OBJECTIVE: To assess correlative strengths of quantitative electroencephalography (qEEG) and visual rating scale EEG features on cognitive outcomes in only autopsied cases from the Arizona Study of Neurodegenerative Disorders (AZSAND). We hypothesized that autopsy proven Parkinson Disease will show distinct EEG features from Alzheimer\'s Disease prior to dementia (mild cognitive impairment).
BACKGROUND: Cognitive decline is debilitating across neurodegenerative diseases. Resting-state EEG analysis, including spectral power across frequency bins (qEEG), has shown significant associations with neurodegenerative disease classification and cognitive status, with autopsy confirmed diagnosis relatively lacking.
METHODS: Biannual EEG was analyzed from autopsied cases in AZSAND who had at least one rsEEG (>1 min eyes closed±eyes open). Analysis included global relative spectral power and a previously described visual rating scale (VRS). Linear mixed regression was performed for neuropsychological assessment and testing within 2 years of death (n = 236, 594 EEG exams) in a mixed linear regression model.
RESULTS: The cohort included cases with final clinicopathologic diagnoses of Parkinson\'s disease (n = 73), Alzheimer disease (n = 65), and tauopathy not otherwise specified (n = 56). A VRS score of 3 diffuse or frequent generalized slowing) over the study duration was associated with an increase in consensus diagnosis cognitive worsening at 4.9 (3.1) years (HR 2.02, CI 1.05-3.87). Increases in global theta power% and VRS were the most consistently associated with large regression coefficients inversely with cognitive performance measures.
CONCLUSIONS: Resting-state EEG analysis was meaningfully related to cognitive performance measures in a community-based autopsy cohort. EEG deserves further study and use as a cognitive biomarker.

UNASSIGNED: Alzheimer\'s disease (AD) is highly heterogeneous, with substantial individual variabilities in clinical progression and neurobiology. Amyloid deposition has been thought to drive cognitive decline and thus a major contributor to the variations in cognitive deterioration in AD. However, the clinical heterogeneity of patients with early symptomatic AD (mild cognitive impairment or mild dementia due to AD) already with evidence of amyloid abnormality in the brain is still unknown.
UNASSIGNED: Participants with a baseline diagnosis of mild cognitive impairment or mild dementia, a positive amyloid-PET scan, and more than one follow-up Alzheimer\'s Disease Assessment Scale-Cognitive Subscale-13 (ADAS-Cog-13) administration within a period of 5-year follow-up were selected from the Alzheimer\'s Disease Neuroimaging Initiative database (n = 421; age = 73±7; years of education = 16 ± 3; percentage of female gender = 43%; distribution of APOE4 carriers = 68%). A non-parametric k-means longitudinal clustering analysis in the context of the ADAS-Cog-13 data was performed to identify cognitive subtypes.
UNASSIGNED: We found a highly variable profile of cognitive decline among patients with early AD and identified 4 clusters characterized by distinct rates of cognitive progression. Among the groups there were significant differences in the magnitude of rates of changes in other cognitive and functional outcomes, clinical progression from mild cognitive impairment to dementia, and changes in markers presumed to reflect neurodegeneration and neuronal injury. A nomogram based on a simplified logistic regression model predicted steep cognitive trajectory with an AUC of 0.912 (95% CI: 0.88 - 0.94). Simulation of clinical trials suggested that the incorporation of the nomogram into enrichment strategies would reduce the required sample sizes from 926.8 (95% CI: 822.6 - 1057.5) to 400.9 (95% CI: 306.9 - 516.8).
UNASSIGNED: Our findings show usefulness in the stratification of patients in early AD and may thus increase the chances of finding a treatment for future AD clinical trials.

BACKGROUND: Patterns of cognitive change and modifiable factors for cognitive decline versus stable cognitive trajectories have rarely been described in lower-educated older adults.
OBJECTIVE: We aimed to identify long-term trajectories of cognitive functioning and possible factors associated with cognitive decline.
METHODS: We used data from 1,042 adults aged ≥ 60 participating in the Health, Welfare and Aging Study (SABE), São Paulo, Brazil, without cognitive impairment at baseline. Data were collected across four waves (2000-2015). Group-based trajectory modelling was used to identify cognitive trajectories. Associations with socioeconomic variables, childhood background, lifestyle, and cardiovascular risk factors were explored using weighted multinomial logistic regressions.
METHODS: The abbreviated Mini-Mental State Examination was used to measure cognition.
RESULTS: Three cognitive trajectories were identified: stable (n= 754, 68.6%), mild-decline (n= 183, 20.8%), and strong-decline (n= 105, 10.7%). At baseline, respondents in the strong-decline group were more likely to be older than those with stable and mild-decline trajectories. Furthermore, participants in both the mild and strong-decline groups were more likely to have no schooling, be divorced/separated, receive less than 4 monthly wages, and be underweight (BMI < 18.5) compared to the stable group. Finally, the mild-decline group was more likely to have lived in rural areas during childhood than participants located in a stable trajectory.
CONCLUSIONS: Our findings suggest that interventions to reduce cognitive decline for low-educated older adults might include strategies addressing inequalities and improving modifiable risk factor burden.

