Network analysis of neuropsychiatric, cognitive, and functional complications of stroke: implications for novel treatment targets.

AIM: Recovery from stroke is adversely affected by neuropsychiatric complications, cognitive impairment, and functional disability. Better knowledge of their mutual relationships is required to inform effective interventions. Network theory enables the conceptualization of symptoms and impairments as dynamic and mutually interacting systems. We aimed to identify interactions of poststroke complications using network analysis in diverse stroke samples. METHODS: Data from 2185 patients were sourced from member studies of STROKOG (Stroke and Cognition Consortium), an international collaboration of stroke studies. Networks were generated for each cohort, whereby nodes represented neuropsychiatric symptoms, cognitive deficits, and disabilities on activities of daily living. Edges characterized associations between them. Centrality measures were used to identify hub items. RESULTS: Across cohorts, a single network of interrelated poststroke complications emerged. Networks exhibited dissociable depression, apathy, fatigue, cognitive impairment, and functional disability modules. Worry was the most central symptom across cohorts, irrespective of the depression scale used. Items relating to activities of daily living were also highly central nodes. Follow-up analysis in two studies revealed that individuals who worried had more densely connected networks than those free of worry (CASPER [Cognition and Affect after Stroke: Prospective Evaluation of Risks] study: S = 9.72, P = 0.038; SSS [Sydney Stroke Study]: S = 13.56, P = 0.069). CONCLUSION: Neuropsychiatric symptoms are highly interconnected with cognitive deficits and functional disabilities resulting from stroke. Given their central position and high level of connectedness, worry and activities of daily living have the potential to drive multimorbidity and mutual reinforcement between domains of poststroke complications. Targeting these factors early after stroke may have benefits that extend to other complications, leading to better stroke outcomes.

Long-Term Cognitive Decline After Stroke: An Individual Participant Data Meta-Analysis.

BACKGROUND: Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive decline after stroke is unclear. We examined the course and determinants of cognitive change after stroke using individual participant data from the Stroke and Cognition Consortium. METHODS: Nine longitudinal hospital-based cohorts from 7 countries were included. Neuropsychological test scores and normative data were used to calculate standardized scores for global cognition and 5 cognitive domains. One-step individual participant data meta-analysis was used to examine the rate of change in cognitive function and risk factors for cognitive decline after stroke. Stroke-free controls were included to examine rate differences. Based on the literature and our own data that showed short-term improvement in cognitive function after stroke, key analyses were restricted to the period beginning 1-year poststroke to focus on its long-term effects. RESULTS: A total of 1488 patients (mean age, 66.3 years; SD, 11.1; 98% ischemic stroke) were followed for a median of 2.68 years (25th-75th percentile: 1.21-4.14 years). After an initial period of improvement through up to 1-year poststroke, decline was seen in global cognition and all domains except executive function after adjusting for age, sex, education, vascular risk factors, and stroke characteristics (-0.053 SD/year [95% CI, -0.073 to -0.033]; P<0.001 for global cognition). Recurrent stroke and older age were associated with faster decline. Decline was significantly faster in patients with stroke compared with controls (difference=-0.078 SD/year [95% CI, -0.11 to -0.045]; P<0.001 for global cognition in a subgroup analysis). CONCLUSIONS: Patients with stroke experience cognitive decline that is faster than that of stroke-free controls from 1 to 3 years after onset. An increased rate of decline is associated with older age and recurrent stroke.

Assessing the Predictive Validity of Simple Dementia Risk Models in Harmonized Stroke Cohorts.

