Racial and ethnic differences in post-stroke subjective cognitive decline exist

Predictors of post stroke cognitive impairment: VITATOPS cognition substudy

INTRODUCTION

Post stroke cognitive impairment (PSCI) is a common complication of ischemic stroke. PSCI can involve different depending on clinical and stroke related characteristics. The aim of this study is to determine the factors associated with impairments in specific cognitive domains.

METHODS

The Vitamins to Prevent Stroke (VITATOPS) trial is a large, multinational randomised controlled trial. In this substudy, consecutive patients admitted for ischaemic stroke or transient ischaemic attack (TIA) at a tertiary hospital in Singapore were included. PSCI was defined as impairment of any of the six cognitive subgroups - visuoconstruction, attention, verbal memory, language, visual memory and visuomotor function - that were assessed annually for up to five years. Univariate and multivariate Cox proportional hazard models were used to determine factors associated with impairments in each of these cognitive domains.

RESULTS

A total of 736 patients were included in this study, of which 173 (23.5 %) developed cognitive impairment. Out of the six cognitive domains, the greatest proportion of patients had an impairment in visuoconstruction (26.4 %) followed by attention (19.8 %), verbal memory (18.3 %), language (17.5 %), visual memory (17.3 %) and visuomotor function (14.8 %). Patients with posterior circulation cerebral infarction (POCI) as the index stroke subtype had higher rates of cognitive impairment. Further subgroup analyses show that Indian race and advanced age were predictive of language impairment, whilst fewer years of education and POCI were predictive of verbal memory impairment. POCI was predictive of visual memory impairment, and advanced age and POCI were predictive of visuomotor function impairment.

CONCLUSION

We identified visuoconstruction and attention domains to be the most affected in our Asian cohort of PSCI. Advanced age, lower levels of education, posterior circulation strokes and concomitant comorbidities such as peripheral artery disease are independent predictors of PSCI.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Looking Upstream to Understand Race/Ethnicity as a Moderator for Poststroke Neuroinflammation and a Social Determinant for Poststroke Aphasia Outcomes

INTRODUCTION

Over the past decade, the stroke literature has begun to acknowledge and explore explanations for longstanding racial/ethnic differences in stroke outcomes. Poststroke cognitive impairment (PSCI) and poststroke aphasia are two such negative poststroke outcomes where racial/ethnic differences exist. Physiological differences, such as stroke type and lesion size, have been used to partially explain the variation in PSCI and aphasia. However, there is some evidence, although limited, that suggests neuroinflammatory processes as part of allostatic load may be a key contributor to the observed disparities.

METHOD

In this tutorial, we explore the influence of race differences in inflammation on poststroke cognitive outcomes. We suggest lifetime stress and other external determinants of health such as neighborhood environment and discriminatory practices through "weathering" explain differences in inflammation. While using an allostatic load framework, we explore the literature focusing specifically on the role of neuroinflammation on poststroke outcomes.

CONCLUSIONS

Examination of the immune response poststroke provides a foundation for understanding the mechanisms of PSCI and poststroke aphasia and the potential contributions of neuroinflammatory processes on poststroke cognitive outcomes. Furthermore, understanding of racial differences in those processes may contribute to a better understanding of racial disparities in general stroke outcomes as well as poststroke aphasia.

Prediction of subjective cognitive decline after corpus callosum infarction by an interpretable machine learning-derived early warning strategy

Background and purpose

Corpus callosum (CC) infarction is an extremely rare subtype of cerebral ischemic stroke, however, the symptoms of cognitive impairment often fail to attract early attention of patients, which seriously affects the long-term prognosis, such as high mortality, personality changes, mood disorders, psychotic reactions, financial burden and so on. This study seeks to develop and validate models for early predicting the risk of subjective cognitive decline (SCD) after CC infarction by machine learning (ML) algorithms.

