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This study aimed to investigate the influence of stroke lesions in pre-defined highly interconnected (rich club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance.We analyzed MRI data recorded at index stroke and ∼3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke (AIS) enrolled in the multisite MRI-GENIE study. Structural stroke lesions were spatially normalized and parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS>2) was modeled in a Bayesian logistic regression framework that relied on both lesion location, as well as the covariates: age, sex, total DWI lesion volume and comorbidities. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. Via model comparisons, we first tested whether the rich club region model was superior to a baseline model considering clinical covariates and lesion volume only. In spatial specificity analyses, we randomized the split into “rich club” and “non-rich club” regions and compared the effect of the actual rich club regions to the distribution of effects from 1,000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club region effects.A total of 822 patients (age: 64.7 (standard deviation: 15.0), 39% women, 27.7% with mRS>2) were analyzed. The rich club model substantially outperformed the baseline model (weights of model comparison: rich club model: 0.96; baseline: 0.04). Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations (15/1,000 random constellations with higher mean posterior values). Among the these 15 random constellations with higher means, the most frequently selected regions were the inferior temporal gyrus (posterior division, 8/15), the putamen (8/15), the cingulate gyrus (7/15) and the superior parietal lobule (6/15). Rich club regions were substantially more important in explaining long-term outcome in women than in men (mean of the difference distribution:-0.107, 90%-HDPI:-0.193 to -0.0124).Lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific, i.e., the majority of random combinations of six regions had comparably smaller effects on long-term outcome. Effects were substantially more pronounced in women.

ObjectiveTo develop a simple and effective risk score for predicting which stroke patients will have persistent impairment of upper extremity motor function at 90 days.DesignPost hoc analysis of clinical trial patients hospitalized with acute ischemic stroke who were followed for 90 days to determine functional outcome.SettingPatient were hospitalized at facilities across the United States.ParticipantsWe created a harmonized cohort of individual patients (N=1653) from the NINDS tPA, ALIAS part 2, IMS-III, DEFUSE 3, and FAST-MAG trials. We split the cohort into balanced derivation and validation samples.InterventionsNot applicable.Main outcome measuresThe primary outcome was persistent arm impairment, defined as a National Institutes of Health Stroke Scale (NIHSS) arm domain score of 2 to 4 at 90 days in patients who had a 24-hour NIHSS arm score of 1 or more. We used least absolute shrinkage and selection operator regression to determine the elements of the persistent upper extremity impairment (PUPPI) index, which we validated as a predictive tool.ResultsWe included 1653 patients (827 derivation, 826 validation), of whom 803 (48.6%) had persistent arm impairment. The PUPPI index gives 1 point each for age 55 years or older and NIHSS values of worse arm (4), worse leg (>2), facial palsy (3), and total NIHSS (≥10). The optimal cutpoint for the PUPPI index was 3 or greater, at which the area under the curve was greater than 0.75 for the derivation and validation cohorts and when using NIHSS values from either 24 hours or in a subacute or discharge time window. Results were similar across different levels of stroke severity.ConclusionThe PUPPI index uses readily available information to accurately predict persistent upper extremity motor impairment at 90 days poststroke. The PUPPI index can be administered in minutes and could be used as inclusion criterion in recovery-related clinical trials or, with additional development, as a prognostic tool for patients, caregivers, and clinicians.

Introduction: Hyperglycemia has consistently been associated with worse outcome following an acute ischemic stroke (AIS). Recent studies have shown that a stress glucose ratio (SGR) may be a better predictor of critical illness than absolute hyperglycemia. An elevated initial stress glucose ratio (iSGR) was significantly associated with malignant cerebral edema and ICH after thrombectomy. We sought to identify genetic loci related to iSGR in a cohort of the GENISIS (Genetics of Early Neurological InStability after Ischemic Stroke) study. Methods: GENISIS is a multi-site international study that enrolled AIS patients within 6 hours of symptom onset. A sub-cohort with available initial glucose and HbA1c levels was selected. For all patients, Hg38 imputed genotypes were available. iSGR was calculated by dividing initial glucose by the estimated average glucose concentration (= 28.7 * A1c - 46.7) and normalized by log transformation for the GWAS. Association was adjusted by age, sex, baseline NIHSS, principal components and genotyping rounds. Samples were analyzed by country of origin and ethnicity using Plink2 and then meta-analyzed by ethnicity using METAL. Results: Three separate populations were identified (African-Americans n=299; European-Americans n=622; and Spanish n=625). Median age was 71 (IQR 60-80) with 46% female. Baseline NIHSS was 11 (IQR 5-16). A suggestive loci (chr13:rs9560146, p=9.88x10 -8 ) was identified in the meta-analysis. Gene-based analyses suggested that the loci in chromosome 13 is driven by KLF5 (p=0.002). In addition, rs9560146 is also associated with KLF5 gene expression in brain (eQTL p=3.30x10 -3 ; frontal cortex: Braineac). Conclusions: We demonstrated that a variant in KLF5 may be associated with iSGR in a cohort of AIS patients. KLF5 is induced under hypoxia conditions and interacts with HIF-1a to mediate glucose homeostasis. Recently, a pre-clinical study demonstrated that a micro RNA (miR-10b-3p) had neuroprotective effects against ischemia/reperfusion injury by targeting KLF5. Thus, investigating the genetic architecture of stress hyperglycemia may be informative and reveal variants, genes or pathways involved in ischemic brain injury. We plan to recruit a cohort for replication and sample size expansion.

Background and ObjectivesTo examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern–specific ways.MethodsMR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3–6 months after stroke were obtained from the MRI–Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning–based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.ResultsA total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location–specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location.DiscussionHigher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.

