A 2-year prospective follow-up study of temporal changes associated with post-stroke cognitive impairment

Prediction Models for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis

BACKGROUND

Stroke is one of the most serious illnesses worldwide and is the primary cause of acquired disability among adults. Post-stroke cognitive impairment (PSCI) is a complication of stroke that significantly impacts patients' daily activities and social functions. Therefore, developing a risk prediction model for PSCI is essential for identifying and preventing disease progression.

OBJECTIVES

This study systematically reviewed and analyzed PSCI prediction models, identifying the associated risk factors.

METHODS

We systematically retrieved literature from PubMed, Cochrane Library, Embase, and other sources. Two researchers independently extracted the literature and assessed the risk of bias using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist and The Prediction Model Risk of Bias Assessment Tool (PROBAST).

RESULTS

A total of 20 articles describe the PSCI prediction model, with an incidence rate ranging from 8% to 75%. The area under the receiver operating characteristic curve (AUC) value for the development models ranged from 0.66 to 0.969, while the validation models ranged from 0.763 to 0.893. Age, diabetes, hypersensitive C-reactive protein (hs-CRP), hypertension, and homocysteine (hcy) were identified as the strongest predictors.

CONCLUSION

In this systematic review, several PSCI prediction models demonstrate promising prediction performance, although they often lack external validation and exhibit high heterogeneity in some predictive factors. Therefore, we recommend that medical practitioners utilize a comprehensive set of predictive factors to screen for high-risk PSCI patients. Furthermore, future research should prioritize refining and validating existing models by incorporating novel variables and methodologies.

Prevalence and Risk Factors of Poststroke Cognitive Impairment: A Systematic Review and Meta-Analysis

BACKGROUND

Stroke is a common disease that poses a significant threat to human health. Approximately one-third of stroke patients experience poststroke cognitive impairment (PSCI), which severely impacts their quality of life and survival time. Although the prevalence and risk factors for PSCI have been widely reported, these results have not been synthesized.

OBJECTIVES

This systematic review was conducted to explore the prevalence and risk factors of PSCI.

METHODS

PubMed, EMBASE, Web of Science, and Cochrane Library were comprehensively searched for studies exploring the prevalence and risk factors of PSCI from inception to July 5, 2022.

RESULTS

A total of 49 articles were included for meta-analysis. It was found that the combined prevalence of PSCI was 39%-47%. Risk factors for PSCI include female gender, age, education level less than 7 years, atrial fibrillation, diabetes, smoking, drinking, hypertension, coronary artery disease, carotid artery plaque, admission NIHSS score ≥ 5, unemployment, and homocysteine.

CONCLUSIONS

This systematic review has revealed a combined prevalence of PSCI is ranging from 39% to 47% and identified several risk factors for PSCI. These findings indicate a high incidence of the condition and underscore the need for increased public awareness. Future investigations should prioritize the identification of PSCI risk factors, providing a theoretical basis for nursing professionals to effectively manage and treat PSCI patients.

Factors Influencing Poststroke Cognitive Dysfunction: Cross-Sectional Analysis

BACKGROUND

Poststroke cognitive impairment (PSCI) is a common and debilitating complication that affects stroke survivors, impacting memory, attention, and executive function. Despite its prevalence, the factors contributing to PSCI remain unclear, with limited insights into how demographic and clinical variables influence cognitive outcomes.

OBJECTIVE

This study investigates the incidence of cognitive impairment in patients with stroke and examines key demographic and clinical factors, such as age, gender, and education level, which contribute to cognitive decline. The aim is to provide a deeper understanding of PSCI to inform early intervention strategies for improving patient outcomes.

METHODS

A cross-sectional study was conducted on 305 patients with ischemic stroke admitted to Zhongda Hospital, Southeast University, from January 2019 to September 2022. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) within 72 hours of hospital admission. Demographic information, including age, gender, and education level, were collected. Statistical analyses were performed using chi-square tests, independent t tests, and multivariate regression to assess the relationship between cognitive function and key variables. Pearson correlation analysis explored associations among age, education, and MMSE scores.

