In this review, we aimed to identify the risk factors that may influence cognitive impairment among stroke survivors, namely, demographic, clinical, psychological, and physical determinants. A search from Medline, Scopus, and ISI Web of Science databases was conducted for papers published from year 2004 to 2015 related to risk factors of cognitive impairment among adult stroke survivors. A total of 1931 articles were retrieved, but only 27 articles met the criteria and were reviewed. In more than half of the articles it was found that demographical variables that include age, education level, and history of stroke were significant risk factors of cognitive impairment among stroke survivors. The review also indicated that diabetes mellitus, hypertension, types of stroke and affected region of brain, and stroke characteristics (e.g., size and location of infarctions) were clinical determinants that affected cognitive status. In addition, the presence of emotional disturbances mainly depressive symptoms showed significant effects on cognition. Independent relationships between cognition and functional impairment were also identified as determinants in a few studies. This review provided information on the possible risk factors of cognitive impairment in stroke survivors. This information may be beneficial in the prevention and management strategy of cognitive impairments among stroke survivors.
It has been reported that approximately 15 to 30% of stroke survivors live with permanent disability [
Cognitive deficits among stroke survivals are widely recognized research area. However, the risk factors for cognitive impairment among stroke survivors have not been addressed adequately [
Stroke survivors with cognitive impairment are most likely to be dependent in activities of daily living. Further deterioration is possible as a result of limitation in activities. Psychiatric problems are also common among stroke survivors. This may delay recovery process and further impair cognitive function due to adaptations to unhealthy lifestyles or noncompliance to rehabilitation [
In order to improve overall physical function among stroke survivors, emotional disturbances such as depressive symptoms require management because both cognition and mood impairments are associated [
In a study by Sachdev et al. [
A cross-sectional study in United Kingdom (UK) found that the prevalence of cognitive impairment was high in the first month after ischemic stroke. This impairment involved speed and attention, frontal executive, nominal skills, perceptual skills, and visual memory [
Searches were conducted using three databases (i.e., Medline, Scopus, and ISI Web of Science). Researchers used the same search terms for all databases: “stroke” OR “cerebrovascular disease” OR “cerebrovascular accident” OR “CVA” AND “mild cognitive impairment” OR “cognitive impairment” OR “MCI”. There were 37 articles in Medline, 1654 articles in Scopus, and 240 articles in ISI Web of Science. Searches were refined by identifying the studies published in the years 2005–2015, full-text English articles, and adult aged as studied population. In addition, researcher restricted searching to area of study in psychology as an additional search criterion. Three hundred and twenty-six retrieved articles were screened using their titles and abstracts. Only 32 articles were related to review objectives and reviewed (12 articles in Medline, 7 articles in Scopus, and 13 articles in ISI Web of Science). Articles related to prestroke cognitive impairment, studies on validation of measurement tools, and molecular factors among stroke survivors were excluded from this review. Only 27 articles were included in this review after excluding five similar articles from different databases (Figure
Studies on cognitive impairment among stroke patients.
