Neopterin, kynurenine metabolites, and indexes related to vitamin B6 are associated with post-stroke cognitive impairment: The Nor-COAST study.

BACKGROUND AND AIMS: We have previously shown that systemic inflammation was associated with post-stroke cognitive impairment (PSCI). Because neopterin, kynurenine pathway (KP) metabolites, and B6 vitamers are linked to inflammation, in our study we investigated whether those biomarkers were associated with PSCI. MATERIAL AND METHODS: The Norwegian Cognitive Impairment After Stroke study is a prospective multicenter cohort study of patients with acute stroke recruited from May 2015 through March 2017. Plasma samples of 422 participants (59 % male) with ischemic stroke from the index hospital stay and 3 months post-stroke were available for analyses of neopterin, KP metabolites, and B6 vitamers using liquid chromatography-tandem mass spectrometry. Mixed linear regression analyses adjusted for age, sex, and creatinine, were used to assess whether there were associations between those biomarkers and cognitive outcomes, measured by the Montreal Cognitive Assessment scale (MoCA) at 3-, 18-, and 36-month follow-up. RESULTS: Participants had a mean (SD) age of 72 (12) years, with a mean (SD) National Institutes of HealthStroke Scale score of 2.7 (3.6) at Day 1. Higher baseline values of quinolinic acid, PAr (i.e., an inflammatory marker based on vitamin B6 metabolites), and HKr (i.e., a marker of functional vitamin B6 status based on selected KP metabolites) were associated with lower MoCA score at 3, 18, and 36 months post-stroke (p < 0.01). Higher baseline concentrations of neopterin and 3-hydroxykynurenine were associated with lower MoCA scores at 18 and 36 months, and higher concentrations of xanthurenic acid were associated with higher MoCA score at 36 months (p < 0.01). At 3 months post-stroke, higher concentrations of neopterin and lower values of pyridoxal 5́-phosphate were associated with lower MoCA scores at 18- and 36-month follow-up, while lower concentrations of picolinic acid were associated with a lower MoCA score at 36 months (p < 0.01). CONCLUSION: Biomarkers and metabolites of systemic inflammation, including biomarkers of cellular immune activation, indexes of vitamin B6 homeostasis, and several neuroactive metabolites of the KP pathway, were associated with PSCI. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02650531.

Delirium is associated with low levels of upright activity in geriatric inpatients-results from a prospective observational study.

BACKGROUND: Delirium is common in geriatric inpatients and associated with poor outcomes. Hospitalization is associated with low levels of physical activity. Motor symptoms are common in delirium, but how delirium affects physical activity remains unknown. AIMS: To investigate differences in physical activity between geriatric inpatients with and without delirium. METHODS: We included acutely admitted patients ≥ 75 years in a prospective observational study at a medical geriatric ward at a Norwegian University Hospital. Delirium was diagnosed according to the DSM-5 criteria. Physical activity was measured by an accelerometer-based device worn on the right thigh. The main outcome was time in upright position (upright time) per 24 h (00.00 to 23.59) on the first day of hospitalization with verified delirium status. Group differences were analysed using t test. RESULTS: We included 237 patients, mean age 86.1 years (Standard Deviation (SD) 5.1), and 73 patients (30.8%) had delirium. Mean upright time day 1 for the entire group was 92.2 min (SD 84.3), with 50.9 min (SD 50.7) in the delirium group and 110.6 min (SD 89.7) in the no-delirium group, mean difference 59.7 minutes, 95% Confidence Interval 41.6 to 77.8, p value < 0.001. DISCUSSION: Low levels of physical activity in patients with delirium raise the question if immobilization may contribute to poor outcomes in delirium. Future studies should investigate if mobilization interventions could improve outcomes of delirium. CONCLUSIONS: In this sample of geriatric inpatients, the group with delirium had lower levels of physical activity than the group without delirium.