RESULTS

Among the 305 patients with stroke, 16.7% (n=51) were diagnosed with cognitive impairment based on MMSE scores. The prevalence of cognitive impairment was slightly higher in males (17.6%, n=159) than females (15.8%, n=146), but this difference was not statistically significant. A strong negative correlation was found between MMSE scores and age (r=-0.32; P<.01), indicating that older patients had lower cognitive function. Education level showed a positive correlation with MMSE scores (r=0.41; P<.01), with patients with higher educational attainment demonstrating better cognitive outcomes. Cognitive function showed a marked decline in patients older than 60 years, particularly in domains such as memory, attention, and language skills.

CONCLUSIONS

This study confirms that age and education are significant factors in determining cognitive outcomes after stroke. The results align with existing literature showing that cognitive function declines with age, while higher educational attainment serves as a protective factor. The findings suggest that individuals with greater cognitive reserve, often linked to higher education, are better equipped to cope with the impact of brain injury. However, the study's reliance on MMSE may have limited its ability to detect domain-specific impairments. Future studies should consider using more sensitive cognitive tools, such as the Montreal Cognitive Assessment (MoCA), to provide a more comprehensive evaluation of PSCI. Cognitive impairment is prevalent among stroke survivors, with age and education level being key factors influencing outcomes. These findings underscore the importance of early detection and targeted interventions to mitigate cognitive decline. Further research with larger samples and more sensitive cognitive assessments is needed to fully understand PSCI and improve rehabilitation strategies for patients with stroke.

The relationship between social and psychological factors with cognitive impairment after stroke: a prospective study

Objectives

To investigate the association between social and psychological factors and the risk of cognitive impairment following acute ischemic stroke.

Materials and methods

A prospective study was conducted at Shanghai Tenth People's Hospital from June 2021 to July 2022. The study focused on social and psychological factors, which were assessed using the Social Support Rating Scale (SSRS), Self-Perceived Burden Scale (SPBS), and Hamilton Depression Scale (HAMD) within 3 days after admission to the hospital. Cognitive function was evaluated using the Montreal Cognitive Assessment at 3 months post-stroke. Logistic hierarchical regression models were used to examine the association between these three indicators and cognitive impairment following a stroke.

Results

Among these patients, cognitive function was assessed in 211 cases at the 3-month follow-up after the initial stroke event. At 3 months post-stroke, 118(55.9%) of the participants experienced cognitive impairment, while 93(44.1%) did not. The scores on the SPBS and HAMD showed significant associations with cognitive impairment at 3 months after stroke. The scores of SPBS [scores: 30~39 vs.<20 points, odds ratio (OR)=2.993 (1.135-7.896); scores: ≥40 vs.<20points, OR=7.382 (1.117-48.799); P=0.043] and the HAMD [scores: >7 vs.≤7 points, OR=3.287(1.362~7.936); P=0.008]. There were no significant associations observed between SSRS and PSCI.

Conclusion

Early screening for depressive symptoms and focusing on self-perceived burden can be beneficial for decision support for clinicians and improve cognitive function recovery at the 3-month mark post-stroke.

Assessing care dependence status and associated influencing factors among middle-aged hemiplegic stroke patients during the post-acute rehabilitation phase: A correlational study

AIMS

To comprehensively examine the prevailing condition of care dependence among middle-aged individuals who have experienced hemiplegia subsequent to a stroke and were currently undergoing post-acute rehabilitation. Additionally, the study sought to analyse the determinants that impacted this phenomenon.

DESIGN

A single-centre, cross-sectional study design.

METHODS

During the period from January 2020 to October 2022, a cohort of 196 hemiplegic stroke patients, aged between 40 and 65, and within 6 months of their stroke onset, was selected from the cerebrovascular outpatient clinic at a tertiary hospital in Hangzhou. The demographic and disease-related data, care dependence level, mental state, nutrition and depression status were collected. Furthermore, all collected data were analysed by descriptive and correlative statistical methods.