BACKGROUND AND PURPOSE: Stroke is associated with an increased risk of dementia. To assist in the early identification of individuals at high risk of future dementia, numerous prediction models have been developed for use in the general population. However, it is not known whether such models also provide accurate predictions among stroke patients. Therefore, the aim of this study was to determine whether existing dementia risk prediction models that were developed for use in the general population can also be applied to individuals with a history of stroke to predict poststroke dementia with equivalent predictive validity. METHODS: Data were harmonized from 4 stroke studies (follow-up range, ≈12-18 months poststroke) from Hong Kong, the United States, the Netherlands, and France. Regression analysis was used to test 3 risk prediction models: the Cardiovascular Risk Factors, Aging and Dementia score, the Australian National University Alzheimer Disease Risk Index, and the Brief Dementia Screening Indicator. Model performance or discrimination accuracy was assessed using the C statistic or area under the curve. Calibration was tested using the Grønnesby and Borgan and the goodness-of-fit tests. RESULTS: The predictive accuracy of the models varied but was generally low compared with the original development cohorts, with the Australian National University Alzheimer Disease Risk Index (C-statistic, 0.66) and the Brief Dementia Screening Indicator (C-statistic, 0.61) both performing better than the Cardiovascular Risk Factors, Aging and Dementia score (area under the curve, 0.53). CONCLUSIONS: Dementia risk prediction models developed for the general population do not perform well in individuals with stroke. Their poor performance could have been due to the need for additional or different predictors related to stroke and vascular risk factors or methodological differences across studies (eg, length of follow-up, age distribution). Future work is needed to develop simple and cost-effective risk prediction models specific to poststroke dementia.

Association of Prediabetes and Type 2 Diabetes With Cognitive Function After Stroke: A STROKOG Collaboration Study.

Background and Purpose- Type 2 diabetes mellitus (T2D) is associated with cognitive impairment and an increased risk of dementia, but the association between prediabetes and cognitive impairment is less clear, particularly in a setting of major cerebrovascular events. This article examines the impact of impaired fasting glucose and T2D on cognitive performance in a stroke population. Methods- Seven international observational studies from the STROKOG (Stroke and Cognition) consortium (n=1601; mean age, 66.0 years; 70% Asian, 26% white, and 2.6% African American) were included. Fasting glucose level (FGL) during hospitalization was used to define 3 groups, T2D (FGL ≥7.0 mmol/L), impaired fasting glucose (FGL 6.1-6.9 mmol/L), and normal (FGL <6.1 mmol/L), and a history of diabetes mellitus and the use of a diabetes mellitus medication were also used to support a diagnosis of T2D. Domain and global cognition Z scores were derived from standardized neuropsychological test scores. The cross-sectional association between glucose status and cognitive performance at 3 to 6 months poststroke was examined using linear mixed models, adjusting for age, sex, education, stroke type, ethnicity, and vascular risk factors. Results- Patients with T2D had significantly poorer performance in global cognition (SD, -0.59 [95% CI, -0.82 to -0.36]; P<0.001) and in all domains compared with patients with normal FGL. There was no significant difference between impaired fasting glucose patients and those with normal FGL in global cognition (SD, -0.10 [95% CI, -0.45 to 0.24]; P=0.55) or in any cognitive domain. Conclusions- Diabetes mellitus, but not prediabetes, is associated with poorer cognitive performance in patients 3 to 6 months after stroke.

Short-term Trajectories of Poststroke Cognitive Function: A STROKOG Collaboration Study.