Diagnostic accuracy of the Clock Drawing Test in screening for early post-stroke neurocognitive disorder: the Nor-COAST study.

BACKGROUND: Post-stroke neurocognitive disorder, though common, is often overlooked by clinicians. Moreover, although the Montreal Cognitive Assessment (MoCA) has proven to be a valid screening test for neurocognitive disorder, even more time saving tests would be preferred. In our study, we aimed to determine the diagnostic accuracy of the Clock Drawing Test (CDT) for post-stroke neurocognitive disorder and the association between the CDT and MoCA. METHODS: This study is part of the Norwegian Cognitive Impairment After Stroke study, a multicentre prospective cohort study following patients admitted with acute stroke. At the three-month follow-up, patients were classified with normal cognition, mild neurocognitive disorder, or major neurocognitive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Any neurocognitive disorder compromised both mild- and major neurocognitive disorder. The CDT at the three-month assessment was given scores ranging from 0 to 5. Patients able to complete the CDT and whose cognitive status could be classified were included in analyses. The CDT diagnostic accuracy for post-stroke neurocognitive disorder was identified using receiver operating characteristic curves, sensitivity, specificity, positive predictive value, and negative predictive value. The association between the MoCA and CDT was analysed with Spearman's rho. RESULTS: Of 554 participants, 238 (43.0%) were women. Mean (SD) age was 71.5 (11.8) years, while mean (SD) National Institutes of Health Stroke Scale score was 2.6 (3.7). The area under the receiver operating characteristic curve of the CDT for major neurocognitive disorder and any neurocognitive disorder was 0.73 (95% CI, 0.68-0.79) and 0.68 (95% CI, 0.63-0.72), respectively. A CDT cutoff of < 5 yielded 68% sensitivity and 60% specificity for any neurocognitive disorder and 78% sensitivity and 53% specificity for major neurocognitive disorder. Spearman's correlation coefficient between scores on the MoCA and CDT was 0.50 (95% CI, 0.44-0.57, p < .001). CONCLUSIONS: The CDT is not accurate enough to diagnose post-stroke neurocognitive disorder but shows acceptable accuracy in identifying major neurocognitive disorder. Performance on the CDT was associated with performance on MoCA; however, the CDT is inferior to MoCA in identifying post-stroke neurocognitive disorder. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02650531). Retrospectively registered January 8, 2016.

A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study.

OBJECTIVE: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up. DESIGN: A prospective multicenter cohort-study with 18-month follow-up. SETTING: Outpatient clinics at 3 university hospitals and 2 local hospitals. PARTICIPANTS: 474 participants with the diagnosis of acute stroke (mean ± SD age; 70.5 (11.3), 59% male; N=474). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The primary outcome, fatigue at 18 months, was assessed using the Fatigue Severity Scale (FSS-7). FSS-7≥5 was defined as fatigue. In total, 45 prediction variables were collected, at initial hospital-stay and 3-month post-stroke. RESULTS: The best performing model, random forest, predicted 69% of all subjects with fatigue correctly with a sensitivity of 0.69 (95% CI: 0.50, 0.86), a specificity of 0.74 (95% CI: 0.66, 0.83), and an Area under the Receiver Operator Characteristic curve of 0.79 (95% CI: 0.69, 0.87) in new unseen data. The proportion of subjects predicted to suffer from fatigue, who truly suffered from fatigue at 18-months was estimated to 0.41 (95% CI: 0.26, 0.57). The proportion of subjects predicted to be free from fatigue who truly did not have fatigue at 18-months was estimated to 0.90 (95% CI: 0.83, 0.96). CONCLUSIONS: Our findings indicate that the model has satisfactory ability to predict fatigue in the chronic phase post-stroke and may be applicable in clinical settings.

Plasma Inflammatory Biomarkers Are Associated With Poststroke Cognitive Impairment: The Nor-COAST Study.

