| 1. |
- Ay, Hakan, et al.
(författare)
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Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network
- 2014
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Ingår i: Stroke. - 0039-2499. ; 45:12, s. 3589-3596
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.
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| 2. |
- Van De Munckhof, Anita, et al.
(författare)
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Outcomes of cerebral venous thrombosis due to vaccine-induced immune thrombotic thrombocytopenia after the acute phase
- 2022
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Ingår i: Stroke. - : American Heart Association. - 0039-2499 .- 1524-4628. ; 53:10, s. 3206-3210
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Tidskriftsartikel (refereegranskat)abstract
- Background: Cerebral venous thrombosis (CVT) due to vaccine-induced immune thrombotic thrombocytopenia (VITT) is a severe condition, with high in-hospital mortality rates. Here, we report clinical outcomes of patients with CVT-VITT after SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) vaccination who survived initial hospitalization.Methods: We used data from an international registry of patients who developed CVT within 28 days of SARS-CoV-2 vaccination, collected until February 10, 2022. VITT diagnosis was classified based on the Pavord criteria. Outcomes were mortality, functional independence (modified Rankin Scale score 0-2), VITT relapse, new thrombosis, and bleeding events (all after discharge from initial hospitalization).Results: Of 107 CVT-VITT cases, 43 (40%) died during initial hospitalization. Of the remaining 64 patients, follow-up data were available for 60 (94%) patients (37 definite VITT, 9 probable VITT, and 14 possible VITT). Median age was 40 years and 45/60 (75%) patients were women. Median follow-up time was 150 days (interquartile range, 94-194). Two patients died during follow-up (3% [95% CI, 1%-11%). Functional independence was achieved by 53/60 (88% [95% CI, 78%-94%]) patients. No new venous or arterial thrombotic events were reported. One patient developed a major bleeding during follow-up (fatal intracerebral bleed).Conclusions: In contrast to the high mortality of CVT-VITT in the acute phase, mortality among patients who survived the initial hospitalization was low, new thrombotic events did not occur, and bleeding events were rare. Approximately 9 out of 10 CVT-VITT patients who survived the acute phase were functionally independent at follow-up.
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| 3. |
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| 4. |
- Bu, Ning, et al.
(författare)
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Imaging Markers of Brain Frailty and Outcome in Patients With Acute Ischemic Stroke
- 2021
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Ingår i: Stroke. - 1524-4628. ; 52:3, s. 1004-1011
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: Functional outcome after stroke may be related to preexisting brain health. Several imaging markers of brain frailty have been described including brain atrophy and markers of small vessel disease. We investigated the association of these imaging markers with functional outcome after acute ischemic stroke. METHODS: We retrospectively studied patients with acute ischemic stroke enrolled in the AXIS-2 trial (AX200 in Ischemic Stroke Trial), a randomized controlled clinical trial of granulocyte colony-stimulating factor versus placebo. We assessed the ratio of brain parenchymal volume to total intracerebral volumes (ie, the brain parenchymal fraction) and total brain volumes from routine baseline magnetic resonance imaging data obtained within 9 hours of symptom onset using the unified segmentation algorithm in SPM12. Enlarged perivascular spaces, white matter hyperintensities, lacunes, as well as a small vessel disease burden, were rated visually. Functional outcomes (modified Rankin Scale score) at day 90 were determined. Logistic regression was used to test associations between brain imaging features and functional outcomes. RESULTS: We enrolled 259 patients with a mean age of 69±12 years and 46 % were female. Increased brain parenchymal fraction was associated with higher odds of excellent outcome (odds ratio per percent increase, 1.078 [95% CI, 1.008-1.153]). Total brain volumes and small vessel disease burden were not associated with functional outcome. An interaction between brain parenchymal fraction and large vessel occlusion on excellent outcome was not observed. CONCLUSIONS: Global brain health, as assessed by brain parenchymal fraction on magnetic resonance imaging, is associated with excellent functional outcome after ischemic stroke. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00927836.
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| 5. |
- Gill, Dipender, et al.
(författare)
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Genetically Determined Risk of Depression and Functional Outcome After Ischemic Stroke
- 2019
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Ingår i: Stroke. - 1524-4628. ; 50:8, s. 2219-2222
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- Psychosocial factors can have implications for ischemic stroke risk and recovery. This study investigated the effect of genetically determined risk of depression on these outcomes using the Mendelian randomization (MR) framework. Methods- Genetic instruments for risk of depression were identified in a discovery genome-wide association study of 246 363 cases and 561 190 controls and further replicated in a separate population of 474 574 cases and 1 032 579 controls. Corresponding genetic association estimates for risk of ischemic stroke were taken from 60 341 cases and 454 450 controls, with those for functional outcome 3 months after ischemic stroke taken from an analysis of 6021 patients. Following statistical power calculation, inverse-variance weighted MR was performed to pool estimates across different instruments. The Cochran Q heterogeneity test, weighted median MR, and MR pleiotropy residual sum and outlier were used to explore possible bias relating to inclusion of pleiotropic variants. Results- There was no MR evidence for an effect of genetically determined risk of depression on ischemic stroke risk. Although suffering low statistical power, the main inverse-variance weighted MR analysis was suggestive of a detrimental effect of genetically determined risk of depression on functional outcome after ischemic stroke (odds ratio of poor outcome [modified Rankin Scale, ≥3] per 1-SD increase in genetically determined risk of depression, 1.81; 95% CI, 0.98-3.35; P=0.06). There was no evidence of heterogeneity between MR estimates produced by different instruments (Q P=0.26). Comparable MR estimates were obtained with weighted median MR (odds ratio, 2.57; 95% CI, 1.05-6.25; P=0.04) and MR pleiotropy residual sum and outlier (odds ratio, 1.81; 95% CI, 0.95-3.46; P=0.08). Conclusions- We found no MR evidence of genetically determined risk of depression affecting ischemic stroke risk but did find consistent MR evidence suggestive of a possible effect on functional outcome after ischemic stroke. Given the widespread prevalence of depression-related morbidity, these findings could have implications for prognostication and personalized rehabilitation after stroke.