Methods

This is a prospective study that enrolled 213 (only 3.7%) CC infarction patients from a nine-year cohort comprising 8,555 patients with acute ischemic stroke. Telephone follow-up surveys were carried out for the patients with definite diagnosis of CC infarction one-year after disease onset, and SCD was identified by Behavioral Risk Factor Surveillance System (BRFSS) questionnaire. Based on the significant features selected by the least absolute shrinkage and selection operator (LASSO), seven ML models including Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), Gaussian Naïve Bayes (GNB), Complement Naïve Bayes (CNB), and Support vector machine (SVM) were established and their predictive performances were compared by different metrics. Importantly, the SHapley Additive exPlanations (SHAP) was also utilized to examine internal behavior of the highest-performance ML classifier.

Results

The Logistic Regression (LR)-model performed better than other six ML-models in SCD predictability after the CC infarction, with the area under the receiver characteristic operator curve (AUC) of 77.1% in the validation set. Using LASSO and SHAP analysis, we found that infarction subregions of CC infarction, female, 3-month modified Rankin Scale (mRS) score, age, homocysteine, location of angiostenosis, neutrophil to lymphocyte ratio, pure CC infarction, and number of angiostenosis were the top-nine significant predictors in the order of importance for the output of LR-model. Meanwhile, we identified that infarction subregion of CC, female, 3-month mRS score and pure CC infarction were the factors which independently associated with the cognitive outcome.

Conclusion

Our study firstly demonstrated that the LR-model with 9 common variables has the best-performance to predict the risk of post-stroke SCD due to CC infarcton. Particularly, the combination of LR-model and SHAP-explainer could aid in achieving personalized risk prediction and be served as a decision-making tool for early intervention since its poor long-term outcome.

Associations Among Loneliness, Purpose in Life and Subjective Cognitive Decline in Ethnoracially Diverse Older Adults Living in the United States

Subjective cognitive decline (SCD), which precedes Mild Cognitive Impairment and dementia, may be affected by purpose in life (PiL) and loneliness in older adults. We investigated associations among PiL, loneliness, and SCD in US Latino (n = 126), Black (n = 74), Asian (n = 33), and White (n = 637) adults. Higher PiL predicted lower SCD in all groups (p-values < .012), except Black participants. Lower loneliness predicted lower SCD in Latino and White groups (p-values < .05), and PiL moderated this association in White adults. PiL and loneliness may play important roles in cognitive decline. Differential predictors of SCD suggest differential targets for preventing cognitive decline and dementia across ethnoracial groups.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The reliability and validity test of subjective cognitive decline questionnaire 21 with population in a Chinese community

BACKGROUND

Subjective cognitive decline-questionnaire 9 (SCD-Q9) was developed to detect SCD complaints at risk of mild cognitive impairment (MCI). However, our previous findings indicated that its coverage might be insufficient. To test this hypothesis, we recently translated SCD-Q21.

OBJECTIVE

To examine the reliability and validity of this translated SCD-Q21 and to explore its effectiveness for discriminating MCI from controls.

METHODS

Item analysis was performed to understand its item discrimination and homogeneity. The Cronbach's α and Spearman-Brown's split-half coefficients were calculated to test its reliability. The Kaiser-Meyer-Olkin (KMO) value, Bartlett's sphericity test, and exploratory factor analysis (EFA) were used to examine its construct validity. The content validity was evaluated using five-grade Likert scale. Finally, the SCD-Q21 scores in MCI and controls were compared.

RESULTS

The difference of each item between the extreme groups was significant. The Cronbach's α coefficient was .913 and Spearman-Brown's split-half coefficient was .894. When performing holding one-out approach, the Cronbach's α coefficient ranged from .906 to .914. The KMO value was .929 and the difference of Bartlett's Sphericity test was significant. All experts scored 5 points when assessing its content. Finally, a significant difference of score was found between MCI and NC groups.

CONCLUSIONS

The reliability and validity of the SCD-Q21 are good, which may pave a way for its application in a wider Chinese-speaking population.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Gendered racial differences and similarities in subjective cognitive decline and life satisfaction: results from a population-based sample

OBJECTIVE

The objectives of this study were to: 1) Determine the association between subjective cognitive decline (SCD) and life satisfaction; and 2) Assess the gendered racial/ethnic disparities in the association between SCD and life satisfaction.

