Cognitive Impairment In People Research Articles

Mitigating cognitive impairment in people with HIV by targeting potential impacts of toxoplasmic infection

Mitigating cognitive impairment in people with HIV by targeting potential impacts of toxoplasmic infection

Functional near-infrared spectroscopy and vagus somatosensory evoked potentials add to the power of established parameters such as poor cognitive performance, dsyosmia and APOe genotype to predict cognitive decline over 8 years in the elderly.

Alzheimer's dementia is the main cause of cognitive impairment in people over the age of 65, with Alzheimer's disease starting presumably 10-15 years before the onset of clinical symptoms. It is therefore important to recognize dementia at an early stage and identify possible predictors. The existing methods, like different parameters of ß-Amyloid and Tau quantification in cerebrospinal fluid (CSF) or the living brain by measure of PET, are invasive and expensive. Therefore, the present study investigates the predictive value of a battery of clinical, neuropsychological, and blood parameters as well as two neurophysiological methods (functional near-infrared spectroscopy [fNIRS] and vagus somatosensory evoked potentials [VSEP]) which are easy to perform, less invasive and cost-efficient, for developing cognitive impairments in the elderly.In this longitudinal, prospective study, we enrolled 604 healthy participants between 70 and 77 years of age. The participants were invited back after a mean time interval of 3 years and 11 months, and after 7 years and 8 months, and their cognitive impairments were determined.Here we show that the development of cognitive impairments after approximately 8 years can be predicted not only by previously known risk factors such as ApoE4 risk alleles, dysosmia, or poor cognitive performance at baseline but that latency prolongation in the VSEP and altered functional activation patterns measured by NIRS at baseline also provide additional predictive value.We therefore suggest that both neurophysiological parameters, VSEP and NIRS, should be included in future studies, investigating the prediction of dementia. Dementia ClinicalTrials.gov Identifier: NCT02224326.

Cognitive impact of anticholinergic and sedative burden in people with HIV.

This study aims to estimate the extent to which anticholinergic and sedative burden is associated with cognitive ability and self-reported cognitive difficulties (SCD) in middle-aged and older adults living with HIV. This cross-sectional analysis examined data from the inaugural visit of participants enrolled in the Positive Brain Health Now (BHN) study. Cognitive ability was measured using the Brief Cognitive Ability Measure (B-CAM; higher is better) and SCD using the Perceived Deficits Questionnaire (PDQ; higher is worse). Medication burden was quantified using several scoring systems, including the Anticholinergic Cognitive Burden (ACB), Anticholinergic and Sedative Burden Catalog (ACSBC), Anticholinergic Drug Scale (ADS), Anticholinergic Risk Scale (ARS), and the Sedative Load Model (SLM). Multivariable Ordinary Least Squares and quantile regression were utilized to estimate average effects and distribution-specific impacts, respectively. Of 824 participants (mean age 53 years, 84.7% men), 41.4% used anticholinergics (ACSBC) and 39% used sedatives (SLM). High anticholinergic burden was linked to worse cognitive ability [ β = -3.81; 95% confidence interval (CI): -7.16, -0.46] and SCD ( β = 3.89; 95% CI: 1.08, 6.71). Using three or more anticholinergics worsened cognitive ability ( β = -4.45; 95% CI: -8.54, -0.35), and using three or more sedatives increased SCD ( β = 4.35; 95% CI: 0.92-7.78). Stronger negative associations were observed in participants with lower cognitive ability and more difficulties. These results suggest that anticholinergic and sedative burden may contribute to cognitive impairment in people with HIV. Personalized medication management and regular cognitive assessments could mitigate these adverse effects.

Associations between dual-task walking and cognitive impairment in people attending a cognitive diagnostic clinic.

Dual-task walking performance is an early marker of dementia. However, there is uncertainty about which measure of the dual-task test is a better marker. The objective of this study was to determine which dual-task measure best differentiates between normal cognition, mild cognitive impairment (MCI) and dementia. Participants (n = 116) were aged ≥60 years attending a cognitive clinic in Melbourne, Australia. Single- and dual-task gait speed were obtained using a 16 metre distance and stopwatch. The cognitive task involved reciting alternate letters of the alphabet sitting and walking. Dual-task interference in gait and cognition was calculated as: single-task-dual-task/single task × 100 and summed to obtain total interference. Multiple linear regression was used to determine differences in single and dual-task measures between those with no cognitive impairment (n = 11), MCI (n = 54) and dementia (n = 51). The mean age of the sample was 76.9 (SD 6.4) years and 48.3% (n = 56) were female. Compared to those with dementia: (a) those with MCI had a higher dual-task letter rate and lower cognitive and total interference (all indicate better performance) (p < .05) and (b) those with no cognitive impairment had a higher single- and dual-task letter rate (both indicate better performance) (p < .05). There were no differences between those with no cognitive impairment and those with MCI (all p > .05). In a cognitive clinic, measurement during dual-task walking differentiated those with dementia from those with MCI or no cognitive impairment. However, differences appear to be driven by performance on the cognitive, rather than the gait task.