BACKGROUND AND OBJECTIVES: Past studies on poststroke cognitive function have focused on the average performance or change over time, but few have investigated patterns of cognitive trajectories after stroke. This project used latent class growth analysis (LCGA) to identify clusters of patients with similar patterns of cognition scores over the first-year poststroke and the extent to which long-term cognitive outcome is predicted by the clusters ("trajectory groups"). METHODS: Data were sought from the Stroke and Cognition consortium. LCGA was used to identify clusters of trajectories based on standardized global cognition scores at baseline (T1) and at the 1-year follow-up (T2). One-step individual participant data meta-analysis was used to examine risk factors for trajectory groups and association of trajectory groups with cognition at the long-term follow-up (T3). RESULTS: Nine hospital-based stroke cohorts with 1,149 patients (63% male; mean age 66.4 years [SD 11.0]) were included. The median time assessed at T1 was 3.6 months poststroke, 1.0 year at T2, and 3.2 years at T3. LCGA identified 3 trajectory groups, which were characterized by different mean levels of cognition scores at T1 (low-performance, -3.27 SD [0.94], 17%; medium-performance, -1.23 SD [0.68], 48%; and high-performance, 0.71 SD [0.77], 35%). There was significant improvement in cognition for the high-performance group (0.22 SD per year, 95% CI 0.07-0.36), but changes for the low-performance and medium-performance groups were not significant (-0.10 SD per year, 95% CI -0.33 to 0.13; 0.11 SD per year, 95% CI -0.08 to 0.24, respectively). Factors associated with the low- (vs high-) performance group include age (relative risk ratio [RRR] 1.18, 95% CI 1.14-1.23), years of education (RRR 0.61, 95% CI 0.56-0.67), diabetes (RRR 3.78, 95% CI 2.08-6.88), large artery vs small vessel strokes (RRR 2.77, 95% CI 1.32-5.83), and moderate/severe strokes (RRR 3.17, 95% CI 1.42-7.08). Trajectory groups were predictive of global cognition at T3, but its predictive power was comparable with scores at T1. DISCUSSION: The trajectory of cognitive function over the first-year poststroke is heterogenous. Baseline cognitive function ∼3.6 months poststroke is a good predictor of long-term cognitive outcome. Older age, lower levels of education, diabetes, large artery strokes, and greater stroke severity are risk factors for lower cognitive performance over the first year.

Profile of and risk factors for poststroke cognitive impairment in diverse ethnoregional groups.

OBJECTIVE: To address the variability in prevalence estimates and inconsistencies in potential risk factors for poststroke cognitive impairment (PSCI) using a standardized approach and individual participant data (IPD) from international cohorts in the Stroke and Cognition Consortium (STROKOG) consortium. METHODS: We harmonized data from 13 studies based in 8 countries. Neuropsychological test scores 2 to 6 months after stroke or TIA and appropriate normative data were used to calculate standardized cognitive domain scores. Domain-specific impairment was based on percentile cutoffs from normative groups, and associations between domain scores and risk factors were examined with 1-stage IPD meta-analysis. RESULTS: In a combined sample of 3,146 participants admitted to hospital for stroke (97%) or TIA (3%), 44% were impaired in global cognition and 30% to 35% were impaired in individual domains 2 to 6 months after the index event. Diabetes mellitus and a history of stroke were strongly associated with poorer cognitive function after covariate adjustments; hypertension, smoking, and atrial fibrillation had weaker domain-specific associations. While there were no significant differences in domain impairment among ethnoracial groups, some interethnic differences were found in the effects of risk factors on cognition. CONCLUSIONS: This study confirms the high prevalence of PSCI in diverse populations, highlights common risk factors, in particular diabetes mellitus, and points to ethnoracial differences that warrant attention in the development of prevention strategies.

STROKOG (stroke and cognition consortium): An international consortium to examine the epidemiology, diagnosis, and treatment of neurocognitive disorders in relation to cerebrovascular disease.

INTRODUCTION: The Stroke and Cognition consortium (STROKOG) aims to facilitate a better understanding of the determinants of vascular contributions to cognitive disorders and help improve the diagnosis and treatment of vascular cognitive disorders (VCD). METHODS: Longitudinal studies with ≥75 participants who had suffered or were at risk of stroke or TIA and which evaluated cognitive function were invited to join STROKOG. The consortium will facilitate projects investigating rates and patterns of cognitive decline, risk factors for VCD, and biomarkers of vascular dementia. RESULTS: Currently, STROKOG includes 25 (21 published) studies, with 12,092 participants from five continents. The duration of follow-up ranges from 3 months to 21 years. DISCUSSION: Although data harmonization will be a key challenge, STROKOG is in a unique position to reuse and combine international cohort data and fully explore patient level characteristics and outcomes. STROKOG could potentially transform our understanding of VCD and have a worldwide impact on promoting better vascular cognitive outcomes.