BACKGROUND: Inflammation is proposed to be involved in the pathogenesis of poststroke cognitive impairment. The aim of this study was to investigate associations between concentrations of systemic inflammatory biomarkers after ischemic stroke and poststroke cognitive impairment. METHODS: The Nor-COAST study (Norwegian Cognitive Impairment After Stroke) is a prospective observational multicenter cohort study, including patients hospitalized with acute stroke between 2015 and 2017. Inflammatory biomarkers, including the TCC (terminal C5b-9 complement complex) and 20 cytokines, were analyzed in plasma, collected at baseline, 3-, and 18 months poststroke, using ELISA and a multiplex assay. Global cognitive outcome was assessed with the Montreal Cognitive Assessment (MoCA) scale. We investigated the associations between plasma inflammatory biomarkers at baseline and MoCA score at 3-, 18-, and 36-month follow-ups; the associations between inflammatory biomarkers at 3 months and MoCA score at 18- and 36-month follow-ups; and the association between these biomarkers at 18 months and MoCA score at 36-month follow-up. We used mixed linear regression adjusted for age and sex. RESULTS: We included 455 survivors of ischemic stroke. Higher concentrations of 7 baseline biomarkers were significantly associated with lower MoCA score at 36 months; TCC, IL (interleukin)-6, and MIP (macrophage inflammatory protein)-1α were associated with MoCA at 3, 18, and 36 months (P<0.01). No biomarker at 3 months was significantly associated with MoCA score at either 18 or 36 months, whereas higher concentrations of 3 biomarkers at 18 months were associated with lower MoCA score at 36 months (P<0.01). TCC at baseline and IL-6 and MIP-1α measured both at baseline and 18 months were particularly strongly associated with MoCA (P<0.01). CONCLUSIONS: Higher concentrations of plasma inflammatory biomarkers were associated with lower MoCA scores up to 36 months poststroke. This was most pronounced for inflammatory biomarkers measured in the acute phase following stroke. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02650531.

Longitudinal brain age prediction and cognitive function after stroke.

Advanced age is associated with post-stroke cognitive decline. Machine learning based on brain scans can be used to estimate brain age of patients, and the corresponding difference from chronological age, the brain age gap (BAG), has been investigated in a range of clinical conditions, yet not thoroughly in post-stroke neurocognitive disorder (NCD). We aimed to investigate the association between BAG and post-stroke NCD over time. Lower BAG (younger appearing brain compared to chronological age) was found associated with lower risk of post-stroke NCD up to 36 months after stroke, even among those showing no evidence of impairments 3 months after hospital admission. For patients with no NCD at baseline, survival analysis suggested that higher baseline BAG was associated with higher risk of post-stroke NCD at 18 and 36 months. In conclusion, a younger appearing brain is associated with a lower risk of post-stroke NCD.

How do busy hospital circumstances affect mortality and readmission within 60 days: A cohort study of 680 000 acute admissions in Norway.

OBJECTIVE: To study mortality and readmissions for older patients admitted during more and less busy hospital circumstances. DESIGN: Cohort study where we identified patients that were admitted to the same hospital, during the same month and day of the week. We estimated effects of inflow of acute patients and the number of concurrent acute inpatients. Mortality and readmissions were analysed using stratified Cox-regression. SETTING: All people 80 years and older acutely admitted to Norwegian hospitals between 2008 and 2016. MAIN OUTCOME MEASURES: Mortality and readmissions within 60 days from admission. RESULTS: Among 294 653 patients with 685 197 admissions, mean age was 86 years (standard deviation 5). Overall, 13% died within 60 days. An interquartile range difference in inflow of acute patients was associated with a hazard ratio (HR) of 0.99, 95% confidence interval (95% CI) 0.98 to 1.00). There was little evidence of differences in readmissions, but a 7% higher risk (HR 1.07, 95% CI 1.06 to 1.09) of being discharged outside ordinary daytime working hours. CONCLUSIONS: Older patients admitted during busier circumstances had similar mortality and readmissions to those admitted during less busy periods. Yet, they showed a higher risk of discharge outside daytime working hours. Despite limited effects of busyness on a hospital level, there could still be harmful effects of local situations.