Funding: This work was supported by grants from the Emergency Medicine Foundation Career Development Grant; AHA Mentored Clinical & Population Research Award (14CRP18860027); NIH/NINDS-R01-NS085419 (C.C., J.M.L.); NIH/NINDS-R37-NS107230, NIH/NINDS U24-NS107230 (J.M.L.); NIH/NINDS-K23-NS099487 (L.H.); NIH/NIA-K99-AG062723 (L.I.); Barnes-Jewish Hospital Foundation (J.M.L.); Biogen (C.C., J.M.L.); Bright Focus Foundation, US Department of Defense, Helsinki University Central Hospital; Finnish Medical Foundation; Finland government subsidiary funds; Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (grants ‘Registro BASICMAR’ Funding for Research in Health (PI051737), ‘GWALA project’ from Fondos de Investigación Sanitaria ISC III (PI10/02064, PI12/01238 and PI15/00451), JR18/00004); Fondos FEDER/EDRF Red de Investigación Cardiovascular (RD12/0042/0020); Fundació la Marató TV3; Genestroke Consortium (76/C/2011); Recercaixa’13 (JJ086116). Tomás Sobrino (CPII17/00027), Francisco Campos (CPII19/00020) and Israel Fernandez are supported by Miguel Servet II Program from Instituto de Salud Carlos III and Fondos FEDER. I.F. is also supported by Maestro project (PI18/01338) and Pre-test project (PMP15/00022) from Instituto de Salud Carlos III and Fondos Feder, Agaur; and Epigenesis project from Marató TV3 Foundation. J.C., J.M., A.D., J.M.-F., J.A. and I.F. are supported by Invictus plus Network (RD16/0019) from Instituto de Salud Carlos III and Fondos Feder. Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP-2013/07559-3) (I.L.-C.), Sigrid Juselius Foundation. The MEGASTROKE project received funding from sources specified at http://www.megastroke.org/acknowledgments.html. B.S., B.A. and F.S. are supported by NIH awards NS097000, NS101718, NS075035, NS079153 and NS106950. During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6h of stroke onset and NIHSS at 24h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke. Postprint

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Intracranial hemorrhage (ICH) is a common finding in patients presenting to the emergency department with acute neurological symptoms. Noncontrast head computed tomography (NCCT) is the primary modality for assessment and detection of ICH in the acute setting. RAPID ICH software aims to automatically detect ICH on NCCT and was previously shown to have high accuracy when applied to a curated test data set. Here, we measured the test performance characteristics of RAPID ICH software in detecting ICH on NCCT performed in patients undergoing emergency stroke evaluation at a tertiary academic comprehensive stroke center.This retrospective study assessed consecutive patients over a 6-month period who presented with acute neurological symptoms suspicious for stroke and underwent NCCT with RAPID ICH postprocessing. RAPID ICH detection was compared with the interpretation of a reference standard comprising a board-certified or board-eligible neuroradiologist, or in cases of discrepancy, adjudicated by a consensus panel of 3 neuroradiologists. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RAPID ICH for ICH detection were determined.Three hundred seven NCCT scans were included in the study. RAPID ICH correctly identified 34 of 37 cases with ICH and 228 of 270 without ICH. RAPID ICH had a sensitivity of 91.9% (78.1%-98.3%), specificity of 84.4% (79.6%-88.6%), NPV of 98.7% (96.3%-99.6%), PPV of 44.7% (37.6%-52.1%), and overall accuracy of 85.3% (80.9%-89.1%).In a real-world scenario, RAPID ICH software demonstrated high NPV but low PPV for the presence of ICH when evaluating possible stroke patients.

Stroke penumbra injury caused by excess glutamate is an important factor in determining stroke outcome; however, several therapeutic approaches aiming to rescue the penumbra have failed, likely due to unspecific targeting and persistent excitotoxicity, which continued far beyond the primary stroke event. Synaptic lipid signaling can modulate glutamatergic transmission via presynaptic lysophosphatidic acid (LPA) 2 receptors modulated by the LPA-synthesizing molecule autotaxin (ATX) present in astrocytic perisynaptic processes. Here, we detected long-lasting increases in brain ATX concentrations after experimental stroke. In humans, cerebrospinal fluid ATX concentration was increased up to 14 days after stroke. Using astrocyte-specific deletion and pharmacological inhibition of ATX at different time points after experimental stroke, we showed that inhibition of LPA-related cortical excitability improved stroke outcome. In transgenic mice and in individuals expressing a single-nucleotide polymorphism that increased LPA-related glutamatergic transmission, we found dysregulated synaptic LPA signaling and subsequent negative stroke outcome. Moreover, ATX inhibition in the animal model ameliorated stroke outcome, suggesting that this approach might have translational potential for improving the outcome after stroke.

INTRODUCTION: Malignant cerebral edema develops in a small subset of patients with hemispheric strokes, precipitating deterioration and death if decompressive hemicraniectomy (DHC) is not performed in a timely manner. Predicting which stroke patients will develop malignant edema is imprecise based on clinical data alone. Head computed tomography (CT) imaging is often performed at baseline and 24-hours. We determined the incremental value of incorporating imaging-derived features from serial CTs to enhance prediction of malignant edema. METHODS: We identified hemispheric stroke patients at three sites with NIHSS ≥ 7 who had baseline as well as 24-hour clinical and CT-imaging data. We extracted quantitative imaging features from baseline and follow-up CTs, including CSF volume, intracranial reserve (CSF/cranial volume), as well as midline shift (MLS) and infarct-related hypodensity volume. Potentially lethal malignant edema was defined as requiring DHC or dying with MLS over 5-mm. We built machine-learning models using logistic regression first with baseline data and then adding 24-hour data including reduction in CSF volume (ΔCSF). Model performance was evaluated with cross-validation using metrics of recall (sensitivity), precision (predictive value), as well as area under receiver-operating-characteristic and precision-recall curves (AUROC, AUPRC). RESULTS: Twenty of 361 patients (6%) died or underwent DHC. Baseline clinical variables alone had recall of 60% with low precision (7%), AUROC 0.59, AUPRC 0.15. Adding baseline intracranial reserve improved recall to 80% and AUROC to 0.82 but precision remained only 16% (AUPRC 0.28). Incorporating ΔCSF improved AUPRC to 0.53 (AUROC 0.91) while all imaging features further improved prediction (recall 90%, precision 38%, AUROC 0.96, AUPRC 0.66). CONCLUSION: Incorporating quantitative CT-based imaging features from baseline and 24-hour CT enhances identification of patients with malignant edema needing DHC. Further refinements and external validation of such imaging-based machine learning models are required.

OBJECTIVE:To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). PATIENTS AND METHODS:This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission. RESULTS:Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm3) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes. CONCLUSION:Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.

Background and Purpose— Cerebral edema (CED) develops in the hours to days after stroke; the resulting increase in brain volume may lead to midline shift (MLS) and neurological deterioration. The time course and implications of edema formation are not well characterized across the spectrum of stroke. We analyzed displacement of cerebrospinal fluid (ΔCSF) as a dynamic quantitative imaging biomarker of edema formation. Methods— We selected subjects enrolled in a stroke cohort study who presented within 6 hours of onset and had baseline and ≥1 follow-up brain computed tomography scans available. We applied a neural network-based algorithm to quantify hemispheric CSF volume at each imaging time point and modeled CSF trajectory over time (using a piecewise linear mixed-effects model). We evaluated ΔCSF within the first 24 hours as an early biomarker of CED (defined as developing MLS on computed tomography beyond 24 hours) and poor outcome (modified Rankin Scale score, 3–6). Results— We had serial imaging in 738 subjects with stroke, of whom 91 (13%) developed CED with MLS. Age did not differ (69 versus 70 years), but baseline National Institutes of Health Stroke Scale was higher (16 versus 7) and baseline CSF volume lower (132 versus 161 mL, both P P Conclusions— CSF volumetrics provides quantitative evaluation of early edema formation. ΔCSF from baseline to 24-hour computed tomography is a promising early biomarker for the development of MLS and worse neurological outcome.