Study | Objective of study | Sample | Methodology | Setting | Prevalence | Outcome | |||
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Demographic | Clinical | Psychological | Physical | ||||||
Sachdev et al. [ |
(a) Identify determinants for CI |
169 | Cross-sectional study | Hospital based | 58% CI (VaD = 21.3%; VaMCI = 36.7%) |
(i) Older age (S) |
Medical factors: |
Depression (NS) |
NR |
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De Ronchi et al. [ |
Detect the impact of stroke on the occurrence of dementia and CIND in different age, sex, and education | 7930 | Cross-sectional study | Population based | 11.6% CI (CIND = 5.1%; M: 4.1%; F: 5.7%) (dementia = 6.5%; M: 4.9%; F: 7.5%) |
(a) Age and education modify effect of stroke on dementia (the risk was twofold stronger in older (75+ years old) and young people (61–75 years old) who had low education (0–3 years of schooling) with stroke as compared with higher education (4+ years of schooling) with stroke) |
History of stroke increased the risk ratio for dementia and CIND | NA | NA |
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Saxena et al. [ |
Determine the prevalence of depressive symptoms and cognitive impairment in stroke patients at 3 phases of rehabilitation processes | 200 | Observational study | Hospital based | Admission = 54.5% CI |
(a) Older age (S) |
Medical factors: |
Depressive symptoms on admission (S) |
Severe physical functioning (S) |
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Cederfeldt et al. [ |
Examine the differences in performance of P-ADL in relation to cognitive impairment at pre- and postdischarge | 45 | Longitudinal study | Hospital based & community based | Acute phase = 29% CI |
NA | NA | NA | (a) Intact cognition (before & after): improved P-ADL |
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Zhou et al. [ |
Identify the frequency and risk factors of cognitive impairment after stroke | 434 | Cross-sectional study | Hospital based | Poststroke CI = 37.1% |
Personal factors: |
Medical factors: |
NA | NA |
|
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Hurford et al. [ |
Examine domain-specific patterns of cognitive change after ischemic stroke | 209 | Cross-sectional study | Hospital based | Changes in the prevalence of cognitive impairment in each cognitive domain from less than 1 month to over 3 months: | ||||
(a) Speed and attention: 72.4% to 37.9% | |||||||||
(b) Frontal executive function: 34.4% to 16.2% | |||||||||
(c) Nominal skills: 30.2% to 8.1% | |||||||||
(d) Perceptual skills: 29.5% to 8.1% | |||||||||
(e) Visual memory: approximately 18% to 10% | |||||||||
(f) Verbal memory: approximately 28% to 18% | |||||||||
Tool used to assess CI: | |||||||||
(a) Neuropsychological tests battery | |||||||||
No determinants on demographic, clinical, psychological, and functional data were reported | |||||||||
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Claesson et al. [ |
Explore the impact of cognitive impairment on ADL performances, utilisation, and costs of health care | 149 | Cross-sectional study | Hospital based | CI = 72% (dementia: 28%) |
NA | NA | NA | Cognitively impaired: high dependency in I-ADL (i.e., continence, indoor mobility, toilet management, transfer, dressing/undressing, grooming, cooking, bath/shower, housework, and outdoor mobility) |
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Liman et al. [ |
(a) Determine the frequency and predictors of CI |
630 | Longitudinal study | Population based | (a) CI at 3 months = 14.8% |
(a) Predictor at 3 months after stroke: |
(a) Predictor at 3 months after stroke: |
NA | (a) Predictor at 3 months after stroke: |
|
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Stephens et al. [ |
Determine the relationship between attention, executive performance, and memory impairments with ADL impairments | 339 | Cross-sectional study | Hospital based | MCI = 19% |
NA | NA | Depression is positively correlated with 18 BADLS items |
(a) CRT = disabilities in basic self-care |
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Tang et al. [ |
Determine the relationship between CMBs and CIND reversion | 328 | Longitudinal study | Hospital based | Impairment at baseline: |
Determinant of reversion of CIND: |
Determinants of reversion of CIND: |
NA | NA |
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Akbari et al. [ |
(a) Investigate whether test performance in neurological and cognitive areas is able to predict daily task performance |
27 | Cross-sectional study | Population based | NR |
(a) Stroke severity (i.e., motor impairment) correlates with dependency in ADL performance | |||
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Narasimhalu et al. [ |
Determine neuroimaging measures (i.e., infarcts, WMH, and neurodegeneration) associated with subjective cognitive impairment (SCI) in cognitively intact patients with lacunar stroke | 145 | Cross-sectional study | Hospital based | SCI = 30.9% |
(a) Age (NS) |
Medical factors: |
Depression (NS) |
NR |
|
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Khedr et al. [ |