High ward occupancy, bedspacing, and 60 day mortality for patients with myocardial infarction, stroke, and heart failure.

AIMS: To study the consequences of crowded wards among patients with cardiovascular disease. METHODS AND RESULTS: This is a cohort study among 201 801 patients with 258 807 admissions who were acutely admitted for myocardial infarction (N = 107 895), stroke (N = 87 336), or heart failure (N = 63 576) to any Norwegian hospital between 2008 and 2016. The ward admitting most patients with the given clinical condition was considered a patient's home ward. We compared patients with the same condition admitted when home ward occupancy was different, at the same hospital and during comparable time periods. Occupancy was standardized such that a one-unit difference corresponded to the interquartile range in occupancy in the given month. One interquartile increase in home ward occupancy was associated with 7% higher odds of admission to an alternate ward [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.09 to 1.11], and length of stay was shorter (-0.10 days, 95% CI -0.18 to -0.09). Patients with heart failure had 15% higher odds of admission to alternate wards (OR 1.15, 95% CI 1.08 to 1.23) and increased mortality [hazard ratio (HR) 1.08, 95% CI 1.03 to 1.15]. We found no apparent effect on mortality for patients with myocardial infarction (HR 0.99, 95% CI 0.94 to 1.05) or stroke (HR 1.00, 95% CI 0.96 to 1.05). CONCLUSIONS: Patients with heart failure had higher risk of admission to alternate wards when home ward occupancy was high. These patients may be negatively affected by full wards.

Is Frailty Index a better predictor than pre-stroke modified Rankin Scale for neurocognitive outcomes 3-months post-stroke?

BACKGROUND: The prognostic value of frailty measures for post-stroke neurocognitive disorder (NCD) remains to be evaluated. AIMS: The aim of this study was to compare the predictive value of pre-stroke FI with pre-stroke modified Rankin Scale (mRS) for post-stroke cognitive impairment. Further, we explored the added value of including FI in prediction models for cognitive prognosis post-stroke. METHODS: We generated a 36-item Frailty Index (FI), based on the Rockwood FI, to measure frailty based on pre-stroke medical conditions recorded in the Nor-COAST multicentre prospective study baseline assessments. Consecutive participants with a FI score and completed cognitive test battery at three months were included. We generated Odds Ratio (OR) with NCD as the dependent variable. The predictors of primary interest were pre-stroke frailty and mRS. We also measured the predictive values of mRS and FI by the area (AUC) under the receiver operating characteristic curve. RESULTS: 598 participants (43.0% women, mean/SD age = 71.6/11.9, mean/SD education = 12.5/3.8, mean/SD pre-stroke mRS = 0.8/1.0, mean/SD GDS pre-stroke = 1.4/0.8, mean/SD NIHSS day 1 3/4), had a FI mean/SD score = 0.14/0.10. The logistic regression analyses showed that FI (OR 3.09), as well as the mRS (OR 2.21), were strong predictors of major NCD. When FI and mRS were entered as predictors simultaneously, the OR for mRS decreased relatively more than that for FI. AUC for NCD post-stroke was higher for FI than for mRS, both for major NCD (0.762 vs 0.677) and for any NCD (0.681 vs 0.638). CONCLUSIONS: FI is a stronger predictor of post-stroke NCD than pre-stroke mRS and could be a part of the prediction models for cognitive prognosis post-stroke. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02650531 .

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

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.

Clinically accessible neuroimaging predictors of post-stroke neurocognitive disorder: a prospective observational study.

