

Cognitive decline affects the quality of life, and dementia affects independence in daily life activities. Multimorbidity in older adults is associated with a higher risk of cognitive impairment. This research aims to study the relationship between cognitive decline and multimorbidity in the elderly population in the Eastern Province, Saudi Arabia. This cross-sectional research was conducted from July to October 2022 among adults over 60 years. All patients with two or more comorbidities were contacted for a face-to-face interview and cognitive testing to estimate cognitive function by trained family physicians using St. Louis University Mental State Examination. ANOVA and Chi-square test were used to test for statistical significance. Binary logistic regression was used to show the odds of having cognitive impairment and multimorbidity. All tests were performed at 5% level of significance. The study involved 343 individuals; majority (74.1%) aged 60-75 years and were males (67.9%). Hypertension, diabetes, and chronic pain were reported by 56%, 48%, and 44% participants, respectively. Thirty percent participants had 3 or more comorbidities. About 36% had mild neurocognitive disorder and 31.2% had dementia. The results showed that age, gender (female), diabetes, stroke, chronic pain, and multimorbidity were significantly associated with cognitive impairment. In our study, hypertension, coronary artery diseases, depression, and anxiety were not significantly associated with risk of cognitive decline. Our study found that multimorbidity is significantly associated with cognitive decline. Controlling comorbidities and preventing risk factors in midlife could help in delaying the progression of the disease.

Body Composition, Sarcopenic Obesity, and Cognitive Function in Older Adults: Findings From the National Health and Nutrition Examination Survey (NHANES) 1999–2002 and 2011–2014

Objective Sarcopenic-obesity (SO) is characterized by the concomitant presence of low muscle mass and high adiposity. This study explores the association of body composition and SO phenotypes with cognitive function in older adults. Methods Cross-sectional data in older adults (≥60 years) from NHANES 1999–2002 and 2011–2014 were used. In the 1999–2002 cohort, phenotypes were derived from body mass index (BMI) and dual-X-ray-absorptiometry, and cognition was assessed the by Digit-Symbol-Substitution-Test (DSST). In the 2011–2014 cohort, phenotypes were derived from BMI, waist-circumference (WC), and hand-grip-strength (HGS). Cognition was assessed using four tests: DSST, Animal Fluency, the Consortium-to-Establish-a-Registry-for-Alzheimer’s-Disease-Delayed-Recall, and Word Learning. Mediation analysis was conducted to evaluate the contribution of inflammation (C-reactive-protein, CRP) and insulin resistance (Homeostatic-Model-Assessment-for-Insulin-Resistance, HOMA-IR) to the association between body composition and cognitive outcomes. Results The SO phenotype had the lowest DSST mean scores (p < 0.05) and was associated with a significant risk of cognitive impairment [Odds Ratio (OR) = 1.9; 95%CI 1.0–3.7, p = 0.027] in the 1999–2002 cohort. A higher ratio of fat mass and fat free mass (FM/FFM) also showed a greater risk of cognitive impairment (OR = 2.0; 95%CI 1.3–3.1, p = 0.004). In the 2011–2014 cohort, the high WC-Low HGS group showed significantly lower scores on all four cognitive tests (p < 0.05) and a higher risk of cognitive impairment. CRP and HOMA-IR were significant partial mediators of the association between FM/FFM and DSST in the 1999–2002 cohort. Conclusions The SO phenotype was associated with a higher risk of cognitive impairment in older adults. Insulin resistance and inflammation may represent key mechanisms linking SO to the development of cognitive impairment.

Multispectral brain connectivity during visual attention distinguishes controlled from uncontrolled hypertension.