Malignant cerebral edema is a devastating complication of stroke, resulting in deterioration and death if hemicraniectomy is not performed prior to herniation. Current approaches for predicting this relatively rare complication often require advanced imaging and still suffer from suboptimal performance. We performed a pilot study to evaluate whether neural networks incorporating data extracted from routine computed tomography (CT) imaging could enhance prediction of edema in a large diverse stroke cohort. An automated imaging pipeline retrospectively extracted volumetric data, including cerebrospinal fluid (CSF) volumes and the hemispheric CSF volume ratio, from baseline and 24 h CT scans performed in participants of an international stroke cohort study. Fully connected and long short-term memory (LSTM) neural networks were trained using serial clinical and imaging data to predict those who would require hemicraniectomy or die with midline shift. The performance of these models was tested, in comparison with regression models and the Enhanced Detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score, using cross-validation to construct precision-recall curves. Twenty of 598 patients developed malignant edema (12 required surgery, 8 died). The regression model provided 95% recall but only 32% precision (area under the precision-recall curve [AUPRC] 0.74), similar to the EDEMA score (precision 28%, AUPRC 0.66). The fully connected network did not perform better (precision 33%, AUPRC 0.71), but the LSTM model provided 100% recall and 87% precision (AUPRC 0.97) in the overall cohort and the subgroup with a National Institutes of Health Stroke Scale (NIHSS) score ≥ 8 (p = 0.0001 vs. regression and fully connected models). Features providing the most predictive importance were the hemispheric CSF ratio and NIHSS score measured at 24 h. An LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24 h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients for surgery prior to deterioration.

Background and PurposeThe genetic architecture of cardioembolic stroke (CES) is still poorly understood. Atrial fibrillation (AF) is the main cause of CES, with which it shares heritability. We aimed to discover novel loci associated with CES by performing a Multitrait Analysis of the GWAS (MTAG) with atrial fibrillation genetic data.MethodsFor the MTAG analysis we used the MEGASTROKE cohort, which comprises European patients with CES and controls (n=362,661) and an AF cohort composed of 1,030,836 subjects. Regional genetic pleiotropy of the significant results was explored using an alternative Bayesian approach with GWAS-pairwise method. A replication was performed in an independent European cohort comprising 9,105 subjects using a Genome Wide Association Study (GWAS).ResultsMTAG-CES analysis revealed 40 novel and significant loci (p-value−8) associated with CES, four of which had not previously been associated with AF. A significant replication was assessed for eight novel loci: CAV1, IGF1R, KIAA1755, NEURL1, PRRX1, SYNE2, TEX41 and WIPF1, showing a p-valueKIAA1755, a locus not previously described associated with AF. Interestingly, 51 AF risk loci were not associated with CES according to GWAS-pairwise analysis. Gene Ontology (GO) analysis revealed that these exclusive AF genes from the 51 loci participate in processes related mainly to cardiac development, whereas genes associated with AF and CES participate mainly in muscle contraction and the conduction of electrical impulses.ConclusionsWe found eight new loci associated with CES. In addition, this study provides novel insights into the pathogenesis of CES, highlighting multiple candidate genes for future functional experiments.

ObjectiveTo examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.MethodsMR neuroimaging and National Institutes of Health Stroke Scale data at index stroke, as well as modified Rankin Scale (mRS) at 3-6 months post-stroke were obtained from MRI-GENIE study of acute ischemic stroke (AIS) patients. Individual WMH volume was automatically derived from FLAIR-images. Stroke lesions were automatically segmented from DWI-images, spatially normalized and parcellated into atlas-defined brain regions. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS>2) were modeled within a purpose-built machine learning and Bayesian regression framework. In particular, interaction effects between stroke lesions and a high versus low WMH burden were integrated via hierarchical model structures. Models were adjusted for the covariates age, age2, sex, total DWI-lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.ResultsA total of 928 AIS patients contributed to stroke severity analyses (mean age: 64.8(14.5), 40% women), 698 patients to functional outcome analyses (mean age: 65.9(14.7), 41% women). Individual stroke lesions were represented in five anatomically distinct left-hemispheric and five right-hemispheric lesion patterns. Across all patients, acute stroke severity was substantially explained by three of these patterns, that were particularly focused on bilateral subcortical and left-hemispherically pronounced cortical regions. In high WMH burden patients, two lesion patterns consistently emerged as more pronounced in case of stroke severity: the first pattern was centered on left-hemispheric insular, opercular and inferior frontal regions, while the second pattern combined right-hemispheric temporo-parietal regions. Bilateral subcortical regions were most relevant in explaining long term unfavorable outcome. No WMH-specific lesion patterns of functional outcomes were substantiated. However, a higher overall WMH burden was associated with higher odds of unfavorable outcomes.ConclusionsHigher WMH burden increases stroke severity in case of stroke lesions involving left-hemispheric insular, opercular and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporo-parietal regions (potentially linked to attention). These findings may contribute to augment stroke outcome predictions and motivate a WMH burden and stroke lesion pattern-specific clinical management of AIS patients.

ObjectiveTo determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS).MethodsWe performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS.ResultsWe observed an association between early onset IS and ABO, a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008).ConclusionThe ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.

While chronological age is one of the most influential determinants of post-stroke outcomes, little is known of the impact of neuroimaging-derived biological brain age. We here first examine whether radiomics analysis of the texture of brain T2-FLAIR MRI images can be used to predict brain age in stroke patients. We then assess the clinical determinants of accelerated brain aging and, finally, its impact on post-stroke functional outcomes. Leveraging a multisite cohort of 4,163 ischemic stroke patients, we show that older-appearing patients have more hypertension, diabetes mellitus, prior strokes, and smoking history and are more likely to develop worse post-stroke outcomes than their younger-appearing counterparts. Our results strengthen the importance of preventive medicine for maintaining brain health in stroke patients as they age and suggest a novel methodology to capture previously undescribed prognostic information available on commonly acquired MRI sequences during routine stroke care.