Glyoxalase 1 overexpression improves neurovascular coupling and limits development of mild cognitive impairment in a mouse model of type 1 diabetes.

Diabetes is associated with cognitive impairment, but the underlying mechanism remains unclear. Methylglyoxal (MGO), a precursor to advanced glycation endproducts (AGEs), is elevated in diabetes and linked to microvascular dysfunction. In this study, overexpression of the MGO-detoxifying enzyme glyoxalase 1 (Glo1) was used in a mouse model of diabetes to explore whether MGO accumulation in diabetes causes cognitive impairment. Diabetes was induced with streptozotocin. Fasting blood glucose, cognitive function, cerebral blood flow, neurovascular coupling (NVC), Glo1 activity, MGO and AGEs were assessed. In diabetes, MGO-derived hydroimidazolone-1 increased in the cortex, and was decreased in Glo1-overexpressing mice compared to controls. Visuospatial memory was decreased in diabetes, but not in Glo1/diabetes. NVC response time was slightly increased in diabetes, and normalised in the Glo1-overexpressing group. No impact of diabetes or Glo1 overexpression on blood-brain barrier integrity or vascular density was observed. Diabetes induced a mild visuospatial memory impairment and slightly reduced NVC response speed and these effects were mitigated by Glo1. This study shows a link between MGO-related AGE accumulation and cerebrovascular/cognitive functions in diabetes. Modulation of the MGO-Glo1 pathway may be a novel intervention strategy in patients with diabetes who have cerebrovascular complications. KEY POINTS: Diabetes is associated with an increased risk of stroke, cognitive decline, depression and Alzheimer's disease, but the underlying mechanism remains unclear. Methylglyoxal (MGO), a highly reactive by-product of glycolysis, plays an important role in the development of diabetes-associated microvascular dysfunction in the periphery and is detoxified by the enzyme glyoxalase 1. Diabetes reduced visuospatial memory in mice and slowed the neurovascular coupling response speed, which was improved by overexpression of glyoxalase 1. MGO formation and MGO-derived advanced glycation endproduct (AGE) accumulation in the brain of diabetic mice are associated with a slight reduction in neurovascular coupling and mild cognitive impairment. The endogenous formation of MGO, and the accumulation of MGO-derived AGEs, might be a potential target in reducing the risk of vascular cognitive impairment in people with diabetes.

Associations between the Framingham Risk Score and cognitive functions in people with multiple sclerosis

Background &amp; Objective: Cognitive impairment is common in people with multiple sclerosis (MS). The Framingham Risk Score (FRS) is an algorithm used to estimate the 10-year risk of developing cardiovascular disease (CVDr). This study aimed to evaluate the possible associations between FRS and cognitive impairment in people with MS. Methods: Demographic characteristics, laboratory parameters, clinical findings, vascular risk factors, and Brief International Cognitive Assessment for MS (BICAMS) test results, FRS and CVDr scores were recorded for 110 MS patients. Results: FRS and CVDr scores exhibited a significant negative correlation with the number of correct responses in the Symbol Digit Modalities Test (p &lt; 0.001 for all) and California Verbal Learning Test–Second UK Edition (CVLT-II) test (p &lt; 0.001 for all), and significant positive correlation with the number of incorrect responses in the CVLT-II (p &lt; 0.001 for all). The total score of the Brief Visuospatial Memory Test Revised had a negative correlation with FRS and CVDr (p &lt; 0.001 for both). BICAMS scores showed no significant correlation with smoking status, homocysteine, and uric acid levels. Conclusion: We suppose that vascular risk factors and FRS and CVDr scores may be associated with the deterioration of working memory, information processing speed, verbal learning, and memory in people with MS. Based on the potential impact of vascular risk factors on cognitive functions, our findings suggest that lifestyle changes, appropriate treatment, and using a multidisciplinary approach toward vascular risk factors during MS management may exhibit a positive effect on cognition in people with MS.