BACKGROUND: Neurocognitive disorder (NCD) is common in stroke survivors. We aimed to identify clinically accessible imaging markers of stroke and chronic pathology that are associated with early post-stroke NCD. METHODS: We included 231 stroke survivors from the "Norwegian Cognitive Impairment after Stroke (Nor-COAST)" study who underwent a standardized cognitive assessment 3 months after the stroke. Any NCD (mild cognitive impairment and dementia) and major NCD (dementia) were diagnosed according to "Diagnostic and Statistical Manual of Mental Disorders (DSM-5)" criteria. Clinically accessible imaging findings were analyzed on study-specific brain MRIs in the early phase after stroke. Stroke lesion volumes were semi automatically quantified and strategic stroke locations were determined by an atlas based coregistration. White matter hyperintensities (WMH) and medial temporal lobe atrophy (MTA) were visually scored. Logistic regression was used to identify neuroimaging findings associated with major NCD and any NCD. RESULTS: Mean age was 71.8 years (SD 11.1), 101 (43.7%) were females, mean time from stroke to imaging was 8 (SD 16) days. At 3 months 63 (27.3%) had mild NCD and 65 (28.1%) had major NCD. Any NCD was significantly associated with WMH pathology (odds ratio (OR) = 2.73 [1.56 to 4.77], p = 0.001), MTA pathology (OR = 1.95 [1.12 to 3.41], p = 0.019), and left hemispheric stroke (OR = 1.8 [1.05 to 3.09], p = 0.032). Major NCD was significantly associated with WMH pathology (OR = 2.54 [1.33 to 4.84], p = 0.005) and stroke lesion volume (OR (per ml) =1.04 [1.01 to 1.06], p = 0.001). CONCLUSION: WMH pathology, MTA pathology and left hemispheric stroke were associated with the development of any NCD. Stroke lesion volume and WMH pathology were associated with the development of major NCD 3 months after stroke. These imaging findings may be used in the routine clinical setting to identify patients at risk for early post-stroke NCD. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02650531 , Registered 8 January 2016 - Retrospectively registered.

Current and Future Prevalence Estimates of Mild Cognitive Impairment, Dementia, and Its Subtypes in a Population-Based Sample of People 70 Years and Older in Norway: The HUNT Study.

BACKGROUND: Having accurate, up-to-date information on the epidemiology of mild cognitive impairment (MCI) and dementia is imperative. OBJECTIVE: To determine the prevalence of MCI and dementia in Norway using data from a large population-based study. METHODS: All people 70 + years of age, n = 19,403, in the fourth wave of the Trøndelag Health Study (HUNT4) were invited to participate in the study HUNT4 70 + . Trained health personnel assessed participants using cognitive tests at a field station, at homes, or at their nursing home. Interviewers also completed a structured carer questionnaire in regard to participants suspected of having dementia. Clinical experts made diagnoses according to DSM-5 criteria. We calculated prevalence weighing the data to ensure population representativeness. RESULTS: A total of 9,930 (51.2%) of the possible 19,403 people participated, and 9,663 of these had sufficient information for analysis. Standardized prevalence of dementia and MCI was 14.6% (95% confidence interval (CI) 13.9-15.4) and 35.3% (95% CI 34.3-36.4), respectively. Dementia was more prevalent in women and MCI more prevalent in men. The most prevalent dementia subtype was Alzheimer's disease (57%). By adding data collected from a study of persons < 70 years in the same region, we estimate that there are 101,118 persons with dementia in Norway in 2020, and this is projected to increase to 236,789 and 380,134 in 2050 and 2100, respectively. CONCLUSION: We found a higher prevalence of dementia and MCI than most previous studies. The present prevalence and future projections are vital for preparing for future challenges to the healthcare system and the entire society.

Test Accuracy of the Montreal Cognitive Assessment in Screening for Early Poststroke Neurocognitive Disorder: The Nor-COAST Study.