RESULTS

The care dependence level was 51.04 ± 9.42, with an incidence of care dependence of 78.1%. Multivariate regression analysis showed that age, history of falls, physical dysfunction, chronic comorbidities, depression, nutritional status and cognitive dysfunction were influencing factors for care dependence in the participants after a stroke.

CONCLUSION

The incidence of care dependence among hemiplegic patients aged from 40 to 65 years old in the early stage after a stroke was high. Nursing staff should focus on these patients with a history of falling, physical dysfunction, comorbidity, depression status, nutritional status and cognitive dysfunction in clinical practice.

RELEVANCE TO CLINICAL PRACTICE

The incidence of care dependence in middle-aged hemiplegic patients following a stroke is significantly increased. Some risk factors should be assessed, monitored, and controlled by nursing staff as early as possible in order to reduce the dependence levels in post-acute rehabilitation period and improve the quality of life of hemiplegia patients.

REPORTING METHOD

Our study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Checklist: cross-sectional studies (see Table S1).

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

MoCA Domain-Specific Pattern of Cognitive Impairment in Stroke Patients Attending Intensive Inpatient Rehabilitation: A Prospective Study

A domain-specific perspective to cognitive functioning in stroke patients may predict their cognitive recovery over time and target stroke rehabilitation intervention. However, data about domain-specific cognitive impairment after stroke are still scarce. This study prospectively investigated the domain-specific pattern of cognitive impairments, using the classification proposed by the Montreal Cognitive Assessment (MoCA), in a cohort of 49 stroke patients at admission (T0), discharge (T1), and six-month follow-up (T2) from subacute intensive rehabilitation. The predictive value of T0 cognitive domains cognitive impairment at T1 and T2 was also investigated. Patients' cognitive functioning at T0, T1, and T2 was assessed through the MoCA domains for executive functioning, attention, language, visuospatial, orientation, and memory. Different evolutionary trends of cognitive domain impairments emerged across time-points. Patients' impairments in all domains decreased from T0 to T1. Attention and executive impairments decreased from T0 to T2 (42.9% and 26.5% to 10.2% and 18.4%, respectively). Conversely, altered visuospatial, language, and orientation increased between T1 and T2 (16.3%, 36.7%, and 40.8%, respectively). Additionally, patients' global cognitive functioning at T1 was predicted by the language and executive domains in a subacute phase (p = 0.031 and p = 0.001, respectively), while in the long term, only attention (p = 0.043) and executive (p = 0.019) domains intervened. Overall, these results confirm the importance of a domain-specific approach to target cognitive recovery across time in stroke patients.

Patterns of Health-Related Quality of Life among Stroke Survivors: A Longitudinal Study

Six months poststroke is critical for optimizing stroke survivors' recovery and improving their health-related quality of life (HRQoL). Understanding HRQoL profiles in specific domains can provide a more typical plan for stroke survivors. This pilot study aimed to explore the HRQoL patterns among 39 stroke survivors within 6 months following diagnosis. The results revealed that there were four patterns based on HRQoL domains. Pattern 1: energy, family role, mobility, self-care, social role, and work/productivity domains likely to improve; Pattern 2: language and vision domains likely to improve and be stable; Pattern 3: thinking and upper extremity function domains likely to worsen and improve later; and Pattern 4: mood and personality domains likely to worsen and be constant. Health care providers can apply these results by continuing to assess and provide care to stroke survivors focusing on functional status, cognitive status, and depression over time. Further study should explore the factors predicting HRQoL.

Association of nursing hours with cognitive function, balance, and dependency level of stroke patients

AIMS

To examine the association of nursing hours given to patients with stroke with clinical characteristics to predict the nursing care needs.

DESIGN

Twenty-four-hour observational study METHODS: Nursing hours per patient day (NHPPD) of 171 stroke patients were measured by 146 nursing personnel who worked on the day of the observation. Cognitive function, balance ability and dependency level were assessed using the Korean version of the Mini-Mental State Examination (K-MMSE), the Korean version of the Berg Balance Scale (K-BBS) and the Korean version of the Modified Barthel Index (K-MBI), respectively.

