Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients.

BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear. AIMS: We determined if WMH in strategic white matter tracts explain cognitive performance after stroke. METHODS: Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus. RESULTS: The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume. CONCLUSION: These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH. DATA ACCESS STATEMENT: The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.

Trigger factors in patients with a patent foramen ovale-associated stroke: A case-crossover study.

BACKGROUND: Patent foramen ovale (PFO) is a congenital anatomical variant which is associated with strokes in young adults. Contrary to vascular risk factors and atherosclerosis, a PFO is present from birth. However, it is completely unknown how an anatomical structure that is already present at birth in a large proportion of the population can convert into a PFO that causes stroke in a few. Recent studies reported a significant association between certain trigger factors and ischemic stroke in young adults. This study aims to investigate these triggers in PFO-associated stroke. METHODS: The ODYSSEY study, a multicenter prospective cohort study between 2013 and 2021, included patients aged 18-49 years experiencing their first-ever ischemic event. Participants completed a questionnaire about exposure to potential trigger factors. A case-crossover design was used to assess the relative risks (RR) with 95% confidence intervals (95% CI). The primary outcome was the RR of potential trigger factors for PFO-associated stroke. RESULTS: Overall, 1043 patients completed the questionnaire and had an ischemic stroke, of which 124 patients had a PFO-associated stroke (median age 42.1 years, 45.2% men). For patients with PFO-associated stroke, the RR was 26.0 (95% CI 8.0-128.2) for fever, 24.2 (95% CI 8.5-68.7) for flu-like disease, and 3.31 (95% CI 2.2-5.1) for vigorous exercise. CONCLUSION: In conclusion, flu-like disease, fever, and vigorous exercise may convert an asymptomatic PFO into a stroke-causing PFO in young adults. DATA ACCESS STATEMENT: The raw and anonymized data used in this study can be made available to other researchers on request. Written proposals can be addressed to the corresponding author and will be assessed by the ODYSSEY investigators for appropriateness of use, and a data sharing agreement in accordance with Dutch regulations will be put in place before data are shared.

Cognitive trajectory in the first year after first-ever ischaemic stroke in young adults: the ODYSSEY study.

BACKGROUND: Limited data exists on cognitive recovery in young stroke patients. We aimed to investigate the longitudinal course of cognitive performance during the first year after stroke at young age and identify predictors for cognitive recovery. METHODS: We conducted a multicentre prospective cohort study between 2013 and 2021, enrolling patients aged 18-49 years with first-ever ischaemic stroke. Cognitive assessments were performed within 6 months and after 1 year following the index event, covering seven cognitive domains. Composite Z-scores using normative data determined cognitive impairment (Z-score<-1.5). A Reliable Change Index (RCI) assessed cognitive recovery (RCI>1.96) or decline (RCI<-1.96). RESULTS: 393 patients (median age 44.3 years, IQR 38.4-47.2) completed cognitive assessments with a median time interval of 403 days (IQR 364-474) between assessments. Based on RCI, a similar proportion of patients showed improvement and decline in each cognitive domain, while the majority exhibited no cognitive change. Among cognitively impaired patients at baseline, improvements were observed in processing speed (23.1%), visuoconstruction (40.1%) and executive functioning (20.0%). Younger age was associated with better cognitive recovery in visuoconstruction, and larger lesion volume was related to cognitive recovery in processing speed. No other predictors for cognitive recovery were identified. CONCLUSIONS: Cognitive impairment remains prevalent in young stroke even 1 year after the event. Most patients showed no cognitive change, however, recovery may have occurred in the early weeks after stroke, which was not assessed in our study. Among initially cognitively impaired patients, cognitive recovery is observed in processing speed, visuoconstruction and executive functioning. It is still not possible to predict cognitive recovery in individual patients.

White Matter Hyperintensity Volume and Poststroke Cognition: An Individual Patient Data Pooled Analysis of 9 Ischemic Stroke Cohort Studies.

BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive dysfunction after ischemic stroke. Yet, uncertainty remains about affected domains, the role of other preexisting brain injury, and infarct types in the relation between WMH burden and poststroke cognition. We aimed to disentangle these factors in a large sample of patients with ischemic stroke from different cohorts. METHODS: We pooled and harmonized individual patient data (n=1568) from 9 cohorts, through the Meta VCI Map consortium (www.metavcimap.org). Included cohorts comprised patients with available magnetic resonance imaging and multidomain cognitive assessment <15 months poststroke. In this individual patient data meta-analysis, linear mixed models were used to determine the association between WMH volume and domain-specific cognitive functioning (Z scores; attention and executive functioning, processing speed, language and verbal memory) for the total sample and stratified by infarct type. Preexisting brain injury was accounted for in the multivariable models and all analyses were corrected for the study site as a random effect. RESULTS: In the total sample (67 years [SD, 11.5], 40% female), we found a dose-dependent inverse relationship between WMH volume and poststroke cognitive functioning across all 4 cognitive domains (coefficients ranging from -0.09 [SE, 0.04, P=0.01] for verbal memory to -0.19 [SE, 0.03, P<0.001] for attention and executive functioning). This relation was independent of acute infarct volume and the presence of lacunes and old infarcts. In stratified analyses, the relation between WMH volume and domain-specific functioning was also largely independent of infarct type. CONCLUSIONS: In patients with ischemic stroke, increasing WMH volume is independently associated with worse cognitive functioning across all major domains, regardless of old ischemic lesions and infarct type.

Sex Differences in Poststroke Cognitive Impairment: A Multicenter Study in 2343 Patients With Acute Ischemic Stroke.

BACKGROUND: Poststroke cognitive impairment (PSCI) occurs in about half of stroke survivors. Cumulative evidence indicates that functional outcomes of stroke are worse in women than men. Yet it is unknown whether the occurrence and characteristics of PSCI differ between men and women. METHODS: Individual patient data from 9 cohorts of patients with ischemic stroke were harmonized and pooled through the Meta-VCI-Map consortium (n=2343, 38% women). We included patients with visible symptomatic infarcts on computed tomography/magnetic resonance imaging and cognitive assessment within 15 months after stroke. PSCI was defined as impairment in ≥1 cognitive domains on neuropsychological assessment. Logistic regression analyses were performed to compare men to women, adjusted for study cohort, to obtain odds ratios for PSCI and individual cognitive domains. We also explored sensitivity and specificity of cognitive screening tools for detecting PSCI, according to sex (Mini-Mental State Examination, 4 cohorts, n=1814; Montreal Cognitive Assessment, 3 cohorts, n=278). RESULTS: PSCI was found in 51% of both women and men. Men had a lower risk of impairment of attention and executive functioning (men: odds ratio, 0.76 [95% CI, 0.61-0.96]), and language (men: odds ratio, 0.67 [95% CI, 0.45-0.85]), but a higher risk of verbal memory impairment (men: odds ratio, 1.43 [95% CI, 1.17-1.75]). The sensitivity of Mini-Mental State Examination (<25) for PSCI was higher for women (0.53) than for men (0.27; P=0.02), with a lower specificity for women (0.80) than men (0.96; P=0.01). Sensitivity and specificity of Montreal Cognitive Assessment (<26.) for PSCI was comparable between women and men (0.91 versus 0.86; P=0.62 and 0.29 versus 0.28; P=0.86, respectively). CONCLUSIONS: Sex was not associated with PSCI occurrence but affected domains differed between men and women. The latter may explain why sensitivity of the Mini-Mental State Examination for detecting PSCI was higher in women with a lower specificity compared with men. These sex differences need to be considered when screening for and diagnosing PSCI in clinical practice.

Subacute cognitive impairment after first-ever transient ischemic attack or ischemic stroke in young adults: The ODYSSEY study.

