Risk factors for cognitive impairment and dementia after stroke: a systematic review and meta-analysis

Impact of depression and cardiovascular risk factors on cognitive impairment in patients with atrial fibrillation: A Systematic review and meta-analysis

BACKGROUND

Atrial fibrillation (AF) is a common cardiac arrhythmia associated with significant cardiovascular morbidity and mortality, as well as cognitive impairment (CI). The interplay between AF and CI is complex, involving various pathophysiological changes and numerous risk factors. Among them, depression has emerged as a significant contributor to both AF and CI, further complicating the relationship between these conditions.

OBJECTIVES

This systematic review and meta-analysis aimed to investigate the influence of depression on the development of cognitive impairment in AF patients and assess the predictive value of the CHA2DS2-VASc score for CI risk.

METHODS

We searched PubMed, Scopus, and Web of Science for relevant studies without language or date restrictions. Ten studies, comprising 1,605,577 participants, were included. A random-effects model was used for meta-analysis, and heterogeneity was assessed using I2 statistics. Funnel plots and Egger's test evaluated publication bias.

RESULTS

Depression significantly increased the risk of CI in AF patients (OR: 2.23, 95 % CI: 1.54-3.21, p < 0.01; I2=99 %). This association persisted in studies excluding baseline CI (OR: 1.95, 95 % CI: 1.33-2.85, p < 0.01; I2=88 %). Subgroup analysis confirmed these results for both prospective (OR: 1.78, 95 % CI: 0.92-3.44, p = 0.02; I2=65 %) and retrospective studies (OR: 2.63, 95 % CI: 1.75-3.93, p < 0.01; I2=100 %). Analysis of CHA2DS2-VASc risk factors showed associations with CI, particularly cerebrovascular disease (OR: 1.86, 95 % CI: 1.61-2.16).

CONCLUSIONS

Our findings support the association between depression and cognitive impairment in AF patients, demonstrating the importance of addressing mental health in cardiovascular care. Future research is necessary for a comprehensive understanding of this association.

Socioeconomic Disparities in Rate of Poststroke Dementia: A Nationwide Cohort Study

BACKGROUND

Socioeconomic disparities exist in acute stroke care as well as in long-term stroke outcomes. We aimed to investigate whether socioeconomic status was associated with the rate of poststroke dementia (PSD).

METHODS

This was a nationwide register-based cohort study including all patients with incident ischemic or hemorrhagic stroke in Denmark from 2010 to 2020. Socioeconomic status was defined by prestroke income, education, and employment. PSD was defined as a dementia diagnosis in the National Patient Registry or a dispensed prescription of dementia medication after a stroke. PSD incidence rates were compared between socioeconomic status groups using Poisson regression.

RESULTS

A total of 98 489 patients with incident stroke without a diagnosis of prestroke dementia were identified and followed for a median (IQR) of 4.2 (IQR, 2.1-7.3) years. Median age was 72 (62-80) years, 56% were male, 5.1% were immigrants, and 86% had ischemic stroke. Dementia was diagnosed in 5680 patients at a median of 2.4 (IQR, 0.9-4.8) years after stroke (incidence rate=12.1/1000 person-years). After adjusting for age, sex, and immigrant status, PSD rates were 1.24 (1.15-1.34) times higher for low income compared with high income, 1.11 (1.03-1.20) times higher for low education compared with high education, and 1.57 (1.38-1.77) times higher for patients without employment compared with patients with employment. Further adjustments for stroke severity, cohabitation, and comorbidities showed similar results. Stratified analyses showed that the socioeconomic disparities in PSD rates were more pronounced among women, immigrants, and patients <70 years of age.

CONCLUSIONS

Low socioeconomic status measured by prestroke income, education, and employment status was associated with higher rates of PSD. These socioeconomic disparities extended beyond what could be explained by common PSD risk factors.

Machine learning-based predictive model for post-stroke dementia

BACKGROUND

Post-stroke dementia (PSD), a common complication, diminishes rehabilitation efficacy and affects disease prognosis in stroke patients. Many factors may be related to PSD, including demographic, comorbidities, and examination characteristics. However, most existing methods are qualitative evaluations of independent factors, which ignore the interaction amongst various factors. Therefore, the purpose of this study is to explore the applicability of machine learning (ML) methods for predicting PSD.

METHODS

9 acceptable features were screened out by the Spearman correlation analysis and Boruta algorithm. We developed and evaluated 8 ML models: logistic regression, elastic net, k-nearest neighbors, decision tree, extreme gradient boosting, support vector machine, random forest, and multilayer perceptron.

