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Carotid artery atherosclerosis, the result of a multitude of vascular risk factors, is a promising marker for use in risk stratification. Recent evidence suggests that carotid artery atherosclerosis affects cognitive function and is an independent risk factor for the development of cognitive impairment. Both atherosclerosis and cognitive impairment develop over a prolonged period (years), and due to the aging population, markers to identify persons at risk are needed. Carotid artery atherosclerosis can easily be visualized using non-invasive ultrasound, potentially enabling early and intensified risk factor management to preserve cognitive function or delay further decline. However, the burden of atherosclerosis and temporal exposure required to pose a risk of cognitive impairment is unclear. This mini-review aims to explore the available evidence on the association between carotid atherosclerosis and cognition, and furthermore identify the remaining gaps in knowledge. [ABSTRACT FROM AUTHOR]

Introduction: Post-stroke cognitive impairment (PSCI) is common, but evidence on the impact of vascular risk factors is lacking. We explored the association between pre-stroke vascular risk factors and PSCI and studied the course of PSCI. Materials and Methods: Vascular risk factors were collected at baseline in stroke survivors (n = 635). Cognitive assessments of attention, executive function, memory, language, and the Montreal Cognitive Assessment (MoCA) were performed at 3 and/or 18 months post-stroke. Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS). PSCI was measured with global z; MoCA z-score; and z-score of the four assessed cognitive domains. Mixed-effect linear regression was applied with global z, MoCA z-score, and z-scores of the cognitive domains as dependent variables. Independent variables were the vascular risk factors (hypertension, hypercholesterolemia, smoking, diabetes mellitus, atrial fibrillation, coronary heart disease, previous stroke), time, and the interaction between these. The analyses were adjusted for age, education, and sex. There were between 5 and 25% missing data for the variables for PSCI. Results: Mean age was 71.6 years (SD 11.7); 42% were females; and the mean NIHSS score at admittance was 3.8 (SD 4.8). Regardless of vascular risk factors, global z, MoCA, and all the assessed cognitive domains were impaired at 3 and 18 months, with MoCA being the most severely impaired. Atrial fibrillation (AF) was associated with poorer language at 18 months and coronary heart disease (CHD) with poorer MoCA at 18 months (LR = 12.80, p = 0.002, and LR = 8.32, p = 0.004, respectively). Previous stroke was associated with poorer global z and attention at 3 and 18 months (LR = 15.46, p < 0.001, and LR = 16.20, p < 0.001). In patients without AF, attention improved from 3 to 18 months, and in patients without CHD, executive function improved from 3 to 18 months (LR = 10.42, p < 0.001, and LR = 9.33, p = 0.009, respectively). Discussion: Our findings indicate that a focal stroke lesion might be related to pathophysiological processes leading to global cognitive impairment. The poorer prognosis of PSCI in patients with vascular risk factors emphasizes the need for further research on complex vascular risk factor interventions to prevent PSCI. [ABSTRACT FROM AUTHOR]

Post‐stroke fatigue (PSF) is prevalent among stroke patients, but its mechanisms are poorly understood. Many patients with PSF experience cognitive difficulties, but studies aiming to identify cognitive correlates of PSF have been largely inconclusive. With the aim of characterizing the relationship between subjective fatigue and attentional function, we collected behavioral data using the attention network test (ANT) and self‐reported fatigue scores using the fatigue severity scale (FSS) from 53 stroke patients. In order to evaluate the utility and added value of computational modeling for delineating specific underpinnings of response time (RT) distributions, we fitted a hierarchical drift diffusion model (hDDM) to the ANT data. Results revealed a relationship between fatigue and RT distributions. Specifically, there was a positive interaction between FSS score and elapsed time on RT. Group analyses suggested that patients without PSF increased speed during the course of the session, while patients with PSF did not. In line with the conventional analyses based on observed RT, the best fitting hDD model identified an interaction between elapsed time and fatigue on non‐decision time, suggesting an increase in time needed for stimulus encoding and response execution rather than cognitive information processing and evidence accumulation. These novel results demonstrate the significance of considering the sustained nature of effort when defining the cognitive phenotype of PSF, intuitively indicating that the cognitive phenotype of fatigue entails an increased vulnerability to sustained effort, and suggest that the use of computational approaches offers a further characterization of specific processes underlying behavioral differences. [ABSTRACT FROM AUTHOR]