Introduction: We aimed to investigate the prevalence of cognitive impairment in the subacute phase after transient ischemic attack (TIA) and ischemic stroke (IS), factors associated with a vascular cognitive disorder, and the prevalence of subjective cognitive complaints and their relation with objective cognitive performance. Patients and methods: In this multicenter prospective cohort study, we recruited patients with first-ever TIA and IS, aged 18-49 years, between 2013 and 2021 for cognitive assessment up to 6 months after index event. We calculated composite Z-scores for seven cognitive domains. We defined cognitive impairment as a composite Z-score < -1.5. We defined major vascular cognitive disorder as a Z-score < -2.0 in one or more cognitive domains. Results: Fifty three TIA and 545 IS patients completed cognitive assessment with mean time to assessment of 89.7 (SD 40.7) days. The median NIHSS at admission was 3 (interquartile range, 1-5). Cognitive impairment was common in five domains (up to 37%), with similar proportion in TIA and IS patients. Patients with major vascular cognitive disorder had a lower education level, higher NIHSS scores and more frequent lesions in the left frontotemporal lobe than without vascular cognitive disorder (p < 0.05 FDR-corrected). Subjective memory and executive cognitive complaints were present in about two-thirds of the patients, but were weakly associated with objective cognitive performance (ß: -0.32 and -0.21, respectively). Discussion and conclusion: In the subacute phase after TIA or stroke in young adults, cognitive impairment and subjective cognitive complaints are prevalent, but they are weakly associated with each other.

Risk Factors and Causes of Ischemic Stroke in 1322 Young Adults.

BACKGROUND: Identification of risk factors and causes of stroke is key to optimize treatment and prevent recurrence. Up to one-third of young patients with stroke have a cryptogenic stroke according to current classification systems (Trial of ORG 10172 in Acute Stroke Treatment [TOAST] and atherosclerosis, small vessel disease, cardiac pathology, other causes, dissection [ASCOD]). The aim was to identify risk factors and leads for (new) causes of cryptogenic ischemic stroke in young adults, using the pediatric classification system from the IPSS study (International Pediatric Stroke Study). METHODS: This is a multicenter prospective cohort study conducted in 17 hospitals in the Netherlands, consisting of 1322 patients aged 18 to 49 years with first-ever, imaging confirmed, ischemic stroke between 2013 and 2021. The main outcome was distribution of risk factors according to IPSS classification in patients with cryptogenic and noncryptogenic stroke according to the TOAST and ASCOD classification. RESULTS: The median age was 44.2 years, and 697 (52.7%) were men. Of these 1322 patients, 333 (25.2%) had a cryptogenic stroke according to the TOAST classification. Additional classification using the ASCOD criteria reduced the number patients with cryptogenic stroke from 333 to 260 (19.7%). When risk factors according to the IPSS were taken into account, the number of patients with no potential cause or risk factor for stroke reduced to 10 (0.8%). CONCLUSIONS: Among young adults aged 18 to 49 years with a cryptogenic ischemic stroke according to the TOAST classification, risk factors for stroke are highly prevalent. Using a pediatric classification system provides new leads for the possible causes in cryptogenic stroke, and could potentially lead to more tailored treatment for young individuals with stroke.

Trigger Factors for Stroke in Young Adults: A Case-Crossover Study.

BACKGROUND AND OBJECTIVES: Causes of stroke in young adults differ from those in the elderly individuals, and in a larger percentage, no cause can be determined. To gain more insight into the etiology of (cryptogenic) stroke in the young population, we investigated whether trigger factors, such as short-lasting exposure to toxins or infection, may play a role. METHODS: Patients aged 18-49 years with a first-ever ischemic stroke or intracerebral hemorrhage (ICH) in 17 participating centers in the Netherlands completed a questionnaire about exposure to 9 potential trigger factors in hazard periods and on a regular yearly basis. A case-crossover design was used to assess relative risks (RRs) with 95% confidence intervals (95% CIs) by the Mantel-Haenszel case-crossover method, for any stroke (ischemic stroke and ICH combined) and for different etiologic subgroups of ischemic stroke. RESULTS: One thousand one hundred forty-six patients completed the questionnaire (1,043 patients with an ischemic stroke and 103 with an ICH, median age 44.0 years, 52.6% men). For any stroke, an increased risk emerged within 1 hour of cola consumption (RR 2.0, 95% CI 1.5-2.8) and vigorous physical exercise (RR 2.6, 95% CI 2.2-3.0), within 2 hours after sexual activity (RR 2.4, 95% CI 1.6-3.5), within 4 hours after illicit drug use (RR 2.8, 95% CI 1.7-4.9), and within 24 hours after fever or flu-like disease (RR 14.1, 95% CI 10.5-31.2; RR 13.9, 95% CI 8.9-21.9). Four trigger factors increased the risk of other determined and cryptogenic ischemic stroke, 3 that of cardioembolic stroke, 2 that of large vessel atherosclerosis and likely atherothrombotic stroke combined and stroke with multiple causes, and none that of stroke due to small vessel disease. DISCUSSION: We identified cola consumption, vigorous physical exercise, sexual activity, illicit drug use, fever, and flu-like disease as potential trigger factors for stroke in the young population and found differences in the type and number of trigger factors associated with different etiologic subgroups of ischemic stroke. These findings might help in better understanding the pathophysiologic mechanisms of (cryptogenic) stroke in the young population.