Producción Científica, Stroke is one of the most common causes of death and disability. Reperfusion therapies are the only treatment available during the acute phase of stroke. Due to recent clinical trials, these therapies may increase their frequency of use by extending the time-window administration, which may lead to an increase in complications such as hemorrhagic transformation, with parenchymal hematoma (PH) being the more severe subtype, associated with higher mortality and disability rates. Our aim was to find genetic risk factors associated with PH, as that could provide molecular targets/pathways for their prevention/treatment and study its genetic correlations to find traits sharing genetic background. We performed a GWAS and meta-analysis, following standard quality controls and association analysis (fastGWAS), adjusting age, NIHSS, and principal components. FUMA was used to annotate, prioritize, visualize, and interpret the meta-analysis results. The total number of patients in the meta-analysis was 2034 (216 cases and 1818 controls). We found rs79770152 having a genome-wide significant association (beta 0.09, p-value 3.90 × 10−8) located in the RP11-362K2.2:RP11-767I20.1 gene and a suggestive variant (rs13297983: beta 0.07, p-value 6.10 × 10−8) located in PCSK5 associated with PH occurrence. The genetic correlation showed a shared genetic background of PH with Alzheimer’s disease and white matter hyperintensities. In addition, genes containing the ten most significant associations have been related to aggregated amyloid-β, tau protein, white matter microstructure, inflammation, and matrix metalloproteinases., Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER) - ( Projects PI 11/0176 and PI18/01338), Instituto de Salud Carlos III - (Project CM18/00198), Agencia de Gestión de Ayudas Universitarias y de Investigación (AGAUR) y Fondo Social Europeo - (Grant 2020FI_B1 00157), Instituto de Salud Carlos III y Fondo Europeo de Desarrollo Regional (FEDER) - (Project CD20/00043), Instituto de Salud Carlos III - (Projects FI19/00309, CP12/03298, CPII17/00027, CPII19/00020)

Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke., Acute ischemic stroke impacts men and women differently. Here, the authors show how different lesion patterns in men and women are linked to the extent of stroke severity.

ObjectiveStudies indicate that the functional outcome evolves in the year after ischemic stroke onset. However, the traditional outcome measure in stroke trials is the modified Rankin Scale (mRS) at 90 days from onset. To determine mRS fluctuations in the first year after stroke, we examined data from 3 major stroke trials.MethodsIn a secondary analysis, we evaluated intrapatient mRS between 90 days and 1 year from stroke onset, the mRS shift (∆mRS = 1 year-day 90), and the trials' primary outcome at day 90 and 1 yearResultsWe included 624 patients from the National Institute of Neurological Disorders and Stroke rt-PA Stroke Study, 587 from Albumin Treatment for Acute Ischaemic Stroke, and 611 from Interventional Management of Stroke III, for which the proportion of patients with a ∆mRS change between day 90 and 1 year was 36.5%, 41.7%, and 36.0%. However, the trials' primary outcomes did not differ at 1 year vs 90 days. Similar findings were seen in a second cohort where we pooled the trials and excluded patients with recurrent stroke or death during the follow-up. In those 1,314 patients, 544 (41.4%) had a ∆mRS change, of which 379 (28.9%) had improvement and 165 (12.5%) had worsening, apart from death.ConclusionWe describe the patient-level spectrum of mRS change from day 90 to 1 year after ischemic stroke in 3 high-quality randomized trials. The patient-level shifts consisted of a sufficiently counterbalanced number of mRS improvements and declines, which masked clinical evolution occurring in over one-third of patients. These results may have important implications, both for clinical trial design and outcome adjudication in stroke research and duration of rehabilitative therapy.

The window for acute ischemic stroke treatment was previously limited to 4.5 hours for intravenous tissue plasminogen activator and to 6 hours for thrombectomy. Recent studies using advanced imaging selection expand this window for select patients up to 24 hours from last known well. These studies directly affect emergency stroke management, including prehospital triage and emergency department (ED) management of suspected stroke patients. This narrative review summarizes the data expanding the treatment window for ischemic stroke to 24 hours and discusses these implications on stroke systems of care. It analyzes the implications on prehospital protocols to identify and transfer large-vessel occlusion stroke patients, on issues of distributive justice, and on ED management to provide advanced imaging and access to thrombectomy centers. The creation of high-performing systems of care to manage acute ischemic stroke patients requires academic emergency physician leadership attentive to the rapidly changing science of stroke care.

Rationale: Ischemic stroke is among the leading causes of adult disability. Part of the variability in functional outcome after stroke has been attributed to genetic factors but no locus has been consistently associated with stroke outcome. Objective: Our aim was to identify genetic loci influencing the recovery process using accurate phenotyping to produce the largest GWAS (genome-wide association study) in ischemic stroke recovery to date. Methods and Results: A 12-cohort, 2-phase (discovery-replication and joint) meta-analysis of GWAS included anterior-territory and previously independent ischemic stroke cases. Functional outcome was recorded using 3-month modified Rankin Scale. Analyses were adjusted for confounders such as discharge National Institutes of Health Stroke Scale. A gene-based burden test was performed. The discovery phase (n=1225) was followed by open (n=2482) and stringent joint-analyses (n=1791). Those cohorts with modified Rankin Scale recorded at time points other than 3-month or incomplete data on previous functional status were excluded in the stringent analyses. Novel variants in PATJ (Pals1-associated tight junction) gene were associated with worse functional outcome at 3-month after stroke. The top variant was rs76221407 (G allele, β=0.40, P =1.70×10 −9 ). Conclusions: Our results identify a set of common variants in PATJ gene associated with 3-month functional outcome at genome-wide significance level. Future studies should examine the role of PATJ in stroke recovery and consider stringent phenotyping to enrich the information captured to unveil additional stroke outcome loci.

As swelling occurs, CSF is preferentially displaced from the ischemic hemisphere. The ratio of CSF volume in the stroke-affected hemisphere to that in the contralateral hemisphere may quantify the progression of cerebral edema. We automatically segmented CSF from 1,875 routine CTs performed within 96 hours of stroke onset in 924 participants of a stroke cohort study. In 737 subjects with follow-up imaging beyond 24-hours, edema severity was classified as affecting less than one-third of the hemisphere (CED-1), large hemispheric infarction (LHI, over one-third the hemisphere), without midline shift (CED-2) or with midline shift (CED-3). Malignant edema was LHI resulting in deterioration, requiring osmotic therapy, surgery, or resulting in death. Hemispheric CSF ratio was lower on baseline CT in those with LHI (0.91 vs. 0.97, p