Background: Post-stroke cognitive impairment (PSCI) is common, but evidence of cognitive symptom profiles, course over time, and pathogenesis is scarce. We investigated the significance of time and etiologic stroke subtype for the probability of PSCI, severity, and cognitive profile. Methods: Stroke survivors (n = 617) underwent cognitive assessments of attention, executive function, memory, language, perceptual-motor function, and the Montreal Cognitive Assessment (MoCA) after 3 and/or 18 months. PSCI was classified according to DSM-5 criteria. Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS). Stroke subtype was categorized as intracerebral hemorrhage (ICH), large artery disease (LAD), cardioembolic stroke (CE), small vessel disease (SVD), or un-/other determined strokes (UD). Mixed-effects logistic or linear regression was applied with PSCI, MoCA, and z-scores of the cognitive domains as dependent variables. Independent variables were time as well as stroke subtype, time, and interaction between these. The analyses were adjusted for age, education, and sex. The effects of time and stroke subtype were analyzed by likelihood ratio tests (LR). Results: Mean age was 72 years (SD 12), 42% were females, and mean NIHSS score at admittance was 3.8 (SD 4.8). Probability (95% CI) for PSCI after 3 and 18 months was 0.59 (0.51–0.66) and 0.51 (0.52–0.60), respectively and remained constant over time. Global measures and most cognitive domains were assessed as impaired for the entire stroke population and for most stroke subtypes. Executive function and language improved for the entire stroke population (LR) = 9.05, p = 0.003, and LR = 10.38, p = 0.001, respectively). After dividing the sample according to stroke subtypes, language improved for ICH patients (LR = 18.02, p = 0.003). No significant differences were found in the severity of impairment between stroke subtypes except for attention, which was impaired for LAD and CE in contrast to no impairment for SVD (LR = 56.58, p < 0.001). Conclusions: In this study including mainly minor strokes, PSCI is common for all subtypes, both early and long-term after stroke, while executive function and language improve over time. The findings might contribute to personalizing follow-up and offer new insights into underlying mechanisms. Further research is needed on underlying mechanisms, PSCI prevention and treatment, and relevance for rehabilitation. [ABSTRACT FROM AUTHOR]

Background: Studies on the relationship between carotid atherosclerosis and cognitive function in subjects from the general population are few and results have been inconsistent.Objective: We aimed to investigate the association between carotid atherosclerotic burden and cognitive function in a cross-sectional analysis of a population-based cohort aged 63-65 years.Methods: All habitants born in 1950 from Akershus County, Norway were invited to participate. A linear regression model was used to assess the association between carotid atherosclerosis and cognitive function. We used carotid plaque score as a measure of carotid atherosclerotic burden and the Montreal Cognitive Assessment (MoCA) for global cognitive function.Results: We analyzed 3,413 individuals aged 63-65 with mean MoCA score 25.3±2.9 and 87% visible carotid plaques. We found a negative correlation between carotid plaque score and MoCA score (r = -0.14, p < 0.001), but this association was lost in multivariable analysis. In contrast, diameter or area of the thickest plaque was independently associated with MoCA score. Lower educational level, male sex, current smoking, and diabetes were also associated with lower MoCA score in multivariable analysis.Conclusion: Carotid atherosclerotic burden was, unlike other measures of advanced carotid atherosclerosis, not independently associated with global cognitive function. [ABSTRACT FROM AUTHOR]

Atherosclerosis, ischemic stroke, secondary prevention, atheroinflammation, plaque, cognition, extracranial carotid stenosis Keywords: extracranial carotid stenosis; atherosclerosis; ischemic stroke; secondary prevention; atheroinflammation; plaque; cognition EN extracranial carotid stenosis atherosclerosis ischemic stroke secondary prevention atheroinflammation plaque cognition 1 2 2 04/08/22 20220406 NES 220406 Extracranial internal carotid artery stenosis is a leading cause of ischemic stroke. Today, stroke physicians on call assess and identify internal carotid artery stenosis on duplex ultrasound or CT angiography as part of the acute diagnostic work up and decision making regarding the potential cause and most beneficial intervention in the acute phase ([1], [2]). [Extracted from the article]

Aims: Clinical guidelines recommend stroke patients are routinely screened for cognitive impairment. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was evaluated for screening for post-stroke cognitive impairment. Methods: The RBANS and a neuropsychological test battery were administered to 60 participants recruited from acute stroke wards. Results: Using a cut-off of <70 points, the RBANS Total Index demonstrated 50% sensitivity and 100% specificity for detecting any cognitive impairment. ROC curve analysis identified an optimum total index cut-off score of <84 points (sensitivity 84%; specificity 90%). The RBANS Indices did not have acceptable sensitivity and specificity using a cut-off of <70 points. ROC curve analysis identified higher optimum cut-offs (sensitivity 79-89%; specificity 48-96%). Conclusion: The RBANS was an acceptable measure for detecting post-stroke cognitive impairment but does not include assessment of executive ability. [ABSTRACT FROM AUTHOR]