(a) Determine the relative frequency of first-ever PSD |
81 | Cross-sectional study | Hospital based | PSD = 21% |
Personal factors: |
Neurological factors: |
Depression (NS) |
Motor and functional disability (S) |
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Makin et al. [ |
Determine the factors associated with the progression of cognitive impairment after stroke | 193 | Longitudinal study | Hospital based | 3 months: |
(a) Older age (S) |
Medical factor: |
Depressive symptoms: not associated with cognitive evolution (progress or no progress) |
NR |
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Čengić et al. [ |
Analyze and compare motor and cognitive impairment in stroke patients at acute, subacute, and chronic phases | 50 | Cross-sectional study | Hospital based | CI at acute, subacute, and chronic phases = 12% |
Personal factors: |
Vascular factors: |
Stress (S) | (a) Physically inactive (S) |
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Douiri et al. [ |
Evaluate the prevalence of cognitive impairment after first-ever stroke up to 15 years | 4212 | Longitudinal study | Population based | (a) CI at 3 months = 24% |
(a) Older age (S) |
Neurological factors: |
NA | NR |
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Knopman et al. [ |
Determine the association of history of stroke with the diagnosis of MCI or cognitive impairment | 2050 | Cross-sectional study with case-control | Population based | MCI = 10.9% |
(I) Association of stroke with MCI: | |||
(a) History of stroke was associated with a higher risk of MCI (adjusted for age, sex, and education) | |||||||||
(b) Association between history of stroke and MCI subtypes (aMCI and naMCI) did not change when diabetes, coronary heart disease, | |||||||||
(c) History of stroke was associated with both aMCI and naMCI, while | |||||||||
(II) Association of stroke with cognitive domains: | |||||||||
(a) History of stroke was significantly associated with lower cognitive function in other domains (language, executive, and visuospatial) except memory | |||||||||
(b) The magnitude of the association was strongest for the executive function domain in unadjusted analyses | |||||||||
(c) Association was elevated about 2-fold for language and visuospatial domains after being adjusted for age, sex, and education | |||||||||
(d) Association of stroke with language, executive, and visuospatial domains did not change when diabetes, coronary heart disease, | |||||||||
(e) | |||||||||
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Sundar and Adwani [ |
(a) Assess cognitive dysfunction at 3 months after ischemic stroke |
164 | Cross-sectional study | Hospital based | Cognitive dysfunction = 31.7% |
(a) Memory was significantly and commonly affected in multi-infarct strokes as compared to single infarcts | |||
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Jokinen et al. [ |
Explore the severity and location of WMHs as predictor of neuropsychological test performance | 323 | Cross-sectional study | Hospital based | Dementia = 14.6% |
Predictors of neuropsychological deficits: |
Predictors of neuropsychological deficits: |
NA | NA |
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Cao et al. [ |
(a) Identify the neuropsychological impairments |
40 | Cross-sectional with case-control study | Hospital based | (a) Dementia = 12.5% |
(a) Lower education level is positively correlated with cognitive performance (global/partial impairment) | |||
(b) Token test, RPM, and AVLT delay and similarities were more often significantly failed tests by patients than control. However, these tests did not correlate with the number and site of lesions, ultrasound pattern, and neurological conditions | |||||||||
(c) No correlation between size, number and side of lesions within demented patients, globally or partially impaired patients, and etiological diagnosis of stroke | |||||||||
(d) Dementia and CI were associated with a lower BI score | |||||||||
Tool used: | |||||||||
(a) Daily activity abilities: BI | |||||||||
(b) Depression scale: SDS | |||||||||
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Mizrahi et al. [ |
Evaluate the relationship between diabetes and overall cognitive status in patients with ischemic stroke | 707 | Retrospective study | Hospital based | CI: NR |
(a) Older age (S) |
Medical factor: |
NA | NA |
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Mizrahi et al. [ |
Evaluate the relationship between atrial fibrillation (AF) and overall cognitive status in patients with ischemic stroke | 707 | Retrospective study | Hospital based | CI: NR |
(a) Older age (S) |
Medical factor: |
NA | NA |
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Tang et al. [ |
Examine the frequency and clinical determinants of poststroke cognitive impairment in Chinese stroke patients without dementia | 179 | Cross-sectional study | Hospital based | CI: 21.8% after 3-month stroke |
(a) Lower education (S) |
Medical factors: |
NA | NA |
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Sachdev et al. [ |