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke.

BACKGROUND: Post-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. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: The 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/.

Improvements in Endovascular Treatment for Acute Ischemic Stroke: A Longitudinal Study in the MR CLEAN Registry.

BACKGROUND: We evaluated data from all patients in the Netherlands who underwent endovascular treatment for acute ischemic stroke in the past 3.5 years, to identify nationwide trends in time to treatment and procedural success, and assess their effect on clinical outcomes. METHODS: We included patients with proximal occlusions of the anterior circulation from the second and first cohorts of the MR CLEAN (Multicenter Randomized Clinical trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) Registry (March 2014 to June 2016; June 2016 to November 2017, respectively). We compared workflow times and rates of successful reperfusion (defined as an extended Thrombolysis in Cerebral Infarction score of 2B-3) between cohorts and chronological quartiles (all included patients stratified in chronological quartiles of intervention dates to create equally sized groups over the study period). Multivariable ordinal logistic regression was used to assess differences in the primary outcome (ordinal modified Rankin Scale at 90 days). RESULTS: Baseline characteristics were similar between cohorts (second cohort n=1692, first cohort n=1488) except for higher age, poorer collaterals, and less signs of early ischemia on computed tomography in the second cohort. Time from stroke onset to groin puncture and reperfusion were shorter in the second cohort (median 185 versus 210 minutes; P<0.001 and 236 versus 270 minutes; P<0.001, respectively). Successful reperfusion was achieved more often in the second than in the first cohort (72% versus 66%; P<0.001). Functional outcome significantly improved (adjusted common odds ratio 1.23 [95% CI, 1.07-1.40]). This effect was attenuated by adjustment for time from onset to reperfusion (adjusted common odds ratio, 1.12 [95% CI, 0.98-1.28]) and successful reperfusion (adjusted common odds ratio, 1.13 [95% CI, 0.99-1.30]). Outcomes were consistent in the analysis per chronological quartile. CONCLUSIONS: Clinical outcomes after endovascular treatment for acute ischemic stroke in routine clinical practice have improved over the past years, likely resulting from improved workflow times and higher successful reperfusion rates.

Temporal evolution and predictors of subjective cognitive complaints up to 4 years after stroke.

OBJECTIVE: To examine the temporal evolution of subjective cognitive complaints in the long-term after stroke, and to identify predictors of long-term subjective cognitive complaints. METHODS: Prospective cohort study including 395 stroke patients. Subjective cognitive complaints were assessed at 2 months, 6 months and 4 years post-stroke, using the Checklist for Cognitive and Emotional consequences following stroke (CLCE-24). The temporal evolution of subjective cognitive complaints was described using multilevel growth modelling. Associations between CLCE-24 cognition score at 4 years post-stroke and baseline characteristics, depression, anxiety, cognitive test performance, and adaptive and maladaptive psychological factors were examined. Significant predictors were entered in a multivariate multilevel model. RESULTS: A significant increase in subjective cognitive complaints from 2 months up to 4 years (mean 3.7 years, standard deviation (SD) 0.6 years) post-stroke was observed (p≤0.001). Two months post-stroke, 76% of patients reported at least one cognitive complaint, 72% at 6 months, and 89% at 4 years post-stroke. A higher level of subjective cognitive complaints at 2 months and lower scores on adaptive and maladaptive psychological factors were significant independent predictors of a higher level of subjective cognitive complaints at 4 years post-stroke. CONCLUSION: Post-stroke subjective cognitive complaints increase over time and can be predicted by the extent of subjective cognitive complaints and the presence of adaptive and maladaptive psychological factors in the early phases after stroke.