RESULTS

A total of 539 stroke patients were included in this study. Among the 8 models used to predict PSD, extreme gradient boosting and random forest showed the highest area under the curve (AUC) of the receiver operating characteristic curve (ROC), with values of 0.7287 and 0.7285, respectively. The most important features for predicting PSD included age, high sensitivity C-reactive protein, stroke side and location, and the occurrence of cerebral hemorrhage.

CONCLUSION

Our findings suggest that ML models, especially extreme gradient boosting, can best predict the risk of PSD.

Innovations and challenges in predicting cognitive trajectories after stroke

This scientific commentary refers to 'Deep learning disconnectomes to accelerate and improve long-term predictions for post-stroke symptoms', by Matsulevits et al. (https://doi.org/10.1093/braincomms/fcae338).

Predicting post-stroke cognitive impairment using electronic health record data

BACKGROUND

Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification.

AIMS

To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records.

METHODS

Cohort study that included primary care patients from two academic medical centers. Patients were aged 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003 and 2016 (development/internal validation cohort) or 2010 and 2022 (external validation cohort). Predictors of PSCI were ascertained from the electronic health record. The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included.

RESULTS

The analysis included 332 incident diagnoses of PSCI in the development cohort (n = 3741), and 161 and 128 incident diagnoses in the internal (n = 1925) and external (n = 2237) validation cohorts, respectively. The C-statistic for predicting PSCI was 0.731 (95% confidence interval (CI): 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-23 points) risk groups. The hazard ratios (HRs) for incident PSCI were significantly different by risk categories in internal (high, HR: 6.2, 95% CI: 4.1-9.3; Intermediate, HR: 2.7, 95% CI: 1.8-4.1) and external (high, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR: 2.8, 95% CI: 1.9-4.3) validation cohorts.

CONCLUSION

Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts.

DATA ACCESS STATEMENT

Mass General Brigham data contain protected health information and cannot be shared publicly. The data processing scripts used to perform analyses will be made available to interested researchers upon reasonable request to the corresponding author.

Microglial activation and polarization in type 2 diabetes-related cognitive impairment: A focused review of pathogenesis

Microglia, as immune cells in the central nervous system, are closely related to cognitive impairment associated with type 2 diabetes (T2D). Preliminary explorations have investigated the relationship between T2D-related cognitive impairment and the activation and polarization of microglia. This review summarizes the potential mechanisms of microglial activation and polarization in the context of T2D. It discusses central inflammatory responses, neuronal apoptosis, amyloid-β deposition, and abnormal phosphorylation of Tau protein mediated by microglial activation and polarization, exploring the connections between microglial activation and polarization and T2D-related cognitive impairment from multiple perspectives. Additionally, this review provides references for future treatment targeting microglia in T2D-related cognitive impairment and for clinical translation.

Atrial fibrillation, hypertension, and the cerebral vasodilatory reserve

Schematic representation for the cascade model of atrial fibrillation, hypertension, the cerebral vasodilatory reserve, and cognitive decline.

Validating the OCS-Plus against a clinical standard: A brief report

This research aimed to determine the sensitivity and clinical validity of the OCS-Plus, a stroke-specific tablet-based cognitive screening tool, in comparison with the MoCA, a routinely used screening tool, after stroke. Eighty-six patients were recruited from Oxfordshire stroke wards over a 22-month period and completed both screens. Overall, we found that the OCS-Plus has good convergent validity and excellent sensitivity when compared with the MoCA. The OCS-Plus is therefore of potential benefit to those seeking a sensitive screening tool.

Correlation of cerebral small vessel disease burden with outcome after lower extremity amputation

AIMS

This study assessed whether changes associated with cerebral small vessel disease (CSVD) evaluated from head computed tomography (CT) images captured for non-related clinical purposes predict overall survival (OS), leg salvage (LS), and amputation-free survival (AFS) after lower extremity amputation (LEA).

METHODS

We retrospectively included a cohort of 240 patients who had undergone a lower extremity amputation in Tampere University Hospital between the years 2007 and 2020 and had a head CT scan (within one year before amputation). A neuroradiologist graded the white matter lesions (WMLs) and reported infarcts, and the latter's effects on OS, LS, and AFS were evaluated.

RESULTS

Altogether, 162 (67.5 %) and 91 (38.1 %) patients had WMLs and infarcts, respectively. Mild/moderate (HR 1.985, CI 95 % 1.317-2.992) and severe (HR 2.259, CI 95 % 1.501-3.399) WMLs and infarcts (HR 1.413, CI 95 % 1.029-1.940) were associated with inferior OS. After a minor amputation, mild/moderate (HR 2.012, CI 95 % 1.054-3.843) and severe (HR 3.879, CI 95 % 2.096-7.180) WMLs were similarly associated with inferior AFS.