RESULTS

The NHPPD were moderately correlated with K-MMSE (r = -.450), K-BBS (r = -.529) and K-MBI (r = -.549). The worse the cognitive function, balance ability and dependency level, the more were the nursing hours given to the patients. Therefore, these factors can be considered to be factors that predict nursing care needs for patients with stroke.

Factors Influencing Post-Stroke Cognitive Impairment in Patients with Type 2 Diabetes Mellitus

Objective

Type 2 diabetes mellitus (T2DM) and ischemic stroke, which are common diseases among older people, are closely related to cognitive impairment. This study aims to investigate the influencing factors of post-stroke cognitive impairment (PSCI) in patients with T2DM.

Methods

We enrolled 161 patients with T2DM who experienced acute ischemic stroke and were hospitalized in the Department of Neurology, Jinan Central Hospital, Shandong, China. Cognitive function was evaluated with the Montreal Cognitive Assessment scale. According to the results, patients were divided into three groups-the cognitively normal group, mild cognitive impairment group, and severe cognitive impairment group. We analyzed general demographic data, laboratory information, imaging data, the results of neuropsychological evaluation, and clinical features as well as influencing factors of PSCI in these patients and established a prediction model.

Results

The three groups of patients were significantly different in terms of age, education level, course of diabetes mellitus (DM), recurrent cerebral infarction (RCI), and other factors. RCI, course of DM, and glycated hemoglobin (HbA1c) were independent risk factors of PSCI in patients with T2DM, with odds ratio (95% confidence interval): 7.17 (2.09, 30.37), 5.39 (2.40, 14.59), and 3.89 (1.66, 10.04), respectively, whereas female, senior high school, serum albumin were protective factors: 0.28 (0.07, 0.95), 0.05 (0.01, 0.21), 0.20 (0.08, 0.42), respectively. Furthermore, we constructed a prediction model using sex, age, education level, RCI, DM course, HbA1c and serum albumin and obtained a receiver operating characteristic (ROC) curve. The area under the ROC curve is 0.966, suggesting the significant association of these influencing factors with PSCI in patients with T2DM.

Conclusion

In this study, the occurrence of PSCI in patients with T2DM was related to RCI, course of DM, and HbA1c, among other factors. Attention to influencing factors is needed in these patients for early diagnosis and timely intervention of cognitive impairment.

Assessment of functioning using the WHODAS 2.0 among people with stroke in Taiwan: A 4-year follow-up study

BACKGROUND

Stroke is a leading cause of long-term disability and is considered a major global health burden.

OBJECTIVES

We aimed to explore the 4-year changes in disability among patients with stroke under the existing health care system in Taiwan.

METHODS

We used the "Taiwan Data Bank of Persons with Disability" (TDPD), which collects data on candidates nationwide who want to apply for government benefits or social welfare. We included adults>18 years with stroke who were registered between July 11, 2012 and October 31, 2018. This was a longitudinal follow-up study with 2 times of assessments. The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) was used to evaluate function initially and at 4-year follow-up. Generalized estimating equations (GEE) were used to analyse changes in disability over 4 years and interaction effects.

RESULTS

A total of 3506 participants (2080 men) with mean age 62.2 (12.5) years and followed up for more than 4 years were included. Generally, participants with stroke showed improved function over the 4 years. Domain scores of mobility, participation, life activities, and overall score significant improved from 55.9 to 54.3, 53.0 to 43.6, 70.9 to 67.4, and 49.8 to 47.3, respectively (P<0.05). With respect to upper- and lower-limb motor deficiency, participants who required assistance or who were dependent showed significant improvement (P<0.05) in most of the WHODAS 2.0 domains except cognition. Younger patients (<65 years) tended to have significantly better outcomes, and institutionalized residents tended to show a significant and considerable deterioration in all WHODAS 2.0 domains.

CONCLUSION

Participants with stroke showed an improvement in levels of functioning, specifically in mobility, participation, and life activities, over 4 years of follow-up.