Background: Motor impairment after ischemic stroke is common and has variable recovery that depends on patient factors and stroke severity. An important challenge in rehabilitation research is enrolling patients who may benefit from interventions to improve recovery because they will not recover with standard care. Hypothesis: We can accurately predict persistent upper extremity motor impairment at 90 days after acute ischemic stroke. Methods: The primary outcome was an NIHSS arm domain score of 2-4 at 90 days in patients with a 24-hour NIHSS arm score of 1-4, which we termed persistent arm impairment. With the NINDS tPA trial dataset we used LASSO regression to select baseline demographics and 24-hour NIHSS score domains for a predictive model. We gave one point each for age ≥60 years and 24-hour NIHSS values of worst arm=4, worst leg>2, facial palsy=3, and total NIHSS≥10. The optimal cutpoint for a positive Persistent UPPer extremity Impairment (PUPPI) Score was ≥3 points. We validated the PUPPI score in the ALIAS Part 2, IMS-III, and DEFUSE 3 trials. Results: We included 431, 383, 331, and 71 patients from the NINDS tPA, ALIAS Part 2, IMS-III, and DEFUSE 3 trials. PUPPI was most common in the NINDS tPA trial (62%) and least common in ALIAS (31.3%). The PUPPI Score accurately predicted PUPPI with an area under the receiver operating curve (AUC) of >0.75 for all trials (Table 1). The positive predictive value was 74.6%, 90.9%, 86.1%, and 74.5% in the NINDS tPA, ALIAS Part 2, IMS-III, and DEFUSE 3 trials (Table 1). Conclusion: The PUPPI score uses readily available information to provide accurate prediction of patients who will have persistent upper extremity motor impairment at 90 days from stroke onset.

IntroductionNeuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of describing the texture of conventional images beyond what meets the naked eye, radiomic analyses hold potential for evaluating brain health. We sought to: 1) evaluate this novel approach to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and 2) uncover associations between predictive radiomic features and patients’ clinical phenotypes.MethodsOur analyses were based on a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images and corresponding deep-learning-generated total brain and WMH segmentation. Radiomic features were extracted from normal-appearing brain tissue (brain mask–WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with the most stable selected features predictive of WMH burden and then related this signature to clinical variables (age, sex, hypertension (HTN), atrial fibrillation (AF), diabetes mellitus (DM), coronary artery disease (CAD), and history of smoking) using canonical correlation analysis.ResultsRadiomic features were highly predictive of WMH burden (R2=0.855±0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-valuesCV1-6CV7=.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and DM, CV4 by HTN, CV5 by AF and DM, CV6 by CAD, and CV7 by CAD and DM.ConclusionRadiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes. Further research could evaluate radiomics to predict the progression of WMH.Research in contextEvidence before this studyWe did a systematic review on PubMed until December 1, 2020, for original articles and reviews in which radiomics were used to characterize stroke or cerebrovascular diseases. Radiomic analyses cover a broad ensemble of high-throughput quantification methods applicable to digitalized medical images that extract high-dimensional data by describing a given region of interest by its size, shape, histogram, and relationship between voxels. We used the search terms “radiomics” or “texture analysis”, and “stroke”, “cerebrovascular disease”, “small vessel disease”, or “white matter hyperintensities”. Our research identified 24 studies, 18 studying radiomics of stroke lesions and 6 studying cerebrovascular diseases. All the latter six studies were based on MRI (T1-FLAIR, dynamic contrast-enhanced imaging, T1 & T2-FLAIR, T2-FLAIR post-contrast, T2-FLAIR, and T2-TSE images). Four studies were describing small vessel disease, and two were predicting longitudinal progression of WMH. The average sample size was small with 96 patients included (maximum: 204). One study on 141 patients identified 7 T1-FLAIR radiomic features correlated with cardiovascular risk factors (age and hyperlipidemia) using univariate correlations. All studies were monocentric and performed on a single MRI scanner.Added value of this studyTo date and to the best of our knowledge, this is the largest radiomics study performed on cerebrovascular disease or any topic, and one of the very few to include a great diversity of participating sites with diverse clinical MRI scanners. This study is the first one to establish a radiomic signature of WMH and to interpret its relationship with common cardiovascular risk factors. Our findings add to the body of evidence that damage caused by small vessel disease extend beyond the visible white matter hyperintensities, but the added value resides in the detection of that subvisible damage on routinely acquired T2-FLAIR imaging. It also suggests that cardiovascular phenotypes might manifest in distinct textural patterns detectable on conventional clinical-grade T2-FLAIR images.Implications of all the available evidenceAssessing brain structural integrity has implications for treatment selection, follow-up, prognosis, and recovery prediction in stroke patients but also other neurological disease populations. Measuring cerebral parenchymal structural integrity usually requires advanced imaging such as diffusion tensor imaging or functional MRI. Translation of those neuroimaging biomarkers remains uncommon in clinical practice mainly because of their time-consuming and costly acquisition. Our study provides a potential novel solution to assess brains’ structural integrity applicable to standard, routinely acquired T2-FLAIR imaging.Future research could, for instance, benchmark this radiomics approach against diffusion or functional MRI metrics in the prediction of cognitive or functional outcomes after stroke.

Background and Purpose: Large-scale observational studies of acute ischemic stroke (AIS) promise to reveal mechanisms underlying cerebral ischemia. However, meaningful quantitative phenotypes attainable in large patient populations are needed. We characterize a dynamic metric of AIS instability, defined by change in National Institutes of Health Stroke Scale score (NIHSS) from baseline to 24 hours baseline to 24 hours (NIHSS baseline – NIHSS 24hours = ΔNIHSS 6-24h ), to examine its relevance to AIS mechanisms and long-term outcomes. Methods: Patients with NIHSS prospectively recorded within 6 hours after onset and then 24 hours later were enrolled in the GENISIS study (Genetics of Early Neurological Instability After Ischemic Stroke). Stepwise linear regression determined variables that independently influenced ΔNIHSS 6 –24h . In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS 6–24h was examined. Finally, the association of ΔNIHSS 6 –24h with 90-day favorable outcomes (modified Rankin Scale score 0–2) was assessed. Independent analysis was performed using data from the 2 NINDS-tPA stroke trials (National Institute of Neurological Disorders and Stroke rt-PA). Results: For 2555 patients with AIS, median baseline NIHSS was 9 (interquartile range, 4–16), and median ΔNIHSS 6 –24h was 2 (interquartile range, 0–5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS 6 –24h (R 2 =0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R 2 =0.27), but much of the variance remained unexplained. ΔNIHSS 6 –24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS 3 –24h was similarly associated with 90-day outcomes. Conclusions: The dynamic phenotype, ΔNIHSS 6–24h , captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS 6 –24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.