CONCLUSIONS

Overall, WML and infarcts detected on head CT scans were associated with impaired OS after LEA and AFS after minor LEA. Evaluation of CSVD could provide useful prognostic information for clinicians.

Characterization and individual-level prediction of cognitive state in the first year after 'mild' stroke

BACKGROUND

Mild stroke affects more than half the stroke population, yet there is limited evidence characterizing cognition over time in this population, especially with predictive approaches applicable at the individual-level. We aimed to identify patterns of recovery and the best combination of demographic, clinical, and lifestyle factors predicting individual-level cognitive state at 3- and 12-months after mild stroke.

METHODS

In this prospective cohort study, the Montreal Cognitive Assessment (MoCA) was administered at 3-7 days, 3- and 12-months post-stroke. Raw changes in MoCA and impairment rates (defined as MoCA<24 points) were compared between assessment time-points. Trajectory clusters were identified using variations of ≥1 point in MoCA scores. To further compare clusters, additional assessments administered at 3- and 12-months were included. Gamma and Quantile mixed-effects regression were used to predict individual MoCA scores over time, using baseline clinical and demographic variables. Model predictions were fitted for each stroke survivor and evaluated using model cross-validation to identify the overall best predictors of cognitive recovery.

RESULTS

Participants' (n = 119) MoCA scores improved from baseline to 3-months (p<0.001); and decreased from 3- to 12-months post-stroke (p = 0.010). Cognitive impairment rates decreased significantly from baseline to 3-months (p<0.001), but not between 3- and 12-months (p = 0.168). Nine distinct trajectory clusters were identified. Clinical characteristics between clusters at each time-point varied in cognitive outcomes but not in clinical and/or activity participation outcomes. Cognitive performance at 3- and 12-months was best predicted by younger age, higher physical activity levels, and left-hemisphere lesion side.

CONCLUSION

More than half of mild-stroke survivors are at risk of cognitive decline one year after stroke, even when preceded by a significantly improving pattern in the first 3-months of recovery. Physical activity was the only modifiable factor independently associated with cognitive recovery. Individual-level prediction methods may inform the timing and personalized application of future interventions to maximize cognitive recovery post-stroke.

Genetic Determinants of Vascular Dementia

Vascular dementia (VaD) is a prevalent form of cognitive impairment with underlying vascular etiology. In this review, we examine recent genetic advancements in our understanding of VaD, encompassing a range of methodologies including genome-wide association studies, polygenic risk scores, heritability estimates, and family studies for monogenic disorders revealing the complex and heterogeneous nature of the disease. We report well known genetic associations and highlight potential pathways and mechanisms implicated in VaD and its pathological risk factors, including stroke, cerebral small vessel disease, and cerebral amyloid angiopathy. Moreover, we discuss important modifiable risk factors such as hypertension, diabetes, and dyslipidemia, emphasizing the importance of a multifactorial approach in prevention, treatment, and understanding the genetic basis of VaD. Last, we outline several areas of scientific advancements to improve clinical care, highlighting that large-scale collaborative efforts, together with an integromics approach can enhance the robustness of genetic discoveries. Indeed, understanding the genetics of VaD and its pathophysiological risk factors hold the potential to redefine VaD on the basis of molecular mechanisms and to generate novel diagnostic, prognostic, and therapeutic tools.

Dementia after Ischemic Stroke, from Molecular Biomarkers to Therapeutic Options

Ischemic stroke is a leading cause of disability worldwide. While much of post-stroke recovery is focused on physical rehabilitation, post-stroke dementia (PSD) is also a significant contributor to poor functional outcomes. Predictive tools to identify stroke survivors at risk for the development of PSD are limited to brief screening cognitive tests. Emerging biochemical, genetic, and neuroimaging biomarkers are being investigated in an effort to unveil better indicators of PSD. Additionally, acetylcholinesterase inhibitors, NMDA receptor antagonists, dopamine receptor agonists, antidepressants, and cognitive rehabilitation are current therapeutic options for PSD. Focusing on the chronic sequelae of stroke that impair neuroplasticity highlights the need for continued investigative trials to better assess functional outcomes in treatments targeted for PSD.

White matter integrity and functional connectivity of the default mode network in acute stroke are associated with cognitive outcome three months post-stroke

BACKGROUND

Knowledge about factors that are associated with post-stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain's default-mode network (DMN) in acute stroke patients with cognitive outcome three months post-stroke.

METHODS

Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24-72 h after symptom onset, and participated in a neuropsychological assessment three months post-stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome.