(a) Investigate neuropsychological features of the VaMCI and its progression over 3 years among stroke patients without dementia |
104 patients; 84 controls | Longitudinal study | Hospital based | Dementia over 3 years: |
(i) Clear determinants of progression did not emerge | |||
(ii) Neuropsychological impairment at baseline tended to predict greater decline | |||||||||
(iii) Global cognitive and functional impairment at baseline may be of importance in predicting dementia | |||||||||
(iv) Converters and nonconverters of VaMCI to VaD did not differ by age, sex, education, burden of vascular risk factors, or structural changes in brain | |||||||||
(v) VaMCI group had more vascular risk factors and more white matter hyperintensities at baseline than the NCI and control groups | |||||||||
(vi) Neuropsychological factor: greater decline of logical memory in VaMCI group | |||||||||
(vii) MRI measures: stroke patients had larger volumes of total, deep, periventricular WMHs and smaller amygdala volume (VaMCI group) | |||||||||
(a) Tools used in neuropsychological assessments: WMS-R, WAIS-R, Boston Naming Test, TMT, SDMT, Western Aphasia Battery, and NART | |||||||||
(b) Tools used in medical and psychiatric assessments: SOFAS, ADL, I-ADL, ESS, GHQ, GDS, HDRS, and Neuropsychiatric Inventory | |||||||||
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Tu et al. [ |
(a) Explore the prevalence and effects of vascular cognitive impairment (VCI) among ischemic stroke patients |
689 | Cross-sectional study with control group | Community based | VCI: 41.8% |
Personal factors: |
Medical factors: |
NA | NA |
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Zhang et al. [ |
Examine the incidence, neuropsychological characteristics, and risk factors of cognitive impairment 3 months after stroke in China | 577 | Cross-sectional study | Hospital based | PSCI: 30.7% |
Personal factors: |
Medical factor: |
Depressive symptom (S) |
NA |
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Narasimhalu et al. [ |
(a) Compare cognitive performance and quality of life (QOL) in stroke survivors and controls |
109 | Cross-sectional with case-control study | Hospital based | CI = 17.4% |
(a) Older age (NS) |
Medical factors: |
Psychiatric morbidity (S) |
NA |
S = significant determinant; NS = nonsignificant determinant; NR = not reported; M = male; F = female; NA = not available; P-ADL = personal activities of daily living; I-ADL = instrumental activities of daily living; WMHs = white matter hyperintensities; WML = white matter lesion; ADL = activities of daily living; BI = Barthel Index; CI = cognitive impairment; MCI = mild cognitive impairment; VaMCI = vascular mild cognitive impairment; SCI = subjective cognitive impairment; NCI = no cognitive impairment; PSCI = poststroke cognitive impairment; VaD = vascular dementia; ESS = European stroke scale; NART = national adult reading test; NART-IQ = national adult reading test-intelligence quotient; IQCODE = informant questionnaire for cognitive decline in the elderly; CVRF = cardiovascular risk factor; TIA = transient ischemic attack; CIND = cognitive impairment no dementia; VaCIND = vascular cognitive impairment no dementia; AACD = age-associated cognitive decline; BADLS = Bristol activities of daily living scale; CRT = choice reaction time; CMBs = cerebral microbleeds; BP = blood pressure; FAB = frontal assessment battery; SSS = Scandinavian stroke scale; MMSE = mini mental state examination; MoCA = Montreal cognitive assessment; PSD = poststroke dementia; Hcy = plasma homocysteine; SPMSQ = short portable mental status questionnaire; aMCI = amnestic mild cognitive impairment; naMCI = nonamnestic mild cognitive impairment; RPM = Raven’s progressive matrices; AVLT = auditory-verbal learning test; BSRT = Babcock story recall test; DST-B = digit span test backward; GDS = geriatric depression scale; HDRS = Hamilton depression rating scale; AMT = abbreviated mental test; CIMP-QUEST = cognitive impairment questionnaire; CDR = clinical dementia rating scale; SI = Sunnaas index of ADL; CAMCOG = Cambridge assessment of mental disorder in the elderly; VDB = vascular dementia battery; FAB = frontal assessment battery; LOTCA = Loewenstein occupational therapy cognitive assessment; PHQ-9 = patient health questionnaire; CASI = cognitive abilities screening instruments; WMS-R = Wechsler memory scale-revised; CES-D = Center for Epidemiologic Studies depression scale; SKT = short cognitive performance test for assessing memory and attention; SDS = self-rating depression scale; NIHSS = National Institutes of Health Stroke Scale; TMT = trail making test; SDMT = symbol digit modalities test; SOFAS = social and occupational functioning scale; GHQ = general health questionnaire; NINDS = National Institute of Neurological Disorders and Stroke; AIREN = Association Internationale pour la Recherche et L’Enseignement en Neurosciences; FOM = Fuld object memory test; RVR = rapid verbal retrieval; WAIS-R = Wechsler adult intelligence scale-revised; BD = block design; DS = digit span; DSM = diagnostic and statistical manual; MRI = magnetic resonance imaging.