Hypertension-related changes in brain function place individuals at higher risk for cognitive impairment and Alzheimer's disease. The existing functional neuroimaging literature has identified important neural and behavioural differences between normotensive and hypertensive individuals. However, previously-used methods (i.e. magnetic resonance imaging, functional near-infrared spectroscopy) rely on neurovascular coupling, which is a useful but indirect measure of neuronal activity. Furthermore, most studies fail to distinguish between controlled and uncontrolled hypertensive individuals, who exhibit significant behavioural and clinical differences. To partially remedy this gap in the literature, we used magnetoencephalography (MEG) to directly examine neuronal activity that is invariant to neurovascular coupling changes induced by hypertension. Our study included 52 participants (19healthy controls, 15 controlled hypertensives, 18 uncontrolled hypertensives) who completed a modified flanker attention task during MEG. We identified significant oscillatory neural responses in two frequencies (alpha: 8-14Hz, gamma: 48-60Hz) for imaging and used grand-averaged images to determine seeds for whole-brain connectivity analysis. We then conducted Fisher-z tests for each pair of groups, using the relationship between the neural connectivity and behavioural attention effects. This highlighted a distributed network of regions associated with cognitive control and selective attention, including frontal-occipital and interhemispheric occipital connections. Importantly, the inferior frontal cortex exhibited a unique neurobehavioural relationship that distinguished the uncontrolled hypertensive group from the controlled hypertensive and normotensive groups. This is the first investigation of hypertension using MEG and identifies critical whole-brain connectivity differences based on hypertension profiles. KEY POINTS: Structural and functional changes in brain circuitry scale with hypertension severity and increase the risk of cognitive impairment and Alzheimer's disease. We harness the excellent spatiotemporal precision of magnetoencephalography (MEG) to directly quantify dynamic functional connectivity in healthy control, controlled hypertensive and uncontrolled hypertensive groups during a flanker task. In the first MEG study of hypertension, we show that there are neurobehavioural relationships that distinguish the uncontrolled hypertensive group from healthy and controlled hypertensive group in the prefrontal cortex. These results provide novel insights into the differential impact of hypertension on brain dynamics underlying selective attention.

The Mediating Role of Psychological Balance on the Effects of Dietary Behavior on Cognitive Impairment in Chinese Elderly.

Cognitive impairment, a significant problem in older adults, may be associated with diet. This study aims to examine the association between the dietary diversity score (DDS), dietary pattern (DP), and cognitive impairment in elderly Chinese. This research further explored the role of psychological balance (PB) as a mediator in the relationship between diet and cognitive impairment. A total of 14,318 older adults from the Chinese Longitudinal Healthy Longevity Study (CLHLS) in 2018 were included. Latent class analysis (LCA) was used to identify patterns in seven food varieties. Binary logistic regression models were used to determine factors associated with the DDS, DP, and cognitive impairment. The multiple mediation effect model was evaluated using model 6 in the PROCESS version 3.5 program. Among the participants, 4294 (29.99%) developed cognitive impairment. Compared to people in food variety group two or lower, people with a high dietary diversity score (DDS) had lower odds of cognitive impairment. Compared to DP1, DP2 (OR = 1.24, 95%CI = 1.09 to 1.40) was associated with a higher risk of cognitive impairment, and DP4 (OR = 0.79, 95%CI = 0.69 to 0.89) was associated with a lower risk of cognitive impairment. PB mediated the relationship between DDS, DP, and cognitive impairment, with a mediating effect of 27.24% and 41.00%. A DP that is rich in fruits, vegetables, red meat, fish, eggs, beans, nuts, and milk was related to a lower risk of cognitive impairment. PB has an indirect impact on cognitive impairment. Our findings underscore the importance of promoting a diverse diet, which may contribute to a lower risk of cognitive impairment in older adults. The PB of the elderly should also be taken into consideration.

Cognitive, behavioral and psychiatric symptoms in patients with spinal cord injury: a scoping review.

Spinal Cord Injury (SCI) is a condition where the spinal cord is damaged and experiences partial or complete loss of motor and/or sensory function, which is typically less than normal. After SCI, patients may exhibit more severe psychiatric symptoms and experience cognitive impairments, including reduced speed and attention processing capacity, as well as difficulties with executive function and episodic memory retention. Among the behavioral and psychiatric symptoms, depression, anxiety, substance use disorder, and posttraumatic stress disorder are the most common. This review aims to investigate the cognitive, behavioral, or psychiatric symptoms of the patient with SCI and their influence on the rehabilitation process. Studies were identified from an online search of PubMed, Web of Science, Cochrane Library, and Embase databases. Studies published between 2013-2023 were selected. This review has been registered on OSF (n) 3KB2U. We have found that patients with SCI are at high risk of cognitive impairment and experience a wide range of difficulties, including tasks based on processing speed and executive function. This clinical population may experience adjustment disorders with depression and anxiety, as well as other psychiatric symptoms such as fatigue, stress, and suicidal ideation. This review has demonstrated that SCI patients may experience psychiatric symptoms and cognitive impairments that affect their functioning. At the same time, these patients may be more prone to various adjustment and mood disorders. Moreover, these two aspects may interact with each other, causing a range of symptoms, increasing the risk of hospitalization, and delaying the rehabilitation process.