Cognitive Trajectories in Older Adults Diagnosed With Hematologic Malignant Neoplasms

More people are surviving long-term after diagnosis with hematologic malignant neoplasm (HMN), yet there are limited data on cancer-related cognitive impairment in people with HMN. Better understanding cognitive outcomes after HMN in older adults is important for patient counseling and management. To model cognitive trajectories and rates of cognitive decline before and after HMN diagnosis in older adults compared with a matched noncancer cohort. In this population-based cohort study, older adults from the Health and Retirement Study (HRS) diagnosed with HMN between 1998 and 2016 after age 65 years were matched 1:3 to participants without cancer from the same HRS wave using propensity scores incorporating variables relevant to cognition. Cognitive trajectories were modeled with piecewise linear splines, and rates of cognitive decline before, during, and after diagnosis were compared in the 2 groups. Data were analyzed from April 2022 to April 2024. HMN diagnosis by Medicare diagnosis codes. Cognitive function was assessed by the Langa-Weir cognitive summary score from 1992 to 2020. Sociodemographic and health-related variables relevant to cognition were incorporated into propensity scores. At baseline, there were 668 participants in the HMN cohort (mean [SD] age, 76.8 [7.6] years; 343 [51.3%] male; 72 [10.8%] Black, 33 [4.9%] Hispanic, and 585 [87.6%] White) and 1994 participants in the control cohort (mean [SD] age, 76.5 [7.3] years; 1020 [51.2%] male; 226 [11.3%] Black, 91 [4.6%] Hispanic, and 1726 [86.6%] White). The HMN cohort consisted predominantly of more indolent diagnoses, and only 96 patients (14.4%) received chemotherapy. Before and in the 2 years around the time of diagnosis, the HMN and control cohorts had similar rates of cognitive decline. At 1 year postdiagnosis and beyond, the rate of cognitive decline was slower in the HMN cohort (-0.18; 95% CI, -0.23 to -0.14) than in the control group (-0.24; 95% CI, -0.26 to -0.23) (P = .02), but this difference was no longer significant after accounting for the competing risk of death (HMN group, -0.27; 95% CI, -0.34 to -0.19; control group, -0.30; 95% CI, -0.33 to -0.27; P = .48). In this cohort study of older adults, the HMN and matched noncancer control cohorts had similar rates of cognitive decline before, during, and after diagnosis after accounting for the competing risk of death.

Strategies for Achieving Better Cognitive Health in Individuals with Schizophrenia Spectrum: A Focus on the Canadian Landscape: Stratégies pour atteindre une meilleure santé cognitive chez les personnes souffrant du spectre de la schizophrénie : un regard sur le paysage canadien.

Schizophrenia spectrum disorders (SSDs) are a group of psychiatric disorders characterized by positive and negative symptoms as well as cognitive impairment that can significantly affect daily functioning. We reviewed evidence-based strategies for improving cognitive function in patients with SSDs, focusing on the Canadian landscape. Although antipsychotic medications can address the positive symptoms of SSDs, cognitive symptoms often persist, causing functional impairment and reduced quality of life. Moreover, cognitive function in patients with SSDs is infrequently assessed in clinical practice, and evidence-based recommendations for addressing cognitive impairment in people living with schizophrenia are limited. While cognitive remediation (CR) can improve several domains of cognitive function, most individuals with SSDs are currently not offered such an intervention. While the development of implementation strategies for CR is underway, available and emerging pharmacological treatments may help overcome the limited capacity for psychosocial approaches. Furthermore, combining pharmacological with non-pharmacological interventions may improve outcomes compared to pharmacotherapy or CR alone. This review highlights the challenges and discusses the potential solutions related to the assessment and management of cognitive impairment to help mental health-care practitioners better manage cognitive impairment and improve daily functioning in individuals with SSDs.

Association between Cardiometabolic Index and Cognitive Function: A Cross-Sectional Study in a Diabetic-Based Population

s Introduction: Diabetes is a significant risk factor for cognitive impairment. Therefore, early identification of cognitive impairment in diabetic patients is particularly important. The aim of this study was to assess the relationship between Cardiometabolic index (CMI) and cognitive function in a diabetic population. Methods: A cross-sectional study was conducted by collecting information from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Multiple linear regression models were used to investigate the correlation between CMI and low cognitive function in a diabetic population. Threshold effects analysis and fitted smoothing curves were used to describe the nonlinear links. Interaction tests and subgroup analyses were also performed. Results: A total of 1,050 people participated in this study, including 561 men and 489 women. In the fully corrected model, CMI was positively associated with low cognitive performance as assessed by CERAD Word List Learning Test (CERAD W-L), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) (OR = 1.37 [1.14, 1.72], p = 7.4 × 10−3), (OR = 1.21 [1.04, 1.51], p = 1.26 × 10−2), and (OR = 1.27 [1.08, 1.63], p = 2.53 × 10−2). Our study found that diabetic patients with higher CMI were at greater risk of developing low cognitive function. The effect of the subgroups on the positive association of CMI with cognitive impairment was not significant. A non-linear association between low cognitive performance and CMI was determined by CERAD W-L, AFT, and DSST (log-likelihood ratio <5 × 10−2). In addition, our also study found that CMI was a better predictor of cognitive impairment in diabetes than weight-adjusted waist index (WWI). Conclusion: Increased CMI is associated with an increased risk of cognitive impairment in people with diabetes. CMI can be used as a new anthropometric measure for predicting cognitive impairment in diabetes, with stronger predictive power than WWI.