Incidence of dementia after ischemic stroke: results of a longitudinal study.

BACKGROUND AND PURPOSE: A number of cross-sectional epidemiological studies have reported that one fourth of elderly patients meet criteria for dementia 3 months after ischemic stroke, but few longitudinal studies of the incidence of dementia after stroke have been performed. We conducted the present study to investigate the incidence and clinical predictors of dementia after ischemic stroke. METHODS: We administered neurological, neuropsychological, and functional assessments annually to 334 ischemic stroke patients (age, 70.4+/-7.5 years) and 241 stroke-free control subjects (age, 70.6+/-6.5 years), all of whom were nondemented in baseline examinations. We diagnosed incident dementia using modified Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition criteria requiring deficits in memory and > or =2 additional cognitive domains, as well as functional impairment. RESULTS: The crude incidence rate of dementia was 8.49 cases per 100 person-years in the stroke cohort and 1.37 cases per 100 person-years in the control cohort. A Cox proportional-hazards analysis found that the relative risk (RR) of incident dementia associated with stroke was 3.83 (95% CI, 2.14 to 6.84), adjusting for demographic variables and baseline Mini-Mental State Examination score. Within the stroke cohort, intercurrent medical illnesses associated with cerebral hypoxia or ischemia were independently related to incident dementia (RR, 4.40; 95% CI, 2.20 to 8.85), adjusting for recurrent stroke, demographic variables, and baseline Mini-Mental State Examination score. CONCLUSIONS: The risk of incident dementia is high among patients with ischemic stroke, particularly in association with intercurrent medical illnesses that might cause cerebral hypoxia or ischemia, suggesting that cerebral hypoperfusion may serve as a basis for some cases of dementia after stroke.

Mortality in patients with dementia after ischemic stroke.

OBJECTIVE: Although dementia is typically considered to be a consequence of a variety of neurologic diseases, it can also serve as a risk factor for other adverse outcomes. The authors investigated dementia as a predictor of long-term survival among patients with ischemic stroke. METHODS: Neurologic, neuropsychological, and functional assessments were administered to 453 patients (mean age +/- SD, 72.0 +/- 8.3 years) 3 months after ischemic stroke. The authors diagnosed dementia in 119 (26.3%) of the patients using modified Diagnostic and Statistical Manual of Mental Disorders, Revised 3rd Edition, criteria requiring deficits in memory and two or more additional cognitive domains as well as functional impairment. Dementia as a predictor of long-term survival during up to 10 years of follow-up was then investigated. RESULTS: The mortality rate was 15.90 deaths per 100 person-years among patients with dementia and 5.37 deaths per 100 person-years among nondemented patients. A Cox proportional hazards analysis found that the relative risk (RR) of death was increased in association with dementia (RR = 2.4; 95% CI = 1.6 to 3.4), adjusting for the following: a major hemispheral stroke syndrome (RR = 1.4); a middle cerebral artery territory index stroke (RR = 1.7); a Stroke Severity Scale score of > or = 4, representing more severe stroke (RR = 1.8); atrial fibrillation (RR = 1.8); congestive heart failure (RR = 2.2); recurrent stroke occurring during follow-up (RR = 3.9); and demographic variables. The risk of death increased in association with the severity of dementia, but it did not differ by dementia subtype. CONCLUSIONS: Dementia is a significant independent risk factor for reduced survival after ischemic stroke, adjusting for other recognized predictors of mortality. The authors hypothesize that patients with dementia are at an elevated risk of mortality because of their increased burden of cerebrovascular disease, a tendency toward undertreatment for stroke prophylaxis among clinicians, or patient noncompliance with treatment regimens.