During the first hours after stroke onset neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between NIH stroke scale (NIHSS) within six hours of stroke onset and NIHSS at 24h (ΔNIHSS). A total of 5,876 individuals from seven countries (Spain, Finland, Poland, United States, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of ΔNIHSS variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture than that of stroke risk. Seven loci (2p25.1, 2q31.2, 2q33.3, 4q34.3, 5q33.2, 6q26 and 7p21.1) were genome-wide significant and explained 2.1% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each loci. eQTL mapping and SMR indicate that ADAM23 (log Bayes Factor (LBF)=6.34) was driving the association for 2q33.3. Gene based analyses suggested that GRIA1 (LBF=5.26), which is predominantly expressed in brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated PARK2 (LBF=5.30) and ABCB5 (LBF=5.70) for the 6q26 and 7p21.1 loci. Human brain single nuclei RNA-seq indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a pre-synaptic protein, and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provides the first evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischemic stroke.RESEARCH INTO CONTEXTEvidence before this studyNo previous genome-wide association studies have investigated the genetic architecture of early outcomes after ischemic stroke.Added Value of this studyThis is the first study that investigated genetic influences on early outcomes after ischemic stroke using a genome-wide approach, revealing seven genome-wide significant loci. A unique aspect of this genetic study is the inclusion of all of the major ethnicities by recruiting from participants throughout the world. Most genetic studies to date have been limited to populations of European ancestry.Implications of all available evidenceThe findings provide the first evidence that genes implicating excitotoxicity contribute to human acute ischemic stroke, and demonstrates proof of principle that GWAS of acute ischemic stroke patients can reveal mechanisms involved in ischemic brain injury.

Acute ischemic stroke affects men and women differently in many ways. In particular, women are oftentimes reported to experience a higher acute stroke severity than men. Here, we derived a low-dimensional representation of anatomical stroke lesions and designed a sex-aware Bayesian hierarchical modelling framework for a large-scale, well phenotyped stroke cohort. This framework was tailored to carefully estimate possible sex differences in lesion patterns explaining acute stroke severity (NIHSS) in 1,058 patients (39% female). Anatomical regions known to subserve motor and language functions emerged as relevant regions for both men and women. Female patients, however, presented a more widespread pattern of stroke severity-relevant lesions than male patients. Furthermore, particularly lesions in the posterior circulation of the left hemisphere underlay a higher stroke severity exclusively in women. These sex-sensitive lesion pattern effects could be discovered and subsequently robustly replicated in two large independent, multisite lesion datasets. The constellation of findings has several important conceptual and clinical implications: 1) suggesting sex-specific functional cerebral asymmetries, and 2) motivating a sex-stratified approach to management of acute ischemic stroke. To go beyond sex-averaged stroke research, future studies should explicitly test whether acute therapies administered on the basis of sex-specific cutoff volumes of salvageable tissue will lead to improved outcomes in women after acute ischemic stroke.

Global outcome measures that are widely used in stroke clinical trials, such as the modified Rankin Scale (mRS), lack sufficient detail to detect changes within specific domains (e.g., sensory, motor, visual, linguistic, or cognitive function). Yet such data are vital for understanding stroke recovery and its mechanisms. Poststroke deficits in specific domains differ in their rate and degree of recovery and in their effects on overall independence and quality of life. For example, even in a patient with complete recovery of strength, persistent deficits in the nonmotor domains such as language and cognition may make a return to independent living impossible. In such cases, global measures based solely on the patient's degree of independence would overlook a complete recovery in the motor domain. Capturing these important aspects of recovery demands a domain-specific approach. If stroke outcomes trials are to incorporate finer-grained recovery metrics—which can require substantial time, effort, and expertise to implement—efficiency must be a priority. In this article, we discuss how commonly collected clinical data from the NIH Stroke Scale can guide the judicious selection of relevant recovery domains for more detailed testing. Our overarching goal is to make the implementation of domain-specific testing more feasible for large-scale clinical trials on stroke recovery.

Introduction: Mechanical thrombectomy (MT) is an important part of acute ischemic stroke (AIS) treatment. Recent trials of MT beyond the 6-hour window have utilized RAPID perfusion imaging for patient selection. The utility of this method is established in patients with large vessel occlusions (LVO) but screening efficiency in real-world practice remains unknown. We present the experience of a single, large volume, Comprehensive Stroke Center (CSC) utilizing RAPID to screen patients for LVO and MT. Methods: We performed a retrospective analysis of prospectively collected consecutive patients who presented to our emergency department (ED) between 01/2018 to 06/2019 with suspected LVO. Protocol was based on 2018 AHA guideline Level IA recommendations and followed DAWN and DEFUSE-3 time and imaging parameters. Patients who underwent RAPID imaging were selected for inclusion. Results: 865 patients met criteria for RAPID perfusion imaging (median age 67, females 52%, outside hospital transfers 29%). Of these, 178 (21% of total) were confirmed to have an LVO (40% ED presentation, 10% inpatient, 50% transfer). For patients presenting to the ED (N=509), 14% had an LVO (median NIHSS 13 [IQR 8-19]), of which 41% underwent MT. Mean CTP core and penumbra volume was 25mL and 100mL respectively. Number needed-to-screen in the ED cohort was 7 to detect LVO and 17 to perform MT. Transfer patients showed no significant difference in LVO detection or MT rates compared to ED patients (56%, p=0.3). Conclusions: In ED-presenting patients at a CSC, the number of RAPID perfusion imaging studies needed to detect an additional case of LVO was 7.1, and to perform an additional MT was 17.4. Current AHA Class IA recommendations for evaluation and treatment of AIS yield a reasonably high rate of LVO detection and subsequent MT in real-world practice. Additional multicenter data will be useful to establish benchmarks and improve screening efficiency.