#3042 Prevalence and associations of impaired cognitive function for people with chronic kidney disease: baseline findings from the NURTuRE-CKD cohort study

Abstract Background and Aims Chronic kidney disease (CKD) is known to be associated with impaired cognitive function, with lower estimated glomerular filtration rate (eGFR) associated with poorer cognitive performance [1]. Though CKD prevalence increases with age, the association with cognitive disorders is not entirely explained by age distribution. Cognitive impairment in CKD is multifactorial with potential biochemical, cardiovascular, medication and socio-economic mediators. As with other long-term conditions, self-management of kidney disease becomes more difficult in the context of cognitive impairment. The prevalence and associations of cognitive impairment in people referred to secondary care with CKD is not well described. This study therefore aimed to identify the prevalence and associations of impaired cognitive function among a referred population of people with CKD. Method The NURTuRE-CKD cohort recruited 2996 people with an estimated Glomerular Filtration Rate (eGFR) of 15-59 ml/min/1.73 m2 (CKD-EPI equation) or ≥60 ml/min/1.73 m2 with a urine albumin to creatinine ratio (uACR) of more than 30 mg/mmol referred to one of 16 secondary care nephrology clinics. Baseline data were collected between 2017-2019 including sociodemographic, anthropometric, biochemical, and clinical information and included the 6-item cognitive impairment test (6-CIT), a commonly used cognitive screening instrument. Other scores collected included the Hospital Anxiety and Depression score (HADS), EQ-5D-5L as a health-related quality of life (HRQoL) measure and Single Item Literacy Screener (SILS). Prevalence of impaired cognitive function (defined as 6-CIT score of 8 or more out of 28) was calculated and multivariable mixed effects logistic regression models used to identify associations with impaired cognitive function. The multivariable model was adjusted for known factors impacting cognitive impairment and recruitment region as a random effect. Results A total of 2743/2996 (91.6%) participants had complete 6-CIT data. Median age was 66 years and 41% were female. Median eGFR was 34 ml/min/1.73 m2. Prevalence of cognitive impairment was 8.7% (240/2743), rising from 5.3% in those &amp;lt;65 to 10.6% in those ≥65 years. eGFR was not associated with cognitive impairment on univariate analysis. After adjustment, greater likelihood of cognitive impairment was independently associated with older age, Asian and Black ethnicity (compared to white), and limited health literacy. Lower likelihood of cognitive impairment was associated with better HRQoL and higher education attainment (Figs 1 and 2). Conclusion Cognitive impairment was relatively common in this cohort of people with CKD. Similar associations for cognitive impairment with age and education in a CKD population had also been identified in CKD-REIN—a prospective cohort of CKD patients recruited from secondary care in France, though using a different cognitive function measure. Associations of limited health literacy, ethnicity, and HRQoL with cognitive impairment were identified risk factors that could aid clinicians in recognising high risk patients to prompt screening and improve management. Follow-up data will allow longitudinal analyses to explore associations between impaired cognitive function and health-related outcomes, between kidney function and change in cognitive function and risk factors for change in cognitive function, including the role of inflammatory markers. Limitations: this analysis only used baseline data so causality cannot be established, 6-CIT is a screening rather than diagnostic tool for cognitive impairment.

Cerebral-cognitive reserve: concept and functions of the cerebral-cognitive reserve

IntroductionThe modern understanding of AD allows us to consider it through the constructs of “vulnerability” and “stability” of the brain as a dynamic system of dialectical interaction between the pathogenic process and the protective process that prevents neurodegeneration. The concept of cognitive reserve (CR) is based on observations of discrepancy between the degree of brain pathology and the severity of clinical manifestations. The concept of “reserve” was proposed to describe the resistance of the brain to a developing damage caused by a pathological process. Stern (2002) considered CR as a protective factor that modifies the impact of brain pathology on cognitive function. The researchers have defined CR as an ability to optimize cognitive function through differential involvement of structures or neural networks of the brain into brain activity.ObjectivesA systematic review of scientific studies has been conductedMethodsThe review includes an analysis of full-text literature sources.ResultsSeveral possible directions of CR influence on cognitive functions have been described:1)CR may reduce the risk of MCI or dementia through mechanisms, which do not depend on the level of neurodegenerative pathological changes in the brain.2)CR can interact with the markers of brain pathology or healthaffectingthe future cognitive decline or risk of progression. It has been found that smaller volumes or thickness in some AD vulnerable areas of the brain represent a stronger risk factor for cognitive impairment in people with low CR than in people with higher CR. CR protective effects on clinical outcomes reduce as the number of damaged neurons increases.3)The protective effect of CR increasesduring late AD onset and at a low rate of the damaged substrate accumulation.4)CR changes the relationship between genetic factors and aging withclinical and cognitive outcomes. The relationship between age and AD pathology level or age-related structural changes in the brain may weaken in people with higher CR ConclusionsThe concept of cerebral-cognitive reserve actualizes the problem of the search for compensatory mechanisms of cognitive deficit in AD, the assessmentof the structure of the reserve, the development and implementationof programs to maintain the reserve, the preventionof its depletion, starting from the preclinical stage of the disease, which can prevent the transformation of preclinical manifestations of AD into cognitive disordersDisclosure of InterestNone Declared

