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The Impact of Vascular Risk Factors on Post-stroke Cognitive Impairment: The Nor-COAST Study.

ABSTRACT: Introduction: Post-stroke cognitive impairment (PSCI) is common, but evidence on the impact of vascular risk factors is lacking. We explored the association between pre-stroke vascular risk factors and PSCI and studied the course of PSCI. Materials and Methods: Vascular risk factors were collected at baseline in stroke survivors (n = 635). Cognitive assessments of attention, executive function, memory, language, and the Montreal Cognitive Assessment (MoCA) were performed at 3 and/or 18 months post-stroke. Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS). PSCI was measured with global z; MoCA z-score; and z-score of the four assessed cognitive domains. Mixed-effect linear regression was applied with global z, MoCA z-score, and z-scores of the cognitive domains as dependent variables. Independent variables were the vascular risk factors (hypertension, hypercholesterolemia, smoking, diabetes mellitus, atrial fibrillation, coronary heart disease, previous stroke), time, and the interaction between these. The analyses were adjusted for age, education, and sex. There were between 5 and 25% missing data for the variables for PSCI. Results: Mean age was 71.6 years (SD 11.7); 42% were females; and the mean NIHSS score at admittance was 3.8 (SD 4.8). Regardless of vascular risk factors, global z, MoCA, and all the assessed cognitive domains were impaired at 3 and 18 months, with MoCA being the most severely impaired. Atrial fibrillation (AF) was associated with poorer language at 18 months and coronary heart disease (CHD) with poorer MoCA at 18 months (LR = 12.80, p = 0.002, and LR = 8.32, p = 0.004, respectively). Previous stroke was associated with poorer global z and attention at 3 and 18 months (LR = 15.46, p < 0.001, and LR = 16.20, p < 0.001). In patients without AF, attention improved from 3 to 18 months, and in patients without CHD, executive function improved from 3 to 18 months (LR = 10.42, p < 0.001, and LR = 9.33, p = 0.009, respectively). Discussion: Our findings indicate that a focal stroke lesion might be related to pathophysiological processes leading to global cognitive impairment. The poorer prognosis of PSCI in patients with vascular risk factors emphasizes the need for further research on complex vascular risk factor interventions to prevent PSCI.

SUBMITTER: Aam S

PROVIDER: S-EPMC8374055 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Post-stroke cognitive impairment (PSCI) is common, but evidence of cognitive symptom profiles, course over time, and pathogenesis is scarce. We investigated the significance of time and etiologic stroke subtype for the probability of PSCI, severity, and cognitive profile. Methods: Stroke survivors (n = 617) underwent cognitive assessments of attention, executive function, memory, language, perceptual-motor function, and the Montreal Cognitive Assessment (MoCA) after 3 and/or 18 months. PSCI was classified according to DSM-5 criteria. Stroke severity was assessed with the National Institutes of Health Stroke Scale (NIHSS). Stroke subtype was categorized as intracerebral hemorrhage (ICH), large artery disease (LAD), cardioembolic stroke (CE), small vessel disease (SVD), or un-/other determined strokes (UD). Mixed-effects logistic or linear regression was applied with PSCI, MoCA, and z-scores of the cognitive domains as dependent variables. Independent variables were time as well as stroke subtype, time, and interaction between these. The analyses were adjusted for age, education, and sex. The effects of time and stroke subtype were analyzed by likelihood ratio tests (LR). Results: Mean age was 72 years (SD 12), 42% were females, and mean NIHSS score at admittance was 3.8 (SD 4.8). Probability (95% CI) for PSCI after 3 and 18 months was 0.59 (0.51-0.66) and 0.51 (0.52-0.60), respectively and remained constant over time. Global measures and most cognitive domains were assessed as impaired for the entire stroke population and for most stroke subtypes. Executive function and language improved for the entire stroke population (LR) = 9.05, p = 0.003, and LR = 10.38, p = 0.001, respectively). After dividing the sample according to stroke subtypes, language improved for ICH patients (LR = 18.02, p = 0.003). No significant differences were found in the severity of impairment between stroke subtypes except for attention, which was impaired for LAD and CE in contrast to no impairment for SVD (LR = 56.58, p < 0.001). Conclusions: In this study including mainly minor strokes, PSCI is common for all subtypes, both early and long-term after stroke, while executive function and language improve over time. The findings might contribute to personalizing follow-up and offer new insights into underlying mechanisms. Further research is needed on underlying mechanisms, PSCI prevention and treatment, and relevance for rehabilitation.

