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Severity of CIND and MCI predict incidence of dementia in an ischemic stroke cohort.

ABSTRACT: The utility of poststroke cognitive status, namely dementia, cognitive impairment no dementia (CIND), mild cognitive impairment (MCI), and no cognitive impairment (NCI), in predicting dementia has been previously examined. However, no studies to date have compared the ability of subtypes of MCI and CIND to predict dementia in a poststroke population.A cohort of ischemic stroke patients underwent neuropsychological assessment annually for up to 5 years. Dementia was defined using the DSM-IV criteria. Univariate and multivariable Cox proportional regression was performed to determine the ability of MCI subtypes, CIND severity, and individual domains of impairment to predict dementia.A total of 362 patients without dementia were followed up for a mean of 3.4 years (17% drop out), with 24 developing incident dementia. Older age, previous and recurrent stroke, and CIND and MCI subtypes were significant predictors of dementia. In multivariable analysis controlling for treatment allocation, patients who were older, had previous or recurrent stroke, and had either CIND moderate or multiple domain MCI with amnestic component were at elevated risk for dementia. In multivariable domain analysis, recurrent strokes, age, and previous strokes, verbal memory, and visual memory were significant predictors of dementia. Receiver operating characteristic curve analysis showed that CIND moderate (area under the curve: 0.893) and multiple domain MCI with amnestic component (area under the curve: 0.832) were significant predictors of conversion to dementia. All other classifications of cognitive impairment had areas under the curve less than 0.7.Stroke patients with cognitive impairment no dementia (CIND) moderate are at higher risk of developing dementia, while CIND mild patients are not at increased risk of developing dementia.

SUBMITTER: Narasimhalu K

PROVIDER: S-EPMC2788800 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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Severity of CIND and MCI predict incidence of dementia in an ischemic stroke cohort.

Narasimhalu K K Ang S S De Silva D A DA Wong M-C MC Chang H-M HM Chia K-S KS Auchus A P AP Chen C C

Neurology 20091201 22

<h4>Background</h4>The utility of poststroke cognitive status, namely dementia, cognitive impairment no dementia (CIND), mild cognitive impairment (MCI), and no cognitive impairment (NCI), in predicting dementia has been previously examined. However, no studies to date have compared the ability of subtypes of MCI and CIND to predict dementia in a poststroke population.<h4>Methods</h4>A cohort of ischemic stroke patients underwent neuropsychological assessment annually for up to 5 years. Dementia ...[more]

PMID: 19949033

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Project description:ImportanceIschemic stroke is associated with increased risk of dementia, but the association of stroke severity and recurrence with risk of impaired cognition is not well known.ObjectiveTo examine the risk of dementia after incident ischemic stroke and assess how it differed by stroke severity and recurrence.Design, setting, and participantsThe Atherosclerosis Risk in Communities (ARIC) study is an ongoing prospective cohort of 15 792 community-dwelling individuals from 4 US states (Mississippi, Maryland, Minnesota, and North Carolina). Among them, 15 379 participants free of stroke and dementia at baseline (1987 to 1989) were monitored through 2019. Data were analyzed from April to October 2021. Associations between dementia and time-varying ischemic stroke incidence, frequency, and severity were studied across an average of 4.4 visits over a median follow-up of 25.5 years with Cox proportional hazards models adjusted for sociodemographic characteristics, apolipoprotein E, and vascular risk factors.ExposuresIncident and recurrent ischemic strokes were classified by expert review of hospital records, with severity defined by the National Institutes of Health Stroke Scale (NIHSS; minor, ≤5; mild, 6-10; moderate, 11-15; and severe, ≥16).Main outcomes and measuresDementia cases adjudicated through expert review of in-person evaluations, informant interviews, telephone assessments, hospitalization codes, and death certificates. In participants with stroke, dementia events in the first year after stroke were not counted.ResultsAt baseline, the mean (SD) age of participants was 54.1 (5.8) years, and 8485 of 15 379 participants (55.2%) were women. A total of 4110 participants (26.7%) were Black and 11 269 (73.3%) were White. A total of 1378 ischemic strokes (1155 incident) and 2860 dementia cases were diagnosed 1 year or more after incident stroke in participants with stroke, or at any point after baseline in participants without stroke, were identified through December 31, 2019. NIHSS scores were available for 1184 of 1378 ischemic strokes (85.9%). Risk of dementia increased with both the number and severity of strokes. Compared with no stroke, risk of dementia by adjusted hazard ratio was 1.76 (95% CI, 1.49-2.00) for 1 minor to mild stroke, 3.47 (95% CI, 2.23-5.40) for 1 moderate to severe stroke, 3.48 (95% CI, 2.54-4.76) for 2 or more minor to mild strokes, and 6.68 (95% CI, 3.77-11.83) for 2 or more moderate to severe strokes.Conclusions and relevanceIn this study, risk of dementia significantly increased after ischemic stroke, independent of vascular risk factors. Results suggest a dose-response association of stroke severity and recurrence with risk of dementia.