BACKGROUND AND PURPOSE: We determined the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) for poststroke neurocognitive disorder defined according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria in a prospective observational study. METHODS: Consecutive participants able to complete a cognitive test battery and MoCA 3 months poststroke were included. The reference standard of neurocognitive disorder was defined as a score of ≥1.5 SD below the normative mean in ≥1 cognitive domain on the cognitive test battery. RESULTS: Among 521 participants (43.6% women; mean age/SD, 71.5/12.0 years; mean education/SD, 12.4/3.8 years), the area under the receiver operating characteristic curve of MoCA for neurocognitive disorder was 0.80 (95% CI, 0.76-0.84). Using the standard MoCA cutoff <26, sensitivity was 0.71 (0.69-0.79) with specificity of 0.73 (0.66-0.76). MoCA cutoff of <27 gave higher sensitivity (0.82 [0.77-0.85]) at the expense of specificity (0.60 [0.53-0.66]). DISCUSSION: MoCA has reasonable accuracy for poststroke neurocognitive disorder diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02650531.

The Risk of Selection Bias in a Clinical Multi-Center Cohort Study. Results from the Norwegian Cognitive Impairment After Stroke (Nor-COAST) Study.

PURPOSE: The Norwegian Cognitive Impairment After Stroke (Nor-COAST) study aimed to estimate the prevalence and incidence of neurocognitive disorder in an unselected stroke cohort. The aim of the present study was to investigate whether selection bias occurred by comparing baseline characteristics from participants with non-participants in Nor-COAST. PATIENTS AND METHODS: Nor-COAST is a prospective cohort multi-center study, recruiting participants from five Norwegian hospitals. Patients with the diagnosis of acute stroke were screened for inclusion. Baseline data from the participants recruited between May 2015 and March 2017 were compared to corresponding data from those not participating in Nor-COAST but registered in the Norwegian Stroke Registry. Regression analysis was used to assess whether age, stroke severity, sex and stroke subtype were independently associated with inclusion in the study. RESULTS: Out of 2505 available patients, 815 (32.5%) were included in Nor-COAST. There were no differences between participants and non-participants with respect to age (mean (SD) age 73.5 (11.7) versus 74.2 (14.5) years) or sex (44.8% versus 46.9% women). A significantly larger proportion of the participants were independent prior to stroke (87% versus 78%), had mild strokes (69% versus 55%) and suffered from cerebral infarction (90% versus 84%). The regression analysis showed decreased odds ratio (OR) of being included for those with higher degree of pre-stroke dependency (OR 0.895, 95% CI 0.825 to 0.971, p=0.007) and a more severe stroke (OR 0.952, 95% CI 0.939 to 0.966, p<0.001). CONCLUSION: The participants in Nor-COAST had a better pre-stroke health condition and milder strokes compared to non-participants. However, the participants should be regarded as representative of the majority of the stroke population which suffers from mild strokes. Nevertheless, baseline information for non-participants should be available also in future clinical studies to make it easier to identify which part of the stroke population the results can be generalized to.

Post-stroke Cognitive Impairment-Impact of Follow-Up Time and Stroke Subtype on Severity and Cognitive Profile: The Nor-COAST Study.

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.

Impact of different methods defining post-stroke neurocognitive disorder: The Nor-COAST study.

INTRODUCTION: Post-stroke neurocognitive disorder (NCD) is common; prevalence varies between studies, partially related to lack of consensus on how to identify cases. The aim was to compare the prevalence of post-stroke NCD using only cognitive assessment (model A), DSM-5 criteria (model B), and the Global Deterioration Scale (model C) and to determine agreement among the three models. METHODS: In the Norwegian Cognitive Impairment After Stroke study, 599 patients were assessed 3 months after suffering a stroke. RESULTS: The prevalence of mild NCD varied from 174 (29%) in model B to 83 (14%) in model C; prevalence of major NCD varied from 249 (42%) in model A to 68 (11%) in model C. Cohen's kappa and Cohen's quadratic weighted kappa showed fair to very good agreement among models; the poorest agreement was found for identification of mild NCD. DISCUSSION: The findings indicate a need for international harmonization to classify post-stroke NCD.