RESULTS

The study cohort comprised 34 patients (mean age: 64 ± 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months post-stroke to a median NIHSS = 1 (p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post-stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed (p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility (p = .033).

CONCLUSIONS

White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post-stroke cognitive outcome beyond demographic, clinical, and macrostructural information.

Peripheral immunity is associated with cognitive impairment after acute minor ischemic stroke and transient ischemic attack

Immunoinflammation is associated with the development of post-stroke cognitive impairment (PSCI), however, peripheral immunity has not been fully explored. We aimed to investigate the association between PSCI and peripheral immune indicators, including neutrophil, lymphocyte, and mononuclear percentages and counts; the systemic immune inflammation index; platelet-to-lymphocyte ratio; neutrophil-to-lymphocyte ratio (NLR); and lymphocyte-to-monocyte ratio. A total of 224 patients with acute minor ischemic stroke or transient ischemic attack with 6-12 months of follow-up were included. PSCI was defined as a Montreal Cognitive Assessment score < 22 during the follow-up period. We performed logistic regression, subgroup analyses based on age and sex, and further established predictive models. We found that increased innate immunity indicators (neutrophils, neutrophil percentage) increased the risk of PSCI, whereas increased adaptive immunity indicator (lymphocytes) were protective against PSCI, especially in patients aged 50-65 years. Neutrophil percentage and NLR improved the predictive efficacy of the models that included demographic, clinical, and imaging information, with the area under the curve increased from 0.765 to 0.804 and 0.803 (P = 0.042 and 0.049, respectively). We conducted a comprehensive analysis of peripheral immunity in PSCI, providing a novel perspective on the early detection, etiology, and treatment of PSCI.

Therapeutic effectiveness of Donepezil hydrochloride in combination with butylphthalide for post-stroke cognitive impairment

OBJECTIVE

To study the therapeutic effectiveness of donepezil hydrochloride (DPZ) in combination with butylphthalide (BP) for the treatment of post-stroke cognitive impairment (PSCI).

METHODS

In this retrospective study, the clinical data of 125 PSCI patients treated at the First Affiliated Hospital of Harbin Medical University from December 2019 to December 2023 were collected and analyzed. The patients were grouped into a joint group (n=75, receiving DPZ + BP) and a control group (n=50, receiving DPZ alone) according to their treatment regimen. Inter-group comparisons were then carried out from the perspectives of therapeutic effectiveness, safety (constipation, abdominal distension and pain, and gastrointestinal reactions), cognitive function (Montreal Cognitive Assessment Scale [MoCA], Chinese Stroke Scale [CSS]), Activities of Daily Living Scale (ADL), and serum biochemical indexes (neuron-specific enolase [NSE], high-sensitivity C-reactive protein [hs-CRP], nitric oxide [NO], and malondialdehyde [MDA]). In addition, a univariate analysis was carried out to identify factors affecting therapeutic effectiveness in PSCI patients.

RESULTS

The joint group showed significantly better therapeutic effectiveness compared to the control group (P<0.05). There was a significant correlation between the type of stroke, treatment method, and therapeutic effectiveness in PSCI patients (P<0.05). There was no significant difference in the total incidence of adverse reactions (P>0.05). After the treatment, compared to the control group, the joint group demonstrated significant improvements in MoCA and ADL scores (all P<0.05) and reductions in CSS scores and levels of NSE, hs-CRP, NO, and MDA (all P<0.05).

CONCLUSIONS

DPZ in combination with BP is highly effective for the treatment of PSCI. It positively affects cognitive function and ADL, alleviates neurological deficits, and reduces abnormal serum biochemical indices without increasing the risk of adverse reaction.

Impact of Helicobacter pylori and metabolic syndrome on mast cell activation-related pathophysiology and neurodegeneration