The effect of amyloid-β (Aβ) on cognitive impairment in patients with small subcortical infarction remains controversial, although a growing body of evidence shows a substantial overlap between Alzheimer\'s disease (AD) and subcortical ischemic vascular dementia, another form of cerebral small vessel disease (cSVD). Therefore, we investigated the relationships between Aβ positivity and the development of post-stroke cognitive impairment (PSCI) in patients with small subcortical infarction.
We prospectively recruited 37 patients aged ≥ 50 years, with first-ever small subcortical infarction, who underwent amyloid positron emission tomography, 3 months after stroke at Korea University Guro Hospital. We also enrolled CU participants matched for age and sex with stroke patients for comparison of Aβ positivity. Patients were followed up at 3 and 12 months after the stroke to assess cognitive decline. Logistic and linear mixed-effect regression analyses were performed to identify the effect of Aβ positivity on PSCI development and long-term cognitive trajectories.
At 3 months after stroke, 12/37 (32.4%) patients developed PSCI, and 11/37 (29.7%) patients had Aβ deposition. Aβ positivity (odds ratio [OR] = 72.2, p = 0.024) was predictive of PSCI development regardless of cSVD burden. Aβ positivity (β = 0.846, p = 0.014) was also associated with poor cognitive trajectory, assessed by the Clinical Dementia Rating-Sum of Box, for 1 year after stroke.
Our findings highlight that Aβ positivity is an important predictor for PSCI development and cognitive decline over 1 year. Furthermore, our results provide evidence that anti-AD medications may be a strategy for preventing cognitive decline in patients with small subcortical infarctions.

The interest in healthy cognitive aging (HCA) has increased substantially over the past decade. Researchers are interested in exploring how health can be promoted and cognitive decline mitigated when pathology is not present. Identifying the necessary strategies is crucial as the gradual accumulation of small declines can lead to negative effects on quality of life over time. However, the conceptualization of HCA is not agreed upon. In fact, authors often turn to the use of traditional pathology screeners in the context of HCA because of their clear threshold results and their wide use in the different fields. This leads to the assumption that individuals are either cognitively unhealthy and therefore may have some form of dementia or are dementia-free and cognitively healthy. We believe that this view is an overly simplistic approach to the understanding of the aging process. In this work, we explore how HCA has been defined and conceptualized within the different fields. We further discuss how time and variability are key concepts that are often missing when studying HCA and propose a definition that aims to unify the findings from the multidisciplinary research that studies HCA and simplify the translation of knowledge. Incorporating these two novel dimensions to the study of HCA has already been proposed methodologically but has yet been discussed at the conceptual level. We believe that the proposed new approach will allow the identification of individual factors that cause changes in cognitive health and will help build new cognitive health strategies and mitigate further declines.

Cognitive impairment is common after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, associations between post-hospital discharge risk factors and cognitive trajectories have not been explored.
A total of 1105 adults (mean age ± SD 64.9 ± 9.9 years, 44% women, 63% White) with severe coronavirus disease 2019 (COVID-19) were evaluated for cognitive function 1 year after hospital discharge. Scores from cognitive tests were harmonized, and clusters of cognitive impairment were defined using sequential analysis.
Three groups of cognitive trajectories were observed during the follow-up: no cognitive impairment, initial short-term cognitive impairment, and long-term cognitive impairment. Predictors of cognitive decline after COVID-19 were older age (β = -0.013, 95% CI = -0.023;-0.003), female sex (β = -0.230, 95% CI = -0.413;-0.047), previous dementia diagnosis or substantial memory complaints (β = -0.606, 95% CI = -0.877;-0.335), frailty before hospitalization (β = -0.191, 95% CI = -0.264;-0.119), higher platelet count (β = -0.101, 95% CI = -0.185;-0.018), and delirium (β = -0.483, 95% CI = -0.724;-0.244). Post-discharge predictors included hospital readmissions and frailty.
Cognitive impairment was common and the patterns of cognitive trajectories depended on sociodemographic, in-hospital, and post-hospitalization predictors.
Cognitive impairment after coronavirus disease 2019 (COVID-19) hospital discharge was associated with higher age, less education, delirium during hospitalization, a higher number of hospitalizations post discharge, and frailty before and after hospitalization. Frequent cognitive evaluations for 12-month post-COVID-19 hospitalization showed three possible cognitive trajectories: no cognitive impairment, initial short-term impairment, and long-term impairment. This study highlights the importance of frequent cognitive testing to determine patterns of COVID-19 cognitive impairment, given the high frequency of incident cognitive impairment 1 year after hospitalization.