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

After stroke, dynamic changes take place from necrotic-apoptotic continuum, inflammatory response to poststroke neurogenesis, and remodeling of the network. These changes and baseline brain pathology such as small vessel disease (SVD) and amyloid burden may be associated with the occurrence of early or late poststroke cognitive impairment (PSCI) or dementia (PSD), which affect not only stroke victims but also their families and even society. We reviewed the current concepts and understanding of the pathophysiology for PSCI/PSD and identified useful tools for the diagnosis and the prediction of PSCI in serological, CSF, and image characteristics. Then, we untangled their relationships with blood pressure (BP) and blood pressure variability (BPV), important but often overlooked risk factors for PSCI/PSD. Finally, we provided evidence for the modifying effects of BP and BPV on PSCI as well as pharmacological and non-pharmacological interventions and life style modification for PSCI/PSD prevention and treatment.

The Role of Cilostazol and Inflammation in Cognitive Impairment After Ischemic Stroke

PURPOSE

The aim of this study is to examine the potential effect of cilostazol and inflammation on cognitive impairment after stroke in an Asian population.

METHODS

Forty-five patients with cognitive impairment after ischemic stroke using cilostazol were enrolled as the study group and 45 patients using aspirin or clopidogrel were enrolled as the control group. Neuropsychiatric assessments were administered at the start of the study and after 6 months. Multiple logistic regression analysis was used to estimate the association between the cognitive change and cilostazol use. Macrophage polarization were assessed using flow cytometry in 7 patients.

RESULTS

There were a significantly higher number of patients with peripheral arterial occlusive disease in the cilostazol group. No significant differences were observed in the cognitive change between the cilostazol and control groups. M1 macrophage subset increment were observed in the patient having a declined cognitive change.

CONCLUSION

Cilostazol did not make a significant difference in cognitive change after ischemic stroke. M1 macrophage subset increment may indicate post stroke cognitive decline. Due to limited number of subjects, these findings should be examined further in large-scale randomized clinical trials.

Predictors of Cognitive Impairment After Stroke: A Prospective Stroke Cohort Study

BACKGROUND

Post-stroke cognitive impairment (PSCI) significantly affects stroke survivors' quality of life and rehabilitation. A risk model identifying cognitive decline at admission would help to improve early detection and management of post-stroke patients.

OBJECTIVE

To develop a new clinical risk score for ischemic stroke survivors in predicting 6-12 months PSCI.

METHODS

We prospectively enrolled 179 patients diagnosed with acute ischemic stroke within a 7-day onset. Data were analyzed based on baseline demographics, clinical risk factors, and radiological parameters. Logistic regression and area under the receiver operating curve (AUROC) were used to evaluate model efficiency.

RESULTS

One hundred forty-five subjects completed a 6-12-month follow-up visit, and 77 patients (53.1%) were diagnosed with PSCI. Age (β= 0.065, OR = 1.067, 95% CI = 1.016-1.120), years of education (β= -0.346, OR = 0.707, 95% CI = 0.607-0.824), periventricular hyperintensity grading (β= 1.253, OR = 3.501, 95% CI = 1.652-7.417), diabetes mellitus (β= 1.762, OR = 5.825, 95% CI = 2.068-16.412), and the number of acute nonlacunar infarcts (β= 0.569, OR = 1.766, 95% CI = 1.243-2.510) were independently associated with 6-12 month PSCI, constituting a model with optimal predictive efficiency (AUC = 0.884, 95% CI = 0.832-0.935).

CONCLUSIONS

The optimized risk model was effective in screening stroke survivors at high risk of developing 6-12 months PSCI in a simple and pragmatic way. It could be a potential tool to identify patients with a high risk of PSCI at an early stage in clinical practice after further independent external cohort validation.

Cardiovascular risk factors indirectly affect acute post-stroke cognition through stroke severity and prior cognitive impairment: a moderated mediation analysis

BACKGROUND

Cognitive impairment is an important consequence of stroke and transient ischaemic attack, but its determinants are not fully understood. Simple univariable or multivariable models have not shown clinical utility for predicting cognitive impairment. Cardiovascular risk factors may influence cognition through multiple, direct, and indirect pathways, including effects on prior cognition and stroke severity. Understanding these complex relationships may help clinical teams plan intervention and follow-up strategies.