Flow chart of the reviewing process.
A total of 27 studies fulfilled this review’s inclusion criteria in identifying demographic, clinical, psychological, and physical related risk factors that are likely to influence cognitive function among stroke survivors (refer to Table
One of the main predictors for cognitive impairment in stroke survivors reported in most studies was increased age [
Gender, family history of dementia, smoking habits, socioeconomic status, marital status, and ethnicity affected cognitive functioning [
Studies showed that stroke survivors who had medical conditions, such as low premorbid intellectual ability, preexisting cognitive impairment, and high stroke severity, and history of stroke and transient ischemic stroke (TIA), poststroke dysphasia, and urinary incontinence (aconuresis) had higher risk of cognitive decline [
Neuroimaging characteristics which explained neurological factors of stroke were also the most influential determinants for poststroke cognitive impairment. There were nine studies reporting on neurological factors. Researchers indicated that infarct volume, left carotid infarction, high level of paraventricular white matter lesion (WML), brain atrophy, basal ganglia infarct, large infarct volume, more cerebral white matter hyperintensities (WMHs), cortical atrophy, lacunar infarct, small vessel occlusion, and dominant hemispheric lesions and cortex lesion were the significant risk factors for cognitive impairment [
The common psychological distress among stroke survivors regardless of the severity of cognitive impairment was depression [
Stroke survivors who are physically dependent and more impaired usually perform poorly in tasks which require higher-order cognitive functions such as motor control, organization, problem solving, and memory. Lower performances in cognitive functions were positively associated with dependency in activity of daily living (ADL) [
Meanwhile, Liman et al. [
Findings from the current review suggested that there were various risk factors of cognitive impairment among stroke survivors. In terms of sociodemographic factors, age and education level were found to be the main predictors of cognitive impairment. Older adults were severely impaired in cognition due to the nature of stroke that accelerates cognitive decline [
Clinical factors were also main risk factors of cognitive impairment in stroke survivors. History of hypertension and diabetes may reduce the brain volume and also cause white matter lesions [
In a study on the effects of blood pressure, low diastolic blood pressure and episode of hypotension were significantly associated with cognitive declines [
Stroke had a significant impact on psychological wellbeing of stroke survivors. Stroke survivors usually experience sleep disturbances, low motivation, low self-esteem, and worries about their future due to restrictions and disabilities [
Mood changes and chronic stress due to physical limitations, restrictions in ADL, and low motivation were possible factors that caused emotional distress among stroke survivors [
Poor performance in executive function can affect individual’s ADL and increase their risk for poststroke disability [
There were two factors which caused cognitively impaired stroke survivors to have poor functional outcomes and these include higher stroke severity and poorer compliance to rehabilitation [
Identifying poststroke risk factors for cognitive impairment at early stage is important. Even more important is to evaluate the contribution of each risk factor towards cognitive impairment. Furthermore, current existing literature is lacking on integrating risk factors which increases poststroke risk for cognitive impairment. Previous studies mainly focus on identifying and grouping risk factors (e.g., [
This review indicated that age, level of education, history of stroke, diabetes mellitus, hypertension, types of stroke, affected region, size and location of infarction, depressive symptoms, and physical function were the potential factors that determine cognitive status of stroke survivors. Identifying these risk factors would be beneficial for clinician and healthcare practitioners in the management of stroke survivors. This will assist in the prevention of further cognitive decline and improve psychological wellbeing through effective intervention. Further research examining in-depth and multiple risk factors discussed in this review is warranted.
This review is a part of fulfilment of master thesis project that was conducted in a community based study.
The authors declare that there is no conflict of interests regarding the publication of this paper.
Researchers would like to express their gratitude to the National Stroke Association of Malaysia (NASAM) and Pusat Pemulihan Kesihatan-PERKIM for their help and support in this study.