Cognitive reserve reflects the brain\'s intrinsic adaptive capacity against the neurodegenerative effects of aging. The maintenance or enhancement of the brain\'s cognitive reserve plays a crucial role in mitigating the severity of pathologies associated with aging. A new movement, social prescribing, which focuses on prescribing lifestyle activities as a treatment for patients, is growing in popularity as a solution against aging pathologies. However, few studies have demonstrated a clear impact of lifestyle activities on individual cognitive health, outside of floor and ceiling effects. Understanding who benefits from which lifestyle factors remains unclear. Here, we investigated the potential effects of lifestyle activities on individuals\' cognitive health from more than 3,530 older adults using a stratification method and advanced analysis technique. Our stratification methods allowed us to observe a new result: older adults who had relatively average cognitive scores were not impacted by lifestyle factors. By comparison, older adults with very high or very low cognitive scores were highly impacted by lifestyle factors. These findings expand the orchid and dandelion theory to the aging field, regarding the biological sensitivity of individuals to harmful and protective environmental effects. Our discoveries demonstrate the role of individual differences in the aging process and its importance for social prescribing programs.

暂无摘要。

OBJECTIVE: The literature on Alzheimer\'s disease (AD) provides little data about long-term cognitive course trajectories. We identify global cognitive outcome trajectories and associated predictor variables that may inform clinical research and care.
METHODS: Data derived from the National Alzheimer\'s Coordinating Center (NACC) Uniform Data Set were used to examine the cognitive course of persons with possible or probable AD, a Mini-Mental State Examination (MMSE) of ≥10, and complete annual assessments for 5 years.
METHODS: Thirty-six Alzheimer\'s Disease Research Centers.
METHODS: Four hundred and fourteen persons.
METHODS: We used a hybrid approach comprising qualitative analysis of MMSE trajectory graphs that were operationalized empirically and binary logistic regression analyses to assess 19 variables\' associations with each trajectory. MMSE scores of ±3 points or greater were considered clinically meaningful.
RESULTS: Five distinct cognitive trajectories were identified: fast decliners (32.6%), slow decliners (30.7%), zigzag stable (15.9%), stable (15.9%), and improvers (4.8%). The decliner groups had three subtypes: curvilinear, zigzag, and late decline. The fast decliners were associated with female gender, lower baseline MMSE scores, a shorter illness duration, or receiving a cognitive enhancer. An early MMSE decline of ≥3 points predicted a worse outcome. A higher rate of traumatic brain injury, the absence of an ApoE ϵ4 allele, and male gender were the strongest predictors of favorable outcomes.
CONCLUSIONS: Our hybrid approach revealed five distinct cognitive trajectories and a variegated pattern within the decliners and stable/improvers that was more consistent with real-world clinical experience than prior statistically modeled studies. Future investigations need to determine the consistency of the distribution of these categories across settings.

OBJECTIVE: Cognitive and mood dysfunction are major contributors to post-stroke disability. The longer-term trajectories of mood and cognition post-stroke remain unclear, as do which cognitive domains decline, improve, or remain stable after stroke, and in which patients. We aimed to characterize the cognitive trajectories of mild ischemic stroke survivors over one year compared to stroke-free controls, and to investigate whether symptoms of anxiety and depression were associated with cognitive function.
METHODS: All participants were tested with a neuropsychological test battery at 3-months and 12-months post-stroke, assessing attention/processing speed, memory, visuospatial function, executive function, and language. Anxiety and depression symptomatology were also assessed at both timepoints.
RESULTS: Stroke participants (N=126, mean age 68.44 years ±11.83, 87 males, median [Q1, Q3] admission NIHSS=2 [1, 4]) performed worse on cognitive tests and endorsed significantly higher depression and anxiety symptomatology than controls (N=40, mean age=68.82 years ±6.33, 25 males) at both timepoints. Mood scores were not correlated with cognitive performance. Stroke participants\' scores trended higher across cognitive domains from 3- to 12-months but statistically significant improvement was only observed on executive function tasks.
CONCLUSIONS: Stroke participants performed significantly worse than controls on all cognitive domains following mild ischemic stroke. Stroke participants only exhibited statistically significant improvement on executive function tasks between 3- and 12- months. Whilst anxiety and depression symptoms were higher in stroke participants, this was not correlated with cognitive performance. Further studies are needed to understand factors underlying cognitive recovery and decline after stroke.