Project description:BackgroundCognitive impairment can complicate minor stroke, but there is limited information on risk factors including peak cognitive ability earlier in life.MethodsWe recruited patients with clinically-evident lacunar or minor non-lacunar ischaemic stroke, recorded clinical features, vascular risk factors, magnetic resonance imaging-detected stroke sub-type and small vessel disease burden. At 1-3 and 12 months after stroke, we assessed educational attainment (years of education), current cognition (Addenbrooke's Cognitive Examination-Revised), pre-morbid intelligence (National Adult Reading Test) and dependency (modified Rankin Scale).ResultsWe recruited 157 patients (87 lacunar, 64 non-lacunar ischaemic strokes), median age 66 (inter-quartile range 56-74) years, 36/157 (23%) patients had a Addenbrooke's Cognitive Examination-Revised score < 82 at one to three months, 29/151 (19%) had a Addenbrooke's Cognitive Examination-Revised < 82 at one year. Lower National Adult Reading Test score (cognitive impairment per point on National Adult Reading Test odds ratio 0.91, 95% confidence interval 0.87, 0.95) and older age (per year of age odds ratio 1.04 (95% confidence interval 1.01, 1.08) predicted one-year cognitive impairment more than stroke severity (per point on National Institute of Health Stroke Scale odds ratio 0.96 (95% confidence interval 0.0.68, 1.31)) or vascular risk factors e.g. hypertension (odds ratio for diagnosis of hypertension 0.52 (95% confidence interval 0.24, 1.15). Cognitive impairment was associated with having more white matter hyper-intensities (odds ratio per point increase in Fazekas score 1.42, 95% confidence interval 1.11, 1.83).DiscussionThis observational study provides evidence that pre-morbid intelligence quotient and education predict cognition after stroke, and confirms the association between cognitive impairment and small vessel disease.ConclusionPre-morbid intelligence should be considered in future studies of post-stroke cognition.

Project description:BACKGROUND:Cognitive impairment is an important consequence of stroke and transient ischaemic attack, but its determinants are not fully understood. Simple univariable or multivariable models have not shown clinical utility for predicting cognitive impairment. Cardiovascular risk factors may influence cognition through multiple, direct, and indirect pathways, including effects on prior cognition and stroke severity. Understanding these complex relationships may help clinical teams plan intervention and follow-up strategies. METHODS:We analysed clinical and demographic data from consecutive patients admitted to an acute stroke ward. Cognitive assessment comprised Abbreviated Mental Test and mini-Montreal Cognitive Assessment. We constructed bias-corrected confidence intervals to test indirect effects of cardiovascular risk factors (hypertension, vascular disease, atrial fibrillation, diabetes mellitus, previous stroke) on cognitive function, mediated through stroke severity and history of dementia, and we assessed moderation effects due to comorbidity. RESULTS:From 594 eligible patients, we included 587 in the final analysis (age range 26-100; 45% female). Our model explained R2?=?62.10% of variance in cognitive test scores. We found evidence for an indirect effect of previous stroke that was associated with increased risk of prevalent dementia and in turn predicted poorer cognitive score (estimate?=?-?0.39; 95% bias-corrected CI, -?0.75 to -?0.13; p?=?0.02). Atrial fibrillation was associated with greater stroke severity and in turn with a poorer cognitive score (estimate?=?-?0.27; 95% bias-corrected CI, -?0.49 to -?0.05; p?=?0.02). Conversely, previous TIA predicted decreased stroke severity and, through that, lesser cognitive impairment (estimate?=?0.38; 95% bias-corrected CI, 0.08 to 0.75; p?=?0.02). Through an association with reduced stroke severity, vascular disease was associated with lesser cognitive impairment, conditional on presence of hypertension and absence of diabetes mellitus (estimate?=?0.36; 95% bias-corrected CI, 0.03 to 0.68; p?=?0.02), although the modelled interaction effects did not reach statistical significance. CONCLUSIONS:We have shown that relationships between cardiovascular risk factors and cognition are complex and simple multivariable models may be overly reductionist. Including direct and indirect effects of risk factors, we constructed a model that explained a substantial proportion of variation in cognitive test scores. Models that include multiple paths of influence and interactions could be used to create dementia prognostic tools for use in other healthcare settings.