METHOD

Data were obtained from 3,795 participants from the Behavioral Risk Factor Surveillance System survey. SCD was operationalized by "During the past 12 months, have you experienced confusion or memory loss that is happening more often or is getting worse?" Life satisfaction was operationalized by the question "In general how satisfied are you with your life?" Interaction terms of SCD*sex, SCD*race/ethnicity, and SCD*sex*race/ethnicity were used to determine potential effect measure modification. Crude and adjusted linear regression models, controlling for age, education, income and employment, were used to assess the association between SCD and life satisfaction by sex, race, and by gendered racial/ethnic groups: Black women, White women, Hispanic women, Other women; and Black men, White men, Hispanic men and Other men.

RESULTS

SCD was negatively associated with life satisfaction in the overall sample (β: -0.55; 95% CI: -0.66, -0.43). However, the negative associations seen across gender, race/ethnicity, and gendered racial/ethnic groups were statistically similar (p for interaction terms > 0.05). The highest effect estimate was seen for Other men (β: -1.22; 95% CI: -1.37, -1.09).

CONCLUSION

Interventions geared towards improving cognition may improve life satisfaction for all groups, irrespective of gender and/or race/ethnicity. Future research may include longitudinal studies to determine the temporal sequence between SCD and life satisfaction.

Circulating Neurofilament Light Predicts Cognitive Decline in Patients With Post-stroke Subjective Cognitive Impairment

Background

Subjective cognitive impairment (SCI) is common after acute ischemic stroke and adversely affects the quality of life. SCI is associated with an increased risk of developing mild cognitive impairment and dementia. Identifying biomarkers which could predict long-term cognitive outcomes of post-stroke SCI is of importance for early intervention. This study aims to investigate the association between circulating neurofilament light (NfL) and long-term cognitive function in patients with post-stroke SCI.

Methods

This longitudinal study recruited 304 patients with post-stroke SCI, and serum NfL levels were determined at baseline. These patients were followed up for 12 months for the observation of cognitive change. Cognitive performances were assessed by a Chinese version of the Telephone Interview of Cognitive Status-40 (TICS-40) scale.

Results

The patients were divided into a progression group (as determined by decreased TICS-40 scores) and a stable group (as determined by increased or unchanged TICS-40 scores). The progression group had significantly higher serum NfL levels than the stable group at baseline. Serum NfL levels were predictive for longitudinal cognitive decline during follow-up.

Conclusion

These findings imply that circulating NfL could predict the long-term cognitive change of patients with post-stroke SCI.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Disparities in Health Care for Black Patients in Physical Medicine and Rehabilitation in the United States: A Narrative Review

Racial health disparities continue to disproportionately affect Black persons in the United States. Black individuals also have increased risk of worse outcomes associated with social determinants of health including socioeconomic factors such as income, education, and employment. This narrative review included studies originally spanning a period of approximately one decade (December 2009-December 2019) from online databases and with subsequent updates though June 2020. The findings to date suggest pervasive inequities across common conditions and injuries in physical medicine and rehabilitation for this group compared to other racial/ethnic groups. We found health disparities across several domains for Black persons with stroke, traumatic brain injury, spinal cord injury, hip/knee osteoarthritis, and fractures, as well as cardiovascular and pulmonary disease. Although more research is needed, some contributing factors include low access to rehabilitation care, fewer referrals, lower utilization rates, perceived bias, and more self-reliance, even after adjusting for hospital characteristics, age, disease severity, and relevant socioeconomic variables. Some studies found that Black individuals were less likely to receive care that was concordant with clinical guidelines per the reported literature. Our review highlights many gaps in the literature on racial disparities that are particularly notable in cardiac, pulmonary, and critical care rehabilitation. Clinicians, researchers, and policy makers should therefore consider race and ethnicity as important factors as we strive to optimize rehabilitation care for an increasingly diverse U.S. population.