Project description:BackgroundFlavonoid-rich foods have antiinflammatory, antiatherogenic, and antithrombotic properties that may contribute to a lower risk of ischemic stroke.ObjectivesWe aimed to investigate the relationship between habitual flavonoid consumption and incidence of ischemic stroke in participants from the Danish Diet, Cancer and Health Study.DesignIn this prospective cohort study, 55,169 Danish residents without a prior ischemic stroke [median (IQR) age at enrolment of 56 y (52-60)], were followed for 21 y (20-22). We used Phenol-Explorer to estimate flavonoid intake from food frequency questionnaires obtained at study entry. Incident cases of ischemic stroke were identified from Danish nationwide registries and restricted cubic splines in Cox proportional hazards models were used to investigate relationships with flavonoid intake.ResultsDuring follow-up, 4237 individuals experienced an ischemic stroke. Compared with participants in Q1 and after multivariable adjustment for demographics and lifestyle factors, those in Q5-for intake of total flavonoids, flavonols, and flavanol oligo + polymers-had a 12% [HR (95% CI): 0.88 (0.81, 0.96)], 10% [0.90 (0.82, 0.98)], and 18% [0.82 (0.75, 0.89)] lower risk of ischemic stroke incidence, respectively. Multivariable (demographic and lifestyle) adjusted associations for anthocyanins and flavones with risk of ischemic stroke were not linear, with moderate but not higher intakes associated with lower risk [anthocyanins Q3 vs. Q1 HR (95% CI): 0.85 (0.79, 0.93); flavones: 0.90 (0.84, 0.97)]. Following additional adjustment for dietary confounders, similar point estimates were observed; however, significance was only retained for anthocyanins and flavanol oligo + polymers [anthocyanins Q3 vs. Q1 HR (95% CI): 0.86 (0.79, 0.94); flavanol oligo + polymers Q5 vs. Q1 0.86 (0.78, 0.94)].ConclusionsThese findings suggest that moderate habitual consumption of healthy flavonoid-rich foods is associated with a lower risk of ischemic stroke and further investigation is therefore warranted.