Project description:BACKGROUND:Early and late onset post-stroke cognitive impairment (PCI) contributes substantially to disability following stroke, and is a high priority within stroke research. The aetiology for PCI is complex and related to the stroke itself, brain resilience, comorbid brain diseases, prestroke vulnerability and complications during the hospital stay. The aim of the Norwegian Cognitive Impairment After Stroke study (Nor-COAST) is to quantify and measure levels of cognitive impairments in a general Norwegian stroke population and to identify biological and clinical markers associated with prognosis for cognitive disorders following incident stroke. The study will be organised within five work packages: 1) Incidence and trajectories 2) Pathological mechanisms 3) Development of a risk score 4) Impact of physical activity and 5) Adherence to secondary prevention. METHODS:Nor-COAST is an ongoing multicentre (five participating hospitals), prospective, cohort study with consecutive inclusion during the acute phase and with follow-up at three and 18?months, and at three years. Inclusion criteria are stroke defined according to the WHO criteria. During the recruitment period from 18.05.2015 to 31.03.2017, 816 participants have been included. Cognitive impairment will be classified according to the DSM-5 criteria using a consensus group. Cognitive function is assessed by a standardised neuropsychological test battery, the Montreal Cognitive Assessment, Trail making A and B, ten-word immediate and delayed recall test, the Controlled Oral Word Association, Global Deterioration Scale and proxy based information by and the Ascertain Dementia 8 item informant questionnaire. Biomarkers include magnetic resonance imaging, routine blood samples and bio-banking. Clinical assessments include characteristics of the stroke, comorbidity, delirium, frailty and tests for cognitive and physical function, sensor based activity monitoring and adherence to secondary prophylaxis. DISCUSSION:Nor-COAST is the first Norwegian multicentre study to quantify burden of PCI that will provide reliable estimates in a general stroke population. A multidisciplinary approach aiming to identify biomarkers and clinical markers of overall prognosis will add new knowledge about risk profiles, including pre-stroke vulnerability and modifiable factors such as physical activity and secondary prophylaxis of relevance for clinical practice and later intervention studies. TRIAL REGISTRATION:ClinicalTrials.gov: NCT02650531 . Retrospectively registered January 8, 2016. First participant included May 18, 2015.

Project description:With increased numbers of older people a higher burden of neurological disorders worldwide is predicted. Stroke and other cerebrovascular diseases do not necessarily present with different phenotypes in Africa but their incidence is rising in tandem with the demographic change in the population. Age remains the strongest irreversible risk factor for stroke and cognitive impairment. Modifiable factors relating to vascular disease risk, diet, lifestyle, physical activity and psychosocial status play a key role in shaping the current spate of stroke related diseases in Africa. Hypertension is the strongest modifiable risk factor for stroke but is also likely associated with co-inheritance of genetic traits among Africans. Somewhat different from high-income countries, strokes attributed to cerebral small vessel disease (SVD) are higher >30% among sub-Saharan Africans. Raised blood pressure may explain most of the incidence of SVD-related strokes but there are likely other contributing factors including dyslipidaemia and diabetes in some sectors of Africa. However, atherosclerotic and cardioembolic diseases combined also appear to be common subtypes as causes of strokes. Significant proportions of cerebrovascular diseases are ascribed to various forms of infectious disease including complications of human immunodeficiency virus. Cerebral SVD leads to several clinical manifestations including gait disturbance, autonomic dysfunction and depression. Pathological processes are characterized by arteriolosclerosis, lacunar infarcts, perivascular spaces, microinfarcts and diffuse white matter changes, which can now all be detected on neuroimaging. Except for isolated cases of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy or CADASIL, hereditary arteriopathies have so far not been reported in Africa. Prevalence estimates of vascular dementia (2-3%), delayed dementia after stroke (10-20%) and vascular cognitive impairment (30-40%) do not appear to be vastly different from those in other parts of the world. However, given the current demographic transition in both urban and rural settings these figures will likely rise. Wider application of neuroimaging modalities and implementation of stroke care in Africa will enable better estimates of SVD and other subtypes of stroke. Stroke survivors with SVD type pathology are likely to have low mortality and therefore portend increased incidence of dementia.

Project description:BackgroundPost-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction.AimsTo determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline.MethodsWe pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site.ResultsWe included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline.ConclusionsThe network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.

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The Impact of Vascular Risk Factors on Post-stroke Cognitive Impairment: The Nor-COAST Study.

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