Prediction of Cognitive Recovery After Stroke: The Value of Diffusion-Weighted Imaging-Based Measures of Brain Connectivity.

BACKGROUND AND PURPOSE: Prediction of long-term recovery of a poststroke cognitive disorder (PSCD) is currently inaccurate. We assessed whether diffusion-weighted imaging (DWI)-based measures of brain connectivity predict cognitive recovery 1 year after stroke in patients with PSCD in addition to conventional clinical, neuropsychological, and imaging variables. METHODS: This prospective monocenter cohort study included 217 consecutive patients with a clinical diagnosis of ischemic stroke, aged ≥50 years, and Montreal Cognitive Assessment score below 26 during hospitalization. Five weeks after stroke, patients underwent DWI magnetic resonance imaging. Neuropsychological assessment was performed 5 weeks and 1 year after stroke and was used to classify PSCD as absent, modest, or marked. Cognitive recovery was operationalized as a shift to a better PSCD category over time. We evaluated 4 DWI-based measures of brain connectivity: global network efficiency and mean connectivity strength, both weighted for mean diffusivity and fractional anisotropy. Conventional predictors were age, sex, level of education, clinical stroke characteristics, neuropsychological variables, and magnetic resonance imaging findings (eg, infarct size). DWI-based measures of brain connectivity were added to a multivariable model to assess additive predictive value. RESULTS: Of 135 patients (mean age, 71 years; 95 men [70%]) with PSCD 5 weeks after ischemic stroke, 41 (30%) showed cognitive recovery. Three of 4 brain connectivity measures met the predefined threshold of P<0.1 in univariable regression analysis. There was no added value of these measures to a multivariable model that included level of education and infarct size as significant predictors of cognitive recovery. CONCLUSIONS: Current DWI-based measures of brain connectivity appear to predict recovery of PSCD but at present have no added value over conventional predictors.

Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts.

BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model. METHODS: In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa. FINDINGS: In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high. INTERPRETATION: To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI. FUNDING: The Netherlands Organisation for Health Research and Development.

The relationship between social cognition and participation in the long term after stroke.

Social cognitive impairments may play a role in participation restrictions after stroke. Understanding their relationship could inform treatment approaches to improve participation. We investigated the relationship between social cognition and participation in the long term after stroke. Of 395 patients participating in a large prospective cohort study, cross-sectional data were available at 3-4 years post-stroke of 118 patients on tests for emotion recognition, theory of mind, empathy, and behaviour regulation. Participation was assessed with the Utrecht Scale for Evaluation of Rehabilitation - Participation (USER-P). Bivariate and multivariate regression analysis were used to examine the relationship between social cognitive domains and participation. The majority suffered from minor stroke (83.1% scored NIHSS 0-4). Only behaviour regulation was related to participation restrictions in bivariate analysis, but social cognitive impairments did not predict participation restrictions in multivariate regression in this group. To conclude, in a sample of minor stroke patients with mild impairments in theory of mind, emotion recognition and behavioural control, there were no associations with restrictions in participation. Research should examine whether a relationship is present in patients with more severe stroke. In addition, measuring social aspects of participation is necessary to further unravel this relationship, to determine treatment targets for improving participation.

High occurrence of impaired emotion recognition after ischemic stroke.