The neuropsychology of vascular cognitive impairment: is there a specific cognitive deficit?

The concept of Vascular Cognitive Impairment (VCI) encompasses patients across the entire continuum of cognitive impairment resulting from cerebrovascular disease (CVD), ranging from high-risk patients with no frank cognitive deficit (the "brain-at-risk" stage) through vascular dementia (VaD). There are accepted differences in the neuropsychological profile of patients with Alzheimer's disease (AD) and VaD. In patients with VaD, executive functions that tend to be disproportionately impaired include planning and sequencing, speed of mental processing, performance on unstructured tasks, and attention. Language production may be impaired in patients with VaD but primary language functions otherwise tend to be preserved. Patients with VaD also exhibit significantly more perseverations than patients with AD. Memory impairment is typically evident in patients with AD+CVD but memory impairment may also occur as a primary consequence of stroke in the posterior cerebral artery territory with involvement of the medial temporal lobe, or as a secondary consequence of a cognitive syndrome involving inattention due to primary executive dysfunction. Compared to VaD, patients with AD may exhibit greater deficits in functions (including memory) mediated by posterior cortical structures, such as the temporal and parietal lobes. AD patients exhibit a faster rate of information decay, reduced ability to benefit from cues to facilitate retrieval, and higher frequency of intrusion errors; in addition, certain aspects of language function, such as naming, may exacerbate deficits on verbal memory tasks. AD tends to affect lexicon while VaD tends to affect syntax. When patients with AD exhibit perseverations, they tend to be elicited by tests of semantic knowledge.

Cognition and white matter lesions.

Although it is recognized that ischemic stroke is a potent risk factor for vascular dementia, the influence of white matter lesions (WML) on cognitive function is less clear. In community-based MRI studies that have administered mental status tests to subjects who were free of clinically evident neurologic disease, a weak relationship between WML and generalized cognitive function has been reported. In studies that have administered neuropsychological test batteries, a stronger and more specific association has been recognized between WML and deficits in executive function, most likely due to the involvement of frontal-subcortical pathways. Cognitive deficits may be related to the total volume of the WML, with a threshold perhaps needing to be surpassed before such deficits are evident, but it is likely that the location of the WML also plays a role, with that threshold varying in association with the distribution of the lesions. Potential confounders of the results of previous studies include small, strategically located subcortical infarctions that may be masked by more extensive WML and other comorbid neurologic disorders, particularly Alzheimer's disease. Future studies should be prospective, utilize standardized methods for structural and functional brain imaging, and administer comprehensive neuropsychological assessments in order to more rigorously investigate the relationship between evolving WML and declining cognitive functions.

Ischemic stroke and depression.

Previous studies of depression after stroke have reported widely variable findings, possibly due to differences between studies in patient characteristics and methods for the assessment of depression, small sample sizes, and the failure to examine stroke-free reference groups to determine the base rate of depression in the general population. In an effort to address certain of those methodologic issues and further investigate the frequency and clinical determinants of depression after stroke, we administered the Structured Interview Guide for the Hamilton Depression Rating Scale (SIGH-D) and neurological, neuropsychological, and functional assessments to 421 patients (age = 71.5 +/- 8.0 years) 3 months after ischemic stroke and 249 stroke-free control subjects (age = 70.8 +/- 6.7 years). We required a SIGH-D total score > 11 for the identification of depression. We found that depression was less frequent (47/421 patients, or 11.2%, and 13/249 control subjects, or 5.2%), less severe, and less persistent in our stroke cohort than previously reported, possibly due to the underrepresentation of patients with a premorbid history of affective illness. Depression was associated with more severe stroke, particularly in vascular territories that supply limbic structures; dementia; and female sex. SIGH-D item analyses suggested that a reliance on nonsomatic rather than somatic symptoms would result in the most accurate diagnoses of depression after ischemic stroke.