Project description:Objectives: Patients with anterior circulation large vessel occlusion are at high risk of acute ischemic stroke, which could be disabling or fatal. In this study, we applied machine learning to develop and validate two prediction models for acute ischemic stroke (Model 1) and severity of neurological impairment (Model 2), both caused by anterior circulation large vessel occlusion (AC-LVO), based on medical history and neuroimaging data of patients on admission. Methods: A total of 1,100 patients with AC- LVO from the Second Hospital of Hebei Medical University in North China were enrolled, of which 713 patients presented with acute ischemic stroke (AIS) related to AC- LVO and 387 presented with the non-acute ischemic cerebrovascular event. Among patients with the non-acute ischemic cerebrovascular events, 173 with prior stroke or TIA were excluded. Finally, 927 patients with AC-LVO were entered into the derivation cohort. In the external validation cohort, 150 patients with AC-LVO from the Hebei Province People's Hospital, including 99 patients with AIS related to AC- LVO and 51 asymptomatic AC-LVO patients, were retrospectively reviewed. We developed four machine learning models [logistic regression (LR), regularized LR (RLR), support vector machine (SVM), and random forest (RF)], whose performance was internally validated using 5-fold cross-validation. The performance of each machine learning model for the area under the receiver operating characteristic curve (ROC-AUC) was compared and the variables of each algorithm were ranked. Results: In model 1, among the included patients with AC-LVO, 713 (76.9%) and 99 (66%) suffered an acute ischemic stroke in the derivation and external validation cohorts, respectively. The ROC-AUC of LR, RLR and SVM were significantly higher than that of the RF in the external validation cohorts [0.66 (95% CI 0.57-0.74) for LR, 0.66 (95% CI 0.57-0.74) for RLR, 0.55 (95% CI 0.45-0.64) for RF and 0.67 (95% CI 0.58-0.76) for SVM]. In model 2, 254 (53.9%) and 31 (37.8%) patients suffered disabling ischemic stroke in the derivation and external validation cohorts, respectively. There was no difference in AUC among the four machine learning algorithms in the external validation cohorts. Conclusions: Machine learning methods with multiple clinical variables have the ability to predict acute ischemic stroke and the severity of neurological impairment in patients with AC-LVO.

Project description:Background and Purpose- APOE-ε4 genotype is a risk factor for sporadic Alzheimer disease and reduced recovery from brain injury. Since data on APOE genotype and dementia associated with transient ischemic attack/stroke are sparse, we determined the associations in a longitudinal population-based cohort. Methods- All patients with transient ischemic attack or stroke (2002-2012) in a defined population of 92 728 OxVASC (Oxford Vascular Study) had follow-up to 5-years. Pre-event and incident postevent dementia were ascertained through direct patient assessment and follow-up, supplemented by review of hospital/primary care records. Associations between pre- and post-event dementia and APOE genotype (ε4/ε4-homozygous and ε4/ε3-heterozygous versus ε3/ε3) were examined using logistic regression and Cox regression models, respectively, adjusted for age, sex, education, cerebrovascular burden (stroke severity, prior stroke, white matter disease), diabetes mellitus, and dysphasia. Results- Among 1767 genotyped patients (mean/SD age, 73.0/13.0 years, 901 [51%] male, 602 [34%] transient ischemic attack), 1058 (59.9%) were APOE-ε3/ε3, 403 (22.8%) were ε4/ε3 and 30 (1.7%) were ε4-homozygous. Homozygosity was associated with both pre-event (adjusted odds ratio, 5.81 [95% CI, 1.93-17.48]; P=0.002) and postevent dementia (adjusted hazard ratio, 3.64 [95% CI, 1.90-7.00]; P<0.0001). Association with postevent dementia was maintained after further adjustment for baseline cognitive impairment (hazard ratio, 2.41 [95% CI, 1.19-4.89]; P=0.01). There were no associations overall between ε4/ε3 and pre-event dementia (adjusted odds ratio, 1.47 [95% CI, 0.88-2.45]; P=0.14) or postevent dementia (hazard ratio, 1.11 [95% CI, 0.84-1.48]; P=0.47). Conclusions- In patients with transient ischemic attack and stroke, APOE-ε4 homozygosity was associated with both pre- and post-event dementia. Associations were independent of cerebrovascular burden and may be mediated through increased neurodegenerative pathology or vulnerability to injury.

Dataset Information

Severity of CIND and MCI predict incidence of dementia in an ischemic stroke cohort.

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Severity of CIND and MCI predict incidence of dementia in an ischemic stroke cohort.

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