METHODS

We analysed clinical and demographic data from consecutive patients admitted to an acute stroke ward. Cognitive assessment comprised Abbreviated Mental Test and mini-Montreal Cognitive Assessment. We constructed bias-corrected confidence intervals to test indirect effects of cardiovascular risk factors (hypertension, vascular disease, atrial fibrillation, diabetes mellitus, previous stroke) on cognitive function, mediated through stroke severity and history of dementia, and we assessed moderation effects due to comorbidity.

RESULTS

From 594 eligible patients, we included 587 in the final analysis (age range 26-100; 45% female). Our model explained R² = 62.10% of variance in cognitive test scores. We found evidence for an indirect effect of previous stroke that was associated with increased risk of prevalent dementia and in turn predicted poorer cognitive score (estimate = - 0.39; 95% bias-corrected CI, - 0.75 to - 0.13; p = 0.02). Atrial fibrillation was associated with greater stroke severity and in turn with a poorer cognitive score (estimate = - 0.27; 95% bias-corrected CI, - 0.49 to - 0.05; p = 0.02). Conversely, previous TIA predicted decreased stroke severity and, through that, lesser cognitive impairment (estimate = 0.38; 95% bias-corrected CI, 0.08 to 0.75; p = 0.02). Through an association with reduced stroke severity, vascular disease was associated with lesser cognitive impairment, conditional on presence of hypertension and absence of diabetes mellitus (estimate = 0.36; 95% bias-corrected CI, 0.03 to 0.68; p = 0.02), although the modelled interaction effects did not reach statistical significance.

CONCLUSIONS

We have shown that relationships between cardiovascular risk factors and cognition are complex and simple multivariable models may be overly reductionist. Including direct and indirect effects of risk factors, we constructed a model that explained a substantial proportion of variation in cognitive test scores. Models that include multiple paths of influence and interactions could be used to create dementia prognostic tools for use in other healthcare settings.

Recombinant Human Growth Hormone Ameliorates Cognitive Impairment in Stroke Patients

OBJECTIVE

We aimed to determine the effects of recombinant human growth hormone (rhGH) replacement on cognitive function in subjects with poststroke cognitive impairment using resting-state functional magnetic resonance imaging.

METHODS

We included 60 patients with a first-ever stroke for 3 months and a diagnosis of cognitive impairment who were randomized 1:1 to receive either rhGH subcutaneously or placebo injection for 6 months. All subjects were required to receive the same rehabilitative therapy program. Both groups were subjected to pretreatment and posttreatment neuropsychological assessment using the Montreal Cognitive Assessment, serum neurotrophic factors, biomarkers of glucose and lipid metabolism, and functional magnetic resonance imaging during 6 months of the study period. The pattern of brain activity was determined by examining the functional connectivity and amplitude of low-frequency fluctuations (ALFF) of blood oxygen level dependent signal.

RESULTS

Forty-three (82.7%) completed the study. Treatment with rhGH reduced levels of triglycerides and low-density lipoprotein cholesterol but did not significantly altered plasma concentrations of glucose and glycated hemoglobin. We found a significant increase in serum insulin-like growth factor 1 levels (32.6%; P < 0.001) in the rhGH-treated group compared with that in the controls. After 6 months of rhGH treatment, mean Montreal Cognitive Assessment score improved from 16.31 (5.32) to 21.19 (6.54) (P < 0.001). The rhGH group showed significant increased area of activation with increased ALFF values in the regions of the frontal lobe, putamen, temporal lobe, and thalamus (P < 0.05), relative to the baseline conditions. The correlation analysis revealed that the ALFF and functional connectivity of default mode network was positively correlated with the ΔMoCA score and ΔIGF-1 levels; that is, the more the scale score increased, the higher the functional connection strength. No undesirable adverse effects were observed.

CONCLUSIONS

The rhGH replacement has a significant impact on global and domain cognitive functions in poststroke cognitive impairment.