Cognitive Impairment in People Living with HIV and the Impact of Mood: Results from a Cross-Sectional Study.

Background: Human Immunodeficiency Virus (HIV) infection represents a significant public health concern and, consequently, the incidence of HIV-Associated Neurocognitive Disorder (HAND) has grown over the years. The present study aims to assess HAND with the Montreal Cognitive Assessment (MoCA) in People Living With HIV/AIDS (PLWHA) to find significant associations with cognitive impairment. Methods: The study included 210 PLWHA, aged from 30 to 81 years, of whom, 137 (65.2%) were males. They were assessed at the Immunology Service of the University Hospital of Monserrato, Cagliari, Italy, between November 2022 and April 2023. Results: The sample showed an overall optimal response to antiretroviral therapy, as shown by the excellent levels of CD4+ lymphocytes and HIV RNA copies. A sum of 115 subjects (54.8%) were considered cognitively impaired and the multivariate analysis demonstrated that it was independently associated with duration of infection (OR: 0.96), age (OR: 1.12), alanine aminotransferase (ALT) (OR: 1.02), and depression (OR: 1.33). By dichotomizing the variables, the significance of the association was confirmed for age (65-year threshold) (χ2: 5.142, p = 0.0233) and depression (χ2: 7.834, p = 0.0051). Conclusions: Our study demonstrates that it is hard to find both statistically and clinically significantly associated variables with cognitive impairment in PLWHA, and that the strongest independent association is with depressed mood.

Identifying and understanding cognitive profiles in multiple sclerosis: a role for visuospatial memory functioning

BackgroundThe heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired).MethodsWe included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing–remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ − 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification.ResultsSix profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997).ConclusionsThis study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.

Abstract TP18: A 15-Minute Cognitive Screen Identifies Post-Stroke Cognitive Impairment

Introduction: While comprehensive neuropsychological evaluations are a valuable part of post-stroke care, time-intensive assessments may not always be feasible or well-tolerated in certain clinical settings. There is a need for a brief cognitive battery that can detect post-stroke cognitive impairment while being efficient with regard to time and resources. Methods: As part of the parallel StrokeCog and Stroke-IMPaCT studies, 127 participants with chronic ischemic stroke completed comprehensive neuropsychological testing at Stanford. They underwent a cognitive battery consisting of 13 tests that encompassed 5 cognitive domains. Partial least square analyses identified a set of candidate tests that were most associated with cognitive impairment on this comprehensive battery, defined as 2 domain z-scores &lt;-1 or 1 domain z-score &lt;-1.5. We used these candidate tests to construct a brief battery of 5 tests (StrokeCog-Brief). Psychometric properties were compared amongst StrokeCog-Brief, the MoCA, and another established 30-minute battery (NINDS-30). Initial findings were cross-validated in an independent sample of 61 participants at University of Manchester. Results: The StrokeCog-Brief battery consisted of 5 measures of language, working memory, learning, and attention/processing speed (HVLT Immediate Recall, Trails A, Trails B, Digit Span Forward/Backward, Phonemic Fluency) that took approximately 15 minutes to complete. StrokeCog-Brief demonstrated high sensitivity (0.97) and adequate specificity (0.78) in detecting cognitive impairment on the comprehensive battery, outperforming both the MoCA (0.77, 0.73) and NINDS-30 (0.97, 0.35). In the cross-validation sample, StrokeCog-Brief similarly demonstrated high sensitivity (0.93) and adequate specificity (0.67), again outperforming both the MoCA (0.60, 0.86) and NINDS-30 (0.81, 0.08). Conclusions: We identified a brief, 15-minute battery of 5 tests that has high sensitivity in detecting cognitive impairment in people who have had a stroke. This brief battery covers multiple cognitive domains commonly impacted by stroke and represents an efficient means to identify chronic post-stroke cognitive impairment.