INTRODUCTION: Deficits of emotion recognition after ischemic stroke are often overlooked by clinicians, and are mostly not spontaneously reported by patients. However, impaired emotion recognition after stroke negatively affects the ability to return to work and the quality of life. It is still unknown how often impairments of emotion recognition occur shortly after ischemic stroke. We aimed to estimate the occurrence of impaired emotion recognition after ischemic stroke and to characterise these patients with impaired emotion recognition. PATIENTS AND METHODS: Two hundred thirty patients were included, derived from a prospective study of cognitive recovery. Five weeks after ischemic stroke a neuropsychological assessment was performed, including an emotion recognition task (i.e. Ekman 60-faces test). Emotion recognition was regarded as impaired if the total score was below the fifth percentile for a large independent reference sample. RESULTS: Emotion recognition was impaired in 33.5% of patients. Patients with impaired emotion recognition were more likely to have an abnormal Montreal Cognitive Assessment during hospitalisation, and 5 weeks after their stroke, a higher proportion of them had a vascular cognitive disorder (VCD). Even 20% of patients without VCD had impaired emotion recognition.Discussion: Emotion recognition was often impaired after ischemic stroke. This is clinically relevant, since impaired emotion recognition negatively impacts social functioning.Conclusion: Even when there was no cognitive disorder in traditional cognitive domains, emotion recognition was impaired in 1 out of 5 patients. Clinicians should systematically ask patients and their caregivers about deficits in emotion recognition, and, if needed, test for these deficits.

Motor Impairment Three Months Post Stroke Implies A Corresponding Cognitive Deficit.

BACKGROUND: While both motor and cognitive impairment are common after stroke, the focus of (early) treatment has always been on motor deficit. AIMS: The objective of the current study was to explore the link between motor and cognitive performance in stroke patients and to examine whether motor performance is associated with cognitive functioning at three months post stroke. METHODS: In both stroke patients (n = 142) and controls (n = 135), with the groups matched on age, gender and premorbid IQ, motor functioning was evaluated using both objective (Purdue Pegboard Test) and subjective measures (specific items from the Frenchay Activities Index and Barthel Index). Cognition, specifically information processing speed, working memory and cognitive flexibility, was assessed using objective tasks. The data were analyzed using Pearson product-moment correlation coefficients and logistic regression. RESULTS: Significant correlations between motor and cognitive functioning were found in stroke patients. The objective motor task was stronger than subjective measures in statistically explaining and predicting cognitive deficit, irrespective of stroke severity. CONCLUSIONS: We conclude that motor impairment at three months post-stroke should serve as a 'red flag' for professionals: cognitive impairment is likely and should also be evaluated.

Absence of an infarct on MRI is not uncommon after clinical diagnosis of ischemic stroke.

INTRODUCTION: An infarct on brain MRI is often seen as gold standard when diagnosing ischemic stroke. Although MRI has high sensitivity in detecting a lesion shortly after ischemic stroke, this rapidly declines when time progresses. We assessed the occurrence of a negative MRI 4-6 weeks after a discharge diagnosis of ischemic stroke, and compared the clinical characteristics of patients with a positive or negative MRI. PATIENTS AND METHODS: The first 125 patients from a prospective longitudinal study of cognitive recovery after ischemic stroke were included in this study. Clinical characteristics were collected during admission. Per protocol, 4-6 weeks after stroke a brain MRI was performed. We operationalized different levels of certainty of the clinical diagnosis of ischemic stroke of a panel of 3 expert vascular neurologists. RESULTS: Thirty patients (24%) were MRI negative. Patients that were MRI negative had lower stroke severity at admission, shorter duration of hospital-stay, and better functional status at discharge. The panel judged that 18/30 (60%) MRI negative patients and 27/30 (90%) MRI positive patients had a likely diagnosis of ischemic stroke. Compared to MRI negative patients with a less likely diagnosis, those with a likely diagnosis had higher admission stroke severity and more often received an acute intervention. DISCUSSION AND CONCLUSION: Absence of an infarct on MRI is not uncommon 4-6 weeks after a clinical diagnosis of ischemic stroke. The relatively high proportion of MRI negative strokes with a likely clinical diagnosis of ischemic stroke indicates that neurologists should be cautious ruling out the diagnosis based on MRI beyond the acute stroke stage.

Course and Predictors of Subjective Cognitive Complaints During the First 12 Months after Stroke.

