Association between Blood Pressure, Blood Pressure Variability, and Post-Stroke Cognitive Impairment

Knowledge domain and emerging trends in post-stroke cognitive impairment: a bibliometric analysis

Background

Cognitive impairment is an important cause of disability and death among the elderly. One of the most important risk factors is stroke. Post-stroke cognitive impairment (PSCI) not only diminishes the quality of life for patients but also increases the burden on families and society. But PSCI can be mitigated through early intervention. Cerebral small vessel disease (CSVD) is one of the significant causes of stroke and has garnered considerable attention in PSCI. Therefore, this study aims to identify research priorities and trends in PSCI through bibliometric analysis, and further explore the role played by CSVD in PSCI.

Methods

In this study, we performed a systematic search in the Science Citation Index Expanded (SCI-E) of the Web of Science Core Collection (WoSCC). VOSviewer, CiteSpace and Origin were mainly used to visualize the research focus and trend in PSCI. In addition, we screened the retrieved literature again, and performed keyword analysis on the studies related to CSVD.

Results

A total of 1,943 publications were retrieved in the field of PSCI in this study, with consistent upward trend in annual publications in recent years. Pendlebury was an important leader in PSCI research. Capital Medical University was in the leading position judging from the number of publications. China had the highest number of publications in this field. The journal Stroke had the strongest international influence in this field. Keywords such as "functional connectivity," "tool," "systematic review," and "meta-analysis" have been revealed to have momentous impact on PSCI in recent years. In the further analysis of PSCI and CSVD, "hypertension," "white matter hyperintensities (WMH)," "cerebral microbleeds (CMBs)," and "cerebral amyloid angiopathy (CAA)" received extensive attention.

Conclusion

The study of PSCI is still in the development stage. This study systematically summarizes the progress and development trend in the field of PSCI, and further explores the relationship between CSVD and PSCI through hypertension and magnetic resonance imaging markers. This study is of great significance for researchers to quickly understand the development of PSCI, but also helps them understand future directions, and provides important insights for the prevention and treatment of PSCI.

Association Between Enlarged Perivascular Spaces and Early Acute Ischemic Stroke with Cognitive Impairment: A Cross-Sectional Study

BACKGROUND

Enlarged perivascular spaces (EPVSs) are commonly detected via magnetic resonance imaging. It is unclear whether EPVSs are associated with cognitive impairment within one month after an acute ischemic stroke (AIS) (i.e., early AIS with cognitive impairment (EAIS-CI)). This study explored the severity and location of EPVSs and their association with EAIS-CI severity and provides clinicians with early warning indicators before the onset of typical clinical symptoms in the Chinese population.

METHODS

The clinical data of 208 patients (176 AIS patients and 32 controls) were prospectively analyzed using the Montreal Cognitive Assessment Beijing version (MoCA-BJ) score as the primary group criterion and the Mini-Mental State Examination (MMSE) score as a supplementary criterion. When EPVS I as the main EPVS type detected by imaging, the basal ganglia (BG) is the area most severely affected. Statistical analysis was conducted on the relevant clinical data.

RESULTS

AIS patients were grouped based on MoCA-BJ scores. Age (p < 0.01), education level (p = 0.02), EPVS I as the main EPVS type (p < 0.01), the number of right-sided BG-EPVSs (p = 0.04), white matter hyperintensities (WMHs) (Fazekas scores: p = 0.02), brain atrophy (global cortical atrophy scores: p < 0.01, Koedam posterior atrophy visual scale scores: p = 0.01, medial temporal lobe atrophy scores: p < 0.01) and AIS lesion volume (p = 0.01) were significantly greater in the EAIS-CI group than in the EAIS without cognitive impairment group. The cognitive domains of attention (p = 0.04) and orientation (p < 0.01) were more closely associated with EPVS I as the main EPVS type. However, multivariate regression analysis did not identify EPVS I as the main EPVS type as the main risk factor for EAIS-CI (p = 0.098). Grouping by MMSE scores revealed that EPVS I as the main EPVS type was linked to low education level (p < 0.01) and was significantly associated with EAIS in individuals with cognitive dementia (p < 0.01).

CONCLUSIONS

As a result of multiple factors, EAIS-CI is significantly associated with a low education level, BG-EPVS, WMHs, and worsening brain atrophy severity. Imaging markers, such as the severity of BG-EPVS, can assist in the early diagnosis and assessment of EAIS-CI.

CLINICAL TRIAL REGISTRATION

The study was registered with the China Clinical Trial Registry (https://www.chictr.org.cn/), registration number: ChiCTR2000038819.

Risk factors for post-cerebral infarction cognitive dysfunction in older adults: a retrospective study

OBJECTIVE

Our research aims to elucidate the significance of type 2 diabetes (T2D) and provides an insight into a novel risk model for post-cerebral infarction cognitive dysfunction (PCICD).