Isolated cognitive impairment in people with multiple sclerosis: frequency, MRI patterns and its development over time

ObjectivesTo study the frequency of isolated (i.e., single-domain) cognitive impairments, domain specific MRI correlates, and its longitudinal development in people with multiple sclerosis (PwMS).Methods348 PwMS (mean age 48 ± 11 years, 67% female, 244RR/52SP/38PP) underwent neuropsychological testing (extended BRB-N) at baseline and at five-year follow-up. At baseline, structural MRI was acquired. Isolated cognitive impairment was defined as a Z-score of at least 1.5 SD below normative data in one domain only (processing speed, memory, executive functioning/working memory, and attention). Multi-domain cognitive impairment was defined as being affected in ≥ 2 domains, and cognitively preserved otherwise. For PwMS with isolated cognitive impairment, MRI correlates were explored using linear regression. Development of isolated cognitive impairment over time was evaluated based on reliable change index.ResultsAt baseline, 108 (31%) PwMS displayed isolated cognitive impairment, 148 (43%) PwMS displayed multi-domain cognitive impairment. Most PwMS with isolated cognitive impairment were impaired on executive functioning/working memory (EF/WM; N = 37), followed by processing speed (IPS; N = 25), memory (N = 23), and attention (N = 23). Isolated IPS impairment was explained by a model of cortical volume and fractional anisotropy (adj. R2 = 0.539, p < 0.001); memory by a model with cortical volume and hippocampal volume (adj. R2 = 0.493, p = 0.002); EF/WM and attention were not associated with any MRI measure. At follow-up, cognitive decline was present in 11/16 (69%) of PwMS with isolated IPS impairment at baseline. This percentage varied between 18 and 31% of PwMS with isolated cognitive impairment in domains other than IPS at baseline.ConclusionIsolated cognitive impairment is frequently present in PwMS and can serve as a proxy for further decline, particularly when it concerns processing speed. Cortical and deep grey matter atrophy seem to play a pivotal role in isolated cognitive impairment. Timely detection and patient-tailored intervention, predominantly for IPS, may help to postpone further cognitive decline.

Don’t be late! Timely identification of cognitive impairment in people with multiple sclerosis: a study protocol

BackgroundCognitive impairment occurs in up to 65% of people with multiple sclerosis (PwMS), negatively affecting daily functioning and health-related quality of life. In general, neuropsychological testing is not part of standard MS-care due to insufficient time and trained personnel. Consequently, a baseline assessment of cognitive functioning is often lacking, hampering early identification of cognitive decline and change within a person over time. To assess cognitive functioning in PwMS in a time-efficient manner, a BICAMS-based self-explanatory digital screening tool called the Multiple Screener©, has recently been developed. The aim of the current study is to validate the Multiple Screener© in a representative sample of PwMS in the Netherlands. Additionally, we aim to investigate how cognitive functioning is related to psychological factors, and both work and societal participation.MethodsIn this cross-sectional multicentre study, 750 PwMS (aged 18–67 years) are included. To obtain a representative sample, PwMS are recruited via 12 hospitals across the Netherlands. They undergo assessment with the Minimal Assessment of Cognitive Functioning in MS (MACFIMS; reference-standard) and the Multiple Screener©. Sensitivity, specificity, and predictive values for identifying (mild) cognitive impairment are determined in a subset of 300 participants. In a second step, the identified cut-off values are tested in an independent subset of at least 150 PwMS. Moreover, test–retest reliability for the Multiple Screener© is determined in 30 PwMS. Information on psychological and work-related factors is assessed with questionnaires.DiscussionValidating the Multiple Screener© in PwMS and investigating cognition and its determinants will further facilitate early identification and adequate monitoring of cognitive decline in PwMS.

Mobile Health App (DIGICOG-MS) for Self-Assessment of Cognitive Impairment in People With Multiple Sclerosis: Instrument Validation and Usability Study.

Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and monitor cognitive impairment, one of the most disturbing symptoms in MS that is experienced by almost 43% to 70% of people with MS. Therefore, we developed DIGICOG-MS (Digital assessment of Cognitive Impairment in Multiple Sclerosis), a smartphone- and tablet-based mHealth app to self-assess cognitive impairment in MS. This study aimed to test the validity and usability of the novel mHealth app with a sample of people with MS. DIGICOG-MS includes 4 digital tests assumed to evaluate the most affected cognitive domains in MS (visuospatial memory [VSM], verbal memory [VM], semantic fluency [SF], and information processing speed [IPS]) and inspired by traditional paper-based tests that assess the same cognitive functions (10/36 Spatial Recall Test, Rey Auditory Verbal Learning Test, Word List Generation, Symbol Digit Modalities Test). Participants were asked to complete both digital and traditional assessments in 2 separate sessions. Convergent validity was analyzed using the Pearson correlation coefficient to determine the strength of the associations between digital and traditional tests. To test the app's reliability, the agreement between 2 repeated measurements was assessed using intraclass correlation coefficients (ICCs). Usability of DIGICOG-MS was evaluated using the System Usability Scale (SUS) and mHealth App Usability Questionnaire (MAUQ) administered at the conclusion of the digital session. The final sample consisted of 92 people with MS (60 women) followed as outpatients at the Italian Multiple Sclerosis Society (AISM) Rehabilitation Service of Genoa (Italy). They had a mean age of 51.38 (SD 11.36) years, education duration of 13.07 (SD 2.74) years, disease duration of 12.91 (SD 9.51) years, and a disability level (Expanded Disability Status Scale) of 3.58 (SD 1.75). Relapsing-remitting MS was most common (68/92, 74%), followed by secondary progressive (15/92, 16%) and primary progressive (9/92, 10%) courses. Pearson correlation analyses indicated significantly strong correlations for VSM, VM, SF, and IPS (all P<.001), with r values ranging from 0.58 to 0.78 for all cognitive domains. Test-retest reliability of the mHealth app was excellent (ICCs>0.90) for VM and IPS and good for VSM and SF (ICCs>0.80). Moreover, the SUS score averaged 84.5 (SD 13.34), and the mean total MAUQ score was 104.02 (SD 17.69), suggesting that DIGICOG-MS was highly usable and well appreciated. The DIGICOG-MS tests were strongly correlated with traditional paper-based evaluations. Furthermore, people with MS positively evaluated DIGICOG-MS, finding it highly usable. Since cognitive impairment poses major limitations for people with MS, these findings open new paths to deploy digital cognitive tests for MS and further support the use of a novel mHealth app for cognitive self-assessment by people with MS in clinical practice.

Machine learning for predicting cognitive deficits using auditory and demographic factors.

Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. Detecting cognitive impairment in people living with HIV (PLWH) is important for early intervention, especially in low- to middle-income countries where most cases exist. Auditory tests relate to neurocognitive test results, but the incremental predictive capability beyond demographic factors is unknown. Use machine learning to predict neurocognitive deficits, using auditory tests and demographic factors. The Infectious Disease Center in Dar es Salaam, Tanzania. Participants were 939 Tanzanian individuals from Dar es Salaam living with and without HIV who were part of a longitudinal study. Patients who had only one visit, a positive history of ear drainage, concussion, significant noise or chemical exposure, neurological disease, mental illness, or exposure to ototoxic antibiotics (e.g., gentamycin), or chemotherapy were excluded. This provided 478 participants (349 PLWH, 129 HIV-negative). Participant data were randomized to training and test sets for machine learning. The main outcome was whether auditory variables combined with relevant demographic variables could predict neurocognitive dysfunction (defined as a score of <26 on the Kiswahili Montreal Cognitive Assessment) better than demographic factors alone. The performance of predictive machine learning algorithms was primarily evaluated using the area under the receiver operational characteristic curve. Secondary metrics for evaluation included F1 scores, accuracies, and the Youden's indices for the algorithms. The percentage of individuals with cognitive deficits was 36.2% (139 PLWH and 34 HIV-negative). The Gaussian and kernel naïve Bayes classifiers were the most predictive algorithms for neurocognitive impairment. Algorithms trained with auditory variables had average area under the curve values of 0.91 and 0.87, F1 scores (metric for precision and recall) of 0.81 and 0.76, and average accuracies of 86.3% and 81.9% respectively. Algorithms trained without auditory variables as features were statistically worse (p < .001) in both the primary measure of area under the curve (0.82/0.78) and the secondary measure of accuracy (72.3%/74.5%) for the Gaussian and kernel algorithms respectively. Auditory variables improved the prediction of cognitive function. Since auditory tests are easy-to-administer and often naturalistic tasks, they may offer objective measures or predictors of neurocognitive performance suitable for many global settings. Further research and development into using machine learning algorithms for predicting cognitive outcomes should be pursued.

Analysis of the difference between Alzheimer's disease, mild cognitive impairment and normal people by using fractal dimensions and small-world network.