Introduction: Hemorrhagic transformation (HT) after acute ischemic stroke (AIS) may contribute to neurologic deterioration. The current radiologic classification of HT is qualitative and distinguishes petechial hemorrhagic infarction from parenchymal hematoma (PH-1 and PH-2). However, this grading scheme is subjective and may not accurately reflect the impact of HT on neurological status and outcome. We sought to evaluate whether the volume of hemorrhage was a better marker of deterioration. Methods: We evaluated AIS patients with follow-up CT imaging from a prospective stroke genetics study. HT seen within 36 hours of AI was classified using ECASS criteria. In addition, we outlined all confluent areas of hemorrhage to derive hemorrhage volume (HV). We calculated ΔNIHSS as the difference between baseline and 24-hour NIHSS. Early neurological deterioration (END) was defined as ΔNIHSS of -4 points or more. Association of radiologic HT grade and HV with ΔNIHSS and END were analyzed using linear regression and receiver-operating-curve testing. Results: We analyzed 948 stroke patients with median NIHSS 7 (IQR 4-14), 64% receiving tPA and ΔNIHSS +2 (IQR 0-5). 294 (31%) had HT (146 HI1, 63 HI2, 42 PH1 and 43 PH2). HT was associated with higher baseline NIHSS but not with tPA treatment or ΔNIHSS. END occurred in 113 (12%) including 46 with HT (16%) vs. 67 (10%) without HT (p=0.02). Amongst those with HT, the radiologic grade was not associated with ΔNIHSS or END (20% of PH2, 20% of PH1 vs. 15% of HI1/HI2, p=0.40). However, greater HV was associated with ΔNIHSS (adjusting for baseline NIHSS and tPA, estimate -1.5 point per 10-ml, p=0.0001) and with END (those with END had median HV 7 vs. 3-ml, p=0.001). A cut-off of 12-ml had 45% sensitivity and 90% specificity for END (AUC of 0.72). Conclusion: We demonstrated that while HT was associated with a higher risk of END, the ECASS classification alone did not distinguish those who worsened. It appears that hemorrhage volume may better predict worsening NIHSS and END with moderate sensitivity.

Introduction: Hyperacute MRI (hMRI) increases the number of patients eligible for IV tPA in: (1) patients initially suspected to be stroke mimics (SM) and (2) patients with wake-up or unwitnessed stroke onset (WU-UW). Performing hMRI in a time-frame to enable tPA delivery is challenging for many centers; thus, we evaluated which factors were associated with delays in hMRI and hMRI-related tPA treatment at our institution since publication of the WAKE-UP stroke trial in August 2018. Methods: We analyzed 1-year of prospectively collected hMRI data performed between 07.01.2018 to 06.30.2019. We divided the year into three 4-month epochs; the 1 st epoch was before and the 2 nd and 3 rd epochs were after implementing the Wake-up protocol for WU-UW stroke presentations as a new indication to our streamlined hMRI protocol. We compared baseline variables, hMRI indication, hMRI-related tPA utilization, and time metrics for completing hMRI between the 2 nd and 3 rd epochs. We also evaluated discharge outcomes and safety of tPA treatment in this hMRI cohort. Results: Across the 3 epochs, 84 patients underwent hMRI (n=10 vs. 37 vs. 37, respectively), of whom 13 were treated with IV tPA. hMRI-related tPA utilization increased in epochs 2 vs 3 after initiation of the Wake-Up protocol: 8.1% (epoch 2) vs. 21.6% (epoch 3), and number-needed-to-MRI for one tPA treatment dropped from 12.3 to 4.6. In epochs 2 vs. 3, MRI order-to-scan time decreased (28 vs 23 minutes, P=0.039), indicative of process improvement over time. Across all epochs, hMRI indication of WU-UW (vs. SM) was associated with shorter door-to-hMRI completion (68 vs. 83.5 minutes, P=0.041) and shorter door-to-needle time (76 vs. 118 minutes; P=0.030), whereas age, NIHSS, and sex were not associated with hMRI efficiency. None of the 13 patients treated with IV tPA developed symptomatic ICH and 92% were discharged to home or inpatient rehabilitation. Conclusion: In the final epoch, < 5 MRIs were performed for one tPA treatment, suggesting that a hMRI protocol may improve with time and increased utilization, justifying the use of hMRI to increase patient eligibility for IV tPA. WU-UW stroke indications for hMRI may predict shorter hMRI process and faster treatment times.

[Background and Purpose] Immune cells play a key role in the first 24h poststroke (acute phase), being associated with stroke outcome. We aimed to find genetic risk factors associated with leukocyte counts during the acute phase of stroke., [Methods] Ischemic stroke patients with leukocyte counts data during the first 24h were included. Genome-wide association study and gene expression studies were performed., [Results] Our genome-wide association study, which included 2064 (Discovery) and 407 (Replication) patients, revealed a new locus (14q24.3) associated with leukocyte counts. After Joint analysis (n=2471) 5 more polymorphisms reached genome-wide significance (P, [Conclusions] We have found the first locus associated with leukocyte counts in ischemic stroke, also associated with acute outcome. Genetic analysis of acute endophenotypes could be useful to find the genetic factors associated with stroke outcome. Our findings suggested a different modulation of immune cells in stroke compared with healthy conditions.

Comment inThe yin and yang of magnesium and calcium: New genetic insights for stroke? [Neurology. 2019]; International audience; Objective To determine whether serum magnesium and calcium concentrations are causally associated with ischemic stroke or any of its subtypes using the mendelian randomization approach. Methods Analyses were conducted using summary statistics data for 13 single-nucleotide polymorphisms robustly associated with serum magnesium (n = 6) or serum calcium (n = 7) concentrations. The corresponding data for ischemic stroke were obtained from the MEGASTROKE consortium (34,217 cases and 404,630 noncases). Results In standard mendelian randomization analysis, the odds ratios for each 0.1 mmol/L (about 1 SD) increase in genetically predicted serum magnesium concentrations were 0.78 (95% confidence interval [CI] 0.69-0.89; p = 1.3 × 10 −4) for all ischemic stroke, 0.63 (95% CI 0.50-0.80; p = 1.6 × 10 −4) for cardioembolic stroke, and 0.60 (95% CI 0.44-0.82; p = 0.001) for large artery stroke; there was no association with small vessel stroke (odds ratio 0.90, 95% CI 0.67-1.20; p = 0.46). Only the association with cardioembolic stroke was robust in sensitivity analyses. There was no association of genetically predicted serum calcium concentrations with all ischemic stroke (per 0.5 mg/dL [about 1 SD] increase in serum calcium: odds ratio 1.03, 95% CI 0.88-1.21) or with any subtype. Conclusions This study found that genetically higher serum magnesium concentrations are associated with a reduced risk of cardioembolic stroke but found no significant association of genetically higher serum calcium concentrations with any ischemic stroke subtype.