METHODS

Our study recruited inpatients hospitalized with cerebral infarction in Xijing hospital, who underwent cognitive assessment of Mini-Mental State Examination (MMSE) from January 2010 to December 2021. Cognitive status was dichotomized into normal cognition and cognitive impairment. Collected data referred to Demographic Features, Clinical Diseases, scale tests, fluid biomarkers involving inflammation, coagulation function, hepatorenal function, lipid and glycemic management.

RESULTS

In our pooled dataset from 924 eligible patients, we included 353 in the final analysis (age range 65-91; 30.31% female). Multivariate logistic regression analysis was performed to show that Rural Areas (OR = 1.976, 95%CI = 1.111-3.515, P = 0.020), T2D (OR = 2.125, 95%CI = 1.267-3.563, P = 0.004), Direct Bilirubin (OR = 0.388, 95%CI = 0.196-0.769, P = 0.007), Severity of Dependence in terms of Barthel Index (OR = 1.708, 95%CI = 1.193-2.445, P = 0.003) that were independently associated with PCICD, constituting a model with optimal predictive efficiency.

CONCLUSION

To the best of our knowledge, this study provides a practicable map of strategical predictors to robustly identify cognitive dysfunction at risk of post-cerebral infarction for clinicians in a broad sense. Of note, our findings support that the decline in serum direct bilirubin (DBil) concentration is linked to protecting cognitive function.

Predictors of Cognitive Functions After Stroke Assessed Using the Wechsler Adult Intelligence Scale: A Retrospective Study

Background

The mechanism(s) of cognitive impairment remains complex, making it difficult to confirm the factors influencing poststroke cognitive impairment (PSCI).

Objective

This study quantitatively investigated the degree of influence and interactions of clinical indicators of PSCI.

Methods

Information from 270 patients with PSCI and their Wechsler Adult Intelligence Scale (WAIS-RC) scores, totaling 18 indicators, were retrospectively collected. Correlations between the indicators and WAIS scores were calculated. Multiple linear regression model(MLR), genetic algorithm modified Back-Propagation neural network(GA-BP), logistic regression model (LR), XGBoost model (XGB), and structural equation model were used to analyze the degree of influence of factors on the WAIS and their mediating effects.

Results

Seven indicators were significantly correlated with the WAIS scores: education, lesion side, aphasia, frontal lobe, temporal lobe, diffuse lesions, and disease course. The MLR showed significant effect of education, lesion side, aphasia, diffuse lesions, and frontal lobe on the WAIS. The GA-BP included five factors: education, aphasia, frontal lobe, temporal lobe, and diffuse lesions. LR predicted that the lesion side contributed more to mild cognitive impairment, while education, lesion side, aphasia, and course of the disease contributed more to severe cognitive impairment. XGB showed that education, side of the lesion, aphasia, and diffuse lesions contributed the most to PSCI. Aphasia plays a significant mediating role in patients with severe PSCI.

Conclusions

Education, lesion side, aphasia, frontal lobe, and diffuse lesions significantly affected PSCI. Aphasia is a mediating variable between clinical information and the WAIS in patients with severe PSCI.

Association Between the Serum Iron and Acute Cognitive Impairment After Stroke: A Cross-Sectional Study

BACKGROUND

Complications such as cognitive impairment are common in stroke victims. The goal of this study was to see if there was a link between blood iron levels and post-stroke cognitive impairment (PSCI) within 2 weeks after stroke.

METHODS

A total of 313 patients with ischemic stroke were recruited and separated into two groups: PSCI (n = 202) and non-PSCI (n = 111). The Mini-mental state examination scale was used to evaluate the cognitive status within 2 weeks after stroke (acute phase). The serum iron levels were divided into 4 layers: Q1 ≤ 11.7 μmol/L, Q2 11.8-15.1 μmol/, Q3 15.2-19.3 μmol/L, Q4 ≥ 19.4 μmol/L, respectively. The connection between serum iron and PSCI was then investigated further using binary logistic regression, which was adjusted for confounders.

RESULTS

The difference in serum iron levels between the PSCI and non-PSCI group was initially conducted by the Mann-Whitney test, and a significant difference was found (14.5 (11.0-17.8) vs. 16.9 (13.7-21.8), p < .001), with no confounders being adjusted. After adjusting for confounding factors, the binary regression analysis showed that the Q4 layer showed the lowest risk of PSCI, with the Q1 layer being the reference. (odds ratio (OR) = 0.297, 95% confidence interval (CI) = 0.136-0.649, p = 0.002).

CONCLUSION

A decreased risk of early-onset PSCI was linked to high serum iron levels. Low serum iron levels were found to be a risk factor for acute cognitive impairment following stroke, which could help physicians identify and take intervention measures early to reduce the risk of cognitive impairment after stroke.