BACKGROUND: Subjective Cognitive Complaints (SCC) are common after stroke. This study documents the prevalence and course of SCC in the first year after stroke and determines which patient characteristics in the first 3 months predict subsequent SCC at 1-year follow-up. METHODS: Using a longitudinal design, 155 patients (mean age 64.0 ± 11.9 years; 69.7% men) were assessed at 3 and 12 months after stroke. SCC were assessed using the Checklist for Cognitive and Emotional consequences following stroke (CLCE) inventory (content component [CLCE-c] and worry component [CLCE-w]). Potential predictors of 12 months SCC included demographics, stroke severity, objective cognitive impairment, psychological factors (depression, anxiety, perceived stress, fatigue, personality traits, coping style), and activities of daily life functioning assessed at 3 months poststroke. Multiple hierarchical linear regression analyses were used to determine predictors of SCC at 12 months poststroke. RESULTS: SCC remained stable from 3 to 12 months over time (CLCE-c from 3.3 ± 2.4 to 3.3 ± 2.6; CLCE-w: from 1.9 ± 2.2 to 2.1 2.5). Independent predictors of SCC at 12 months were baseline CLCE-c (ß = 0.54) and perceived stress (ß = 0.23) for content, and baseline CLCE-w (ß = 0.57) and depressive symptoms (ß = 0.23) for worry. CONCLUSIONS: Patients who report SCC at 3 months after stroke are likely to continue having these complaints at 1 year follow-up. Perceived stress and depressive symptoms additionally increase the likelihood of having SCC at 12 months, independent of SCC at 3 months poststroke. Rehabilitation programs that target reduction of stress and depression in the first months after stroke might reduce sustained SCC and improve well-being.

Extent to Which Network Hubs Are Affected by Ischemic Stroke Predicts Cognitive Recovery.

Background and Purpose- It is uncertain what determines the potential for cognitive recovery after ischemic stroke. The extent to which strategic areas of the brain network, so-called hubs, are affected by the infarct could be a key factor. We developed a lesion impact score, which estimates the damage to network hubs by integrating information on infarct size with healthy brain network topology. We verified whether the lesion impact score indeed reflects global network disturbances in patients and assessed if it could predict cognitive recovery. Methods- Seventy-five ischemic stroke patients without signs of a prestroke cognitive disorder were included, all with evidence of a cognitive disorder during hospitalization. A brain magnetic resonance imaging and neuropsychological assessment were performed 5 weeks (±1 week) after stroke. Neuropsychological testing was repeated after 1 year to assess cognitive recovery. Brain networks were reconstructed from diffusion-weighted data and consisted of 90 gray matter regions (ie, network nodes). A standard brain network map, indicating the hub-score of each node, was obtained from network data of 44 cognitively healthy adults. For each patient, we calculated the lesion impact score by multiplying the percentage of node volume affected by the infarct with the node's corresponding hub-score. The patients' maximum lesion impact score was used as outcome predictor. Results- A higher lesion impact score in patients, indicating an increasing infarct size in nodes with a higher hub-score, was related to lower global brain network efficiency (ß=-0.528 [-0.776 to -0.277]; P<0.001), independent of age, brain volume, infarct volume, and white matter hyperintensity severity. A lower lesion impact score, however, was an independent predictor of cognitive recovery 1 year after stroke (odds ratio=0.434 [0.193-0.978]; P=0.044). Conclusions- We introduced a lesion impact score that combines information on infarct size and network topology to predict long-term recovery after stroke. This score can potentially be used in a clinical setting, also without availability of high-resolution diffusion-weighted magnetic resonance imaging.

The Meta VCI Map consortium for meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping: Design and multicenter pilot study.

INTRODUCTION: The Meta VCI Map consortium performs meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping. Integration of data from different cohorts will increase sample sizes, to improve brain lesion coverage and support comprehensive lesion-symptom mapping studies. METHODS: Cohorts with available imaging on white matter hyperintensities or infarcts and cognitive testing were invited. We performed a pilot study to test the feasibility of multicenter data processing and analysis and determine the benefits to lesion coverage. RESULTS: Forty-seven groups have joined Meta VCI Map (stroke n = 7800 patients; memory clinic n = 4900; population-based n = 14,400). The pilot study (six ischemic stroke cohorts, n = 878) demonstrated feasibility of multicenter data integration (computed tomography/magnetic resonance imaging) and achieved marked improvement of lesion coverage. DISCUSSION: Meta VCI Map will provide new insights into the relevance of vascular lesion location for cognitive dysfunction. After the successful pilot study, further projects are being prepared. Other investigators are welcome to join.