Background and Purpose— Stroke mimics (SM) challenge the initial assessment of patients presenting with possible acute ischemic stroke (AIS). When SM is considered likely, intravenous tissue-type plasminogen activator (tPA) may be withheld, risking an opportunity to treat AIS. Although computed tomography is routinely used for tPA decision making, magnetic resonance imaging (MRI) may diagnose AIS when SM is favored but not certain. We hypothesized that a hyperacute MRI (hMRI) protocol would identify tPA-eligible AIS patients among those initially favored to have SM. Methods— A streamlined hMRI protocol was designed based on barriers to rapid patient transport, MRI acquisition, and post-MRI tPA delivery. Neurologists were trained to order hMRI when SM was favored and tPA was being withheld. The use of hMRI for tPA decision making, door-to-needle times, and outcomes were compared before hMRI implementation (pre-hMRI: August 1, 2011 to July 31, 2013) and after (post-hMRI, August 1, 2013, to January 15, 2015). Results— Post hMRI, 57 patients with suspected SM underwent hMRI (median MRI-order-to-start time, 29 minutes), of whom, 11 (19%) were diagnosed with AIS and 7 (12%) received tPA. Pre-hMRI, no tPA-treated patients were screened with hMRI. Post hMRI, 7 of 106 (6.6%) tPA-treated patients underwent hMRI to aid in decision making because of suspected SM (0% versus 6.6%; P =0.001). To ensure standard care was maintained after implementing the hMRI protocol, pre- versus post-hMRI tPA-treated cohorts were compared and did not differ: door-to-needle time (39 versus 37 minutes; P =0.63), symptomatic hemorrhage rate (4.5% versus 1.9%; P =0.32), and favorable discharge location (85% versus 89%; P =0.37). Conclusions— A streamlined hMRI protocol permitted tPA administration to a small, but significant, subset of AIS patients initially considered to have SM.

ObjectiveTo validate the Genot-PA score, a clinical-genetic logistic regression score that stratifies the thrombolytic therapy safety, in a new cohort of patients with stroke.MethodsWe enrolled 1,482 recombinant tissue plasminogen activator (rtPA)-treated patients with stroke in Spain and Finland from 2003 to 2016. Cohorts were analyzed on the basis of ethnicity and therapy: Spanish patients treated with IV rtPA within 4.5 hours of onset (cohort A and B) or rtPA in combination with mechanical thrombectomy within 6 hours of onset (cohort C) and Finnish participants treated with IV rtPA within 4.5 hours of onset (cohort D). The Genot-PA score was calculated, and hemorrhagic transformation (HT) and parenchymal hematoma (PH) risks were determined for each score stratum.ResultsGenot-PA score was tested in 1,324 (cohort A, n = 726; B, n = 334; C, n = 54; and D, n = 210) patients who had enough information to complete the score. Of these, 213 (16.1%) participants developed HT and 85 (6.4%) developed PH. In cohorts A, B, and D, HT occurrence was predicted by the score (p = 2.02 × 10−6, p = 0.023, p = 0.033); PH prediction was associated in cohorts A through C (p = 0.012, p = 0.034, p = 5.32 × 10−4). Increased frequency of PH events from the lowest to the highest risk group was found (cohort A 4%–15.7%, cohort B 1.5%–18.2%, cohort C 0%–100%). The best odds ratio for PH prediction in the highest-risk group was obtained in cohort A (odds ratio 5.16, 95% confidence interval 1.46–18.08, p = 0.009).ConclusionThe Genot-PA score predicts HT in patients with stroke treated with IV rtPA. Moreover, in an exploratory study, the score was associated with PH risk in mechanical thrombectomy-treated patients.

Malignant cerebral edema (CED) complicates at least 20 % of large hemispheric infarcts (LHI) and may result in neurological deterioration or death. Midline shift (MLS) is a standard but crude measure of edema severity. We propose that volumetric analysis of shifts in cerebrospinal fluid (CSF) over time provides a reliable means of quantifying the spectrum of edema severity after LHI. We identified 38 patients from 2008 to 2014 with NIHSS ≥8, baseline CT

Background: Target Stroke establishes the goal to administer IV Alteplase within 60 minutes of ED arrival. High-performing centers frequently treat within 45 minutes. Median door-to-needle (DTN) times at our tertiary care academic hospital are consistently < 30 minutes. Monthly case reviews investigate factors associated with DTN times greater than 45 minutes. Methods: Utilizing our stroke registry, patients treated with Alteplase from 2013-2015 were identified. Baseline demographics, medical comorbidities, weekend or after hours (7PM-7AM) presentation, initial NIHSS, initial BP greater than 185/110 and management, posterior circulation symptoms and ED crowding using the National Emergency Department Overcrowding Scale (NEDOCS) were extracted. Arrival date and time of arrival were cross-referenced with NEDOCS. Patients were divided into cohorts of treatment less than 45 minutes vs. greater than 45 minutes. Continuous variables were tested for normal distribution using Shapiro-Wilk, then either an unpaired t test or Wilcoxon’s test was applied to test for significance. Dichotomous variables were tested for significance with Chi-square analysis. Results: A total of 239 patients were included in the analysis. Data is presented in Table 1. After adjusting for multiple comparisons, there was a statistically significant difference in the distribution of baseline NIHSS scores (p=0.0006), diabetes (p=0.0023), and minor strokes (NIHSS less than 3, p=0.0003). Conclusion: Diabetics and patients with minor symptoms are more likely to have longer DTN times. Elevated BP, ED crowding, weekend and after hour arrivals do not significantly delay evaluation and treatment. While not significant after adjusting for multiple tests, both posterior stoke recognition and method of treating BP should be scrutinized as they are modifiable risk factors. Future awareness of discrete patient characteristics may help identify patients at risk for prolonged DTN.DTN.

Introduction: Delays in door-to-needle time (DNT) for tPA administration are associated with worse outcomes after acute ischemic stroke (AIS). Studies suggest tPA is safe and effective in young adults, though the effect of age on timeliness of tPA decision making is unknown. In the young adult population, lower frequency of stroke and higher frequency of stroke mimics may lead to DNT delays. We tested the hypothesis that DNT are longer in young adults with AIS. Methods: From 1/2009 to 3/2016, patient demographics and tPA metrics were prospectively collected on all tPA-treated patients at a large, urban academic hospital. Discharge diagnosis (including stroke mimics) and symptomatic intracranial hemorrhage (sICH) rates were collected by retrospective chart review. DNT was compared between young (age ≤ 45) and older adults (age > 45) and across four age groups: ≤45, 46-65, 66-85, and ≥86. Univariate analysis evaluated associations between DNT and baseline characteristics (age, race, sex, admission year, onset-to-arrival time, and admission NIHSS), followed by forward stepwise linear regression including variables with P Results: Of 560 patients treated with tPA, 63 (11%) were age ≤45 and 497 (89%) were age > 45. Mean DNT was 63 minutes in young adults compared to 50 minutes in older adults (P=0.002). Across four age groups, DNTs were longer in young adults (P=0.027, Figure). In multivariable analysis, age ≤45 (P=0.012), lower NIHSS (P=0.006), and more remote admission year (P=0.001) independently predicted longer DNT. Stroke mimics were more frequent in young adults: 32% vs 7% (P Conclusions: Despite established safety and efficacy of tPA in young adults, we found DNT delays in this population. Further studies are needed to confirm this finding and address age-related disparities in DNT.