This research examined the distinctions in brain network characteristics among individuals with Alzheimer's disease (AD), mild cognitive impairment (MCI), and a control group. Magnetic resonance imaging (MRI) and mini-mental state examination (MMSE) data were retrieved from the Alzheimer's Disease Neuroimaging Initiative (ANDI) database, comprising 40 subjects in each group. Correlation maps for evaluating brain network connectivity were generated using fractal dimension (FD) analysis, a method capable of quantifying morphological changes in cortical and cerebral regions. Employing graph theory, each parcellated brain region was represented as a node, and edges between nodes were utilized to compute small-world network properties for each group. In the comparison between control and AD demonstrated the significantly lower FD values (P<0.05) in temporal lobe, motor cortex, part of occipital and parietal, hippocampus, amygdala, and entorhinal cortex, which present the atrophy. Similarly, comparing control group to MCIs, regions closely associated with memory, such as the hippocampus, showed significantly lower FD values. Furthermore, both AD and MCI groups displayed diminished connectivity and decreased network efficiency. In conclusion, fractal dimension (FD) analysis illustrate the progression of structural declination from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Additionally, structural small-world network analysis presents itself as a potential method for assessing network efficiency and the progression of AD. Moving forward, further clinical assessments are warranted to validate the findings observed in this study.

Anticholinergic deprescribing interventions for reducing risk of cognitive decline or dementia in older adults with and without prior cognitive impairment.

Anticholinergics are medications that block the action of acetylcholine in the central or peripheral nervous system. Medications with anticholinergic properties are commonly prescribed to older adults. The cumulative anticholinergic effect of all the medications a person takes is referred to as the anticholinergic burden. A high anticholinergic burden may cause cognitive impairment in people who are otherwise cognitively healthy, or cause further cognitive decline in people with pre-existing cognitive problems. Reducing anticholinergic burden through deprescribing interventions may help to prevent onset of cognitive impairment or slow the rate of cognitive decline. Primary objective • To assess the efficacy and safety of anticholinergic medication reduction interventions for improving cognitive outcomes in cognitively healthy older adults and older adults with pre-existing cognitive issues. Secondary Objectives • To compare the effectiveness of different types of reduction interventions (e.g. pharmacist-led versus general practitioner-led, educational versus audit and feedback) for reducing overall anticholinergic burden. • To establish optimal duration of anticholinergic reduction interventions, sustainability, and lessons learnt for upscaling • To compare results according to differing anticholinergic scales used in medication reduction intervention trials • To assess the efficacy of anticholinergic medication reduction interventions for improving other clinical outcomes, including mortality, quality of life, clinical global impression, physical function, institutionalisation, falls, cardiovascular diseases, and neurobehavioral outcomes. We searched CENTRAL on 22 December 2022, and we searched MEDLINE, Embase, and three other databases from inception to 1 November 2022. We included randomised controlled trials (RCTs) of interventions that aimed to reduce anticholinergic burden in older people and that investigated cognitive outcomes. Two review authors independently assessed studies for inclusion, extracted data, and assessed the risk of bias of included studies. The data were not suitable for meta-analysis, so we summarised them narratively. We used GRADE methods to rate our confidence in the review results. We included three trials with a total of 299 participants. All three trials were conducted in a cognitively mixed population (some cognitively healthy participants, some participants with dementia). Outcomes were assessed after one to three months. One trial reported significantly improved performance on the Digit Symbol Substitution Test (DSST) in the intervention group (treatment difference 0.70, 95% confidence interval (CI) 0.11 to 1.30), although there was no difference between the groups in the proportion of participants with reduced anticholinergic burden. Two trials successfully reduced anticholinergic burden in the intervention group. Of these, one reported no significant difference between the intervention versus control in terms of their effect on cognitive performance measured by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) immediate recall (mean between-group difference 0.54, 95% CI -0.91 to 2.05), CERAD delayed recall (mean between-group difference -0.23, 95% CI-0.85 to 0.38), CERAD recognition (mean between-group difference 0.77, 95% CI -0.39 to 1.94), and Mini-Mental State Examination (mean between-group difference 0.39, 95% CI -0.96 to 1.75). The other trial reported a significant correlation between anticholinergic burden and a test of working memory after the intervention (which suggested reducing the burden improved performance), but reported no effect on multiple other cognitive measures. In GRADE terms, the results were of very low certainty. There were no reported between-group differences for any other clinical outcome we investigated. It was not possible to investigate differences according to type of reduction intervention or type of anticholinergic scale, to measure the sustainability of interventions, or to establish lessons learnt for upscaling. No trials investigated safety outcomes. There is insufficient evidence to reach any conclusions on the effects of anticholinergic burden reduction interventions on cognitive outcomes in older adults with or without prior cognitive impairment. The evidence from RCTs was of very low certainty so cannot support or refute the hypothesis that actively reducing or stopping prescription of medications with anticholinergic properties can improve cognitive outcomes in older people. There is no evidence from RCTs that anticholinergic burden reduction interventions improve other clinical outcomes such as mortality, quality of life, clinical global impression, physical function, institutionalisation, falls, cardiovascular diseases, or neurobehavioral outcomes. Larger RCTs investigating long-term outcomes are needed. Future RCTs should also investigate potential benefits of anticholinergic reduction interventions in cognitively healthy populations and cognitively impaired populations separately.