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%) Tools used to assess CI: (a) MMSE and Global Deterioration Scale (b) DSM-III-R and experts opinion
(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) (b) Sex did not modify the effect of stroke on dementia
History of stroke increased the risk ratio for dementia and CIND
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 Discharge = 33.7% Follow-up (6 months) = 40.4% Tool used to assess CI: (a) AMT
(a) Older age (S) ≥76 years (b) Divorced (S)
Medical factors: (a) Poststroke dysphasia (S) (b) Poststroke urinary incontinence (S) (c) Cognitive impairment on admission (S) Vascular factor: (a) Ischemic heart disease (S)
Depressive symptoms on admission (S) Tool used: (a) GDS
Identify the frequency and risk factors of cognitive impairment after stroke
434
Cross-sectional study
Hospital based
Poststroke CI = 37.1% Stroke-related CI = 32.2% First-ever stroke CI = 29.6% Tool used to assess CI: (a) MMSE (b) IQCODE
Personal factors: (a) Older age (S) (8.5 years older than cognitive intact group) (b) Lower education (S) (≤6 years) Life style factor: (a) Everyday alcohol drinking (S)
Medical factors: (a) History of stroke (S) (b) Dysphasia (S) Neurological factor: (a) Left carotid infarction (S)
(a) Determine the frequency and predictors of CI (b) Examine the prevalence and factors associated with cognitive recovery and cognitive stability
630
Longitudinal study
Population based
(a) CI at 3 months = 14.8% (b) CI at 1 year = 13.3% (c) CI at 3 years = 11.8% Tool used to assess CI: (a) MMSE
(a) Predictor at 3 months after stroke: Older age (S) (b) Predictor for cognitive stability up to 3 years: Younger age (S)
(a) Predictor at 3 months after stroke: Diabetes mellitus (S)
NA
(a) Predictor at 3 months after stroke: stroke severity on day 7/BI (S) (b) Predictor for cognitive stability up to 3 years: less stroke severity/high BI (S) Tool used: (a) BI
Depression is positively correlated with 18 BADLS items Tool used: (a) GDS
(a) CRT = disabilities in basic self-care (b) Executive function = disabilities in intermediate self-care (c) MMSE = disabilities in complex self-management (d) Memory impairment: not associated with any disabilities in ADL Tool used: (a) BADLS
Determine the relationship between CMBs and CIND reversion
328
Longitudinal study
Hospital based
Impairment at baseline: (a) Visuomotor speed = 60.6% (b) Executive function = 49.6% (c) Visual memory = 29.9% (d) Verbal memory = 29.1% (e) Visual construction = 20.5% (f) Language = 13.4% (g) Attention = 6.3% Tools used to assess CI: (a) Modified VDB (b) FAB (c) MMSE (d) DSM-IV
Determinant of reversion of CIND: (a) Younger age (S) (b) Higher education (NS) Determinant of reversion of language domains: (a) Younger age (NS)
Determinants of reversion of CIND: (I) Medical factors: (a) Less visual constructional impairment (NS) (b) Less verbal memory impairment (NS) (c) More likely having visual memory impairment (NS) (d) More likely having executive function impairment (NS) (II) Vascular factors: (a) Absence of CMBs (S) (b) Absence of lobar CMBs (NS) (c) Hypertension (NS) (III) Neurological factors: (a) Small volume of WMHs (NS) Determinants of reversion of language domains: (a) Absence of CMBs (NS) (b) Small volume of WMHs (NS)
(a) Investigate whether test performance in neurological and cognitive areas is able to predict daily task performance (b) Examine whether the potential of tool measures can predict functional outcomes
27
Cross-sectional study
Population based
NR Tool used to assess cognitive status: (a) LOTCA
(a) Stroke severity (i.e., motor impairment) correlates with dependency in ADL performance (b) Self-care activities correlate with general cognitive performance (total score of LOTCA) (c) Visual perception and visuomotor organization correlated with BI components (d) Determinants on demographic, clinical, psychological, and physical data were not reported (e) LOTCA is not suitable to predict dependency in BADLS performance after stroke Tool used: (a) Neurological impairment = NIHSS (b) ADL performance = BI
(a) Determine the relative frequency of first-ever PSD (b) Determine the risk factors of PSD (c) Determine the relationship between total Hcy level and PSD
81
Cross-sectional study
Hospital based
PSD = 21% (PSD in ischemic stroke: 76.5%, PSD in hemorrhagic stroke: 23.5%) Tools used to assess CI: (a) Neuropsychological tests battery (b) MMSE (c) CASI (d) WMS-R (e) DSM-IV