Both Helicobacter pylori (H. pylori) infection and metabolic syndrome (MetS) are highly prevalent worldwide. The emergence of relevant research suggesting a pathogenic linkage between H. pylori infection and MetS-related cardio-cerebrovascular diseases and neurodegenerative disorders, particularly through mechanisms involving brain pericyte deficiency, hyperhomocysteinemia, hyperfibrinogenemia, elevated lipoprotein-a, galectin-3 overexpression, atrial fibrillation, and gut dysbiosis, has raised stimulating questions regarding their pathophysiology and its translational implications for clinicians. An additional stimulating aspect refers to H. pylori and MetS-related activation of innate immune cells, mast cells (MC), which is an important, often early, event in systemic inflammatory pathologies and related brain disorders. Synoptically, MC degranulation may play a role in the pathogenesis of H. pylori and MetS-related obesity, adipokine effects, dyslipidemia, diabetes mellitus, insulin resistance, arterial hypertension, vascular dysfunction and arterial stiffness, an early indicator of atherosclerosis associated with cardio-cerebrovascular and neurodegenerative disorders. Meningeal MC can be activated by triggers including stress and toxins resulting in vascular changes and neurodegeneration. Likewise, H.pylori and MetS-related MC activation is linked with: (a) vasculitis and thromboembolic events that increase the risk of cardio-cerebrovascular and neurodegenerative disorders, and (b) gut dysbiosis-associated neurodegeneration, whereas modulation of gut microbiota and MC activation may promote neuroprotection. This narrative review investigates the intricate relationship between H. pylori infection, MetS, MC activation, and their collective impact on pathophysiological processes linked to neurodegeneration. Through a comprehensive search of current literature, we elucidate the mechanisms through which H. pylori and MetS contribute to MC activation, subsequently triggering cascades of inflammatory responses. This highlights the role of MC as key mediators in the pathogenesis of cardio-cerebrovascular and neurodegenerative disorders, emphasizing their involvement in neuroinflammation, vascular dysfunction and, ultimately, neuronal damage. Although further research is warranted, we provide a novel perspective on the pathophysiology and management of brain disorders by exploring potential therapeutic strategies targeting H. pylori eradication, MetS management, and modulation of MC to mitigate neurodegeneration risk while promoting neuroprotection.

The Role of Helicobacter pylori and Metabolic Syndrome-Related Mast Cell Activation Pathologies and Their Potential Impact on Pregnancy and Neonatal Outcomes

Helicobacter pylori infection, a significant global burden beyond the gastrointestinal tract, has long been implicated in various systemic pathologies. Rising evidence suggests that the bacterium's intricate relationship with the immune system and its potential to induce chronic inflammation impact diverse pathophysiological processes in pregnant women that may in turn affect the incidence of several adverse pregnancy and neonate outcomes. Helicobacter pylori infection, which has been linked to metabolic syndrome and other disorders by provoking pericyte dysfunction, hyperhomocysteinemia, galectin-3, atrial fibrillation, gut dysbiosis, and mast cell activation pathologies, may also contribute to adverse pregnancy and neonatal outcomes. Together with increasing our biological understanding of the individual and collective involvement of Helicobacter pylori infection-related metabolic syndrome and concurrent activation of mast cells in maternal, fetus, and neonatal health outcomes, the present narrative review may foster related research endeavors to offer novel therapeutic approaches and informed clinical practice interventions to mitigate relevant risks of this critical topic among pregnant women and their offspring.

Association between socioeconomic status and post-stroke depression in middle-aged and older adults: results from the China health and retirement longitudinal study

INTRODUCTION

Post-stroke depression (PSD) is a common neuropsychiatric complication that affects approximately one-third of stroke patients. The treatment and prognosis of this disease are poor. Socioeconomic status (SES) is closely related to health outcomes; however, only a few previous studies have focused on the association between SES and PSD. Given the substantial population of stroke patients in China, it is crucial to examine the potential risk factors associated with PSD. Conducting studies on this population and investigating the influence of economic conditions can provide valuable guiding theoretical insights into PSD prevention and management.

METHODS

We used data from the 2018 China Health and Retirement Longitudinal Study and selected appropriate samples for analysis. Depression was estimated using the Center of Epidemiologic Studies Depression Scale-10, a validated tool for assessing depression in the general population. Multiple logistic regression analysis was employed to assess the association between SES and PSD and to evaluate any urban-rural differences.

RESULTS

Of the 749 respondents, 370 (49.4%) had depression. Stroke patients with a middle school education demonstrated a greater risk of developing depression than those with a primary school education or below after adjusting for all control variables (odds ratio (OR) = 1.60, 95% confidence interval (CI): 1.03-2.51, P = 0.036). However, stroke patients with a high school education or above had a lower risk of developing depression than those with a primary school education or below (OR = 0.50, 95% CI: 0.28-0.88, P = 0.016). In rural areas, stroke patients with a high school or above education level had lower rates of depression than those with a primary school education or below (OR = 0.44, 95% CI: 0.21-0.91, P = 0.027). This difference was not significant in urban areas.

CONCLUSIONS

SES significantly influences the occurrence of PSD, which is reflected by education attainment and annual household expenditures. Education attainment was an independent influence on PSD, with a more pronounced effect in rural versus urban areas. We hope to reduce the prevalence of PSD and enhance the comprehensive management of this disease by modifying the influencing factors. Sex, self-reported health status, activities of daily living, night-time sleep duration, and life satisfaction also influenced the occurrence of PSD.