Personal factors: (a) Older age (S) (b) Lower education (S) (c) Family history of dementia (S) Life style factor: (a) Smoking (S)
Neurological factors: (a) Large size of infarction (S) (b) Lacunar infarct (S) (c) Dominant hemispheric lesion (S) Vascular factors: (a) Hypertension (S) (b) High Hcy level (S) (c) Atrial fibrillation (NS) (d) Ischemic heart disease (NS) (e) Carotid stenosis (NS)
Depression (NS) Tool used: (a) HDRS
Motor and functional disability (S) Tools used: (a) SSS (b) BI
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% Tools used to assess CI: (a) Modified MMSE (b) SKT
Personal factors: (a) Older age (NS) (patient’s age under 75 years) (b) Lower education (S) (partially or fully completed elementary school) (c) Heredity (S) Life style and habits: (a) Smoking (S) (b) Alcohol drinking (S) (c) Obesity (S)
Vascular factors: (a) Hypertension (S) (b) Hyperlipoproteinemia (S) (c) Diabetes (S) (d) Heart disease (S)
Stress (S)
(a) Physically inactive (S) (b) Acute and subacute phases: better motor recovery and better cognitive status Tool used: (a) ESS
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% Tool used to assess CI: (a) Neuropsychological tests battery (b) DSM-IV
(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, APOE genotype, and hypertension were added to the model
(c) History of stroke was associated with both aMCI and naMCI, while APOE ɛ4 genotype was associated with aMCI only
(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, APOE genotype, and hypertension were added to the model
(e) APOE ɛ4 genotype was only associated with poor performance in the memory domain
(a) Assess cognitive dysfunction at 3 months after ischemic stroke (b) Assess frontal executive function using MMSE (c) Evaluate the degree and type of cognitive dysfunction in ischemic stroke subgroups
164
Cross-sectional study
Hospital based
Cognitive dysfunction = 31.7% (17.07% had been impaired on frontal executive functions only) Tool used to assess CI: (a) Modified Folstein’s MMSE (b) FAB
(a) Memory was significantly and commonly affected in multi-infarct strokes as compared to single infarcts (b) Frontal executive dysfunction was not significantly different in single versus multiple infarcts and cortical versus subcortical infarcts (c) Number of infarcts did not appear to influence cognitive dysfunction at 3 months of stroke (d) Determinants on demographic, clinical, psychological, and physical data were not reported
(a) Identify the neuropsychological impairments (b) Identify the clinical characteristics related to cognitively impaired patients
40
Cross-sectional with case-control study
Hospital based
(a) Dementia = 12.5% (b) CI = 7.5% (c) Partial CI = 20% Tool used to assess CI: (a) MMSE (b) Neuropsychological tests battery
(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
(a) Investigate neuropsychological features of the VaMCI and its progression over 3 years among stroke patients without dementia (b) Investigate risk factors for VaMCI conversion to dementia (c) Examine relationship of MRI measures with conversion
104 patients; 84 controls
Longitudinal study
Hospital based
Dementia over 3 years: (a) VaMCI subject: 24.4% (b) NCI subject: 8.5% Tool used to assess CI: (a) Consensus diagnosis by experts based on cognitive domains, functional status, and vascular etiologies
(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
(a) Explore the prevalence and effects of vascular cognitive impairment (VCI) among ischemic stroke patients (b) Provide a basis for prevention and treatment strategies
689
Cross-sectional study with control group
Community based
VCI: 41.8% (a) VaCIND: 32.1% (b) VaD: 9.7% Tool used to assess CI: (a) MMSE and MoCA (b) Criteria in NINDS and AIREN (c) Expert consensus
Personal factors: (a) Older age (S) (b) Low level of education (S) (c) Professional worker (S) (d) Living alone (S)# Behaviour and life style: (a) High alcohol intake (S) (b) Lack of hobbies (S)# (c) Longer sleep (S) (d) Irregular health check-up (S) Dietary habits: (a) Not eating fruit/vegetables (S) (b) Not drinking milk (S) (c) Not drinking tea (S)
Medical factors: (a) Family history of stroke (S) (b) Aconuresis (S) Vascular factors: (a) Hyperlipidemia (S)# (b) TIA (S) Neurological factors: (a) High level of paraventricular WML (S) (b) Macroangiopathy disease (S) (c) Brain atrophy (S)#