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| 6. |
- Lemmens, Robin, et al.
(författare)
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The association of the 4q25 susceptibility variant for atrial fibrillation with stroke is limited to stroke of cardioembolic etiology.
- 2010
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Ingår i: Stroke; a journal of cerebral circulation. - 1524-4628. ; 41:9, s. 1850-7
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: Genome-wide association studies recently identified 2 variants on chromosome 4q25 as susceptibility factors for atrial fibrillation. Interestingly, these variants were subsequently also shown to be associated with stroke. However, it remains unclear whether 4q25 associates with all the stroke subtypes or with cardioembolic stroke in particular, which is often attributable to atrial fibrillation. METHODS: We performed a large case-control association study in 4199 ischemic stroke patients, all subtyped according to Trial of Org 10172 in Acute Stroke Treatment criteria, and 3750 controls derived from 6 studies conducted in Australia, Austria, Belgium, Poland, Spain, and Sweden. Two variants on chromosome 4q25, rs1906591 and rs10033464, were genotyped. RESULTS: Within cases, the A-allele of rs1906591 was associated with atrial fibrillation (odds ratio, 1.64 [95% CI, 1.43 to 1.90]; P=9.2 . 10(-12)), whereas rs10033464 was only marginally associated. There was an association between overall ischemic stroke and rs1906591 (odds ratio, 1.20 [95% CI, 1.09 to 1.32]; P=1.2 . 10(-4)). However, this was probably caused by the large effect of stroke of cardioembolic etiology because no relation was obtained in any other subgroup of stroke. The rs10033464 variant failed to show any relationship with ischemic stroke. CONCLUSIONS: We replicated the association of the rs1906591 variant on chromosome 4q25 with atrial fibrillation and ischemic stroke of cardioembolic etiology. The 4q25 locus failed to associate with noncardiac subtypes of ischemic stroke.
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| 7. |
- Pfeiffer, Dorothea, et al.
(författare)
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Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke
- 2019
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Ingår i: Stroke. - 1524-4628. ; 50:2, s. 298-304
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- We sought to explore the effect of genetic imbalance on functional outcome after ischemic stroke (IS). Methods- Copy number variation was identified in high-density single-nucleotide polymorphism microarray data of IS patients from the CADISP (Cervical Artery Dissection and Ischemic Stroke Patients) and SiGN (Stroke Genetics Network)/GISCOME (Genetics of Ischaemic Stroke Functional Outcome) networks. Genetic imbalance, defined as total number of protein-coding genes affected by copy number variations in an individual, was compared between patients with favorable (modified Rankin Scale score of 0-2) and unfavorable (modified Rankin Scale score of ≥3) outcome after 3 months. Subgroup analyses were confined to patients with imbalance affecting ohnologs-a class of dose-sensitive genes, or to those with imbalance not affecting ohnologs. The association of imbalance with outcome was analyzed by logistic regression analysis, adjusted for age, sex, stroke subtype, stroke severity, and ancestry. Results- The study sample comprised 816 CADISP patients (age 44.2±10.3 years) and 2498 SiGN/GISCOME patients (age 67.7±14.2 years). Outcome was unfavorable in 122 CADISP and 889 SiGN/GISCOME patients. Multivariate logistic regression analysis revealed that increased genetic imbalance was associated with less favorable outcome in both samples (CADISP: P=0.0007; odds ratio=0.89; 95% CI, 0.82-0.95 and SiGN/GISCOME: P=0.0036; odds ratio=0.94; 95% CI, 0.91-0.98). The association was independent of age, sex, stroke severity on admission, stroke subtype, and ancestry. On subgroup analysis, imbalance affecting ohnologs was associated with outcome (CADISP: odds ratio=0.88; 95% CI, 0.80-0.95 and SiGN/GISCOME: odds ratio=0.93; 95% CI, 0.89-0.98) whereas imbalance without ohnologs lacked such an association. Conclusions- Increased genetic imbalance was associated with poorer functional outcome after IS in both study populations. Subgroup analysis revealed that this association was driven by presence of ohnologs in the respective copy number variations, suggesting a causal role of the deleterious effects of genetic imbalance.
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| 8. |
- Wouters, Anke, et al.
(författare)
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Association Between Time From Stroke Onset and Fluid-Attenuated Inversion Recovery Lesion Intensity Is Modified by Status of Collateral Circulation.
- 2016
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Ingår i: Stroke: a journal of cerebral circulation. - 1524-4628. ; 47, s. 1018-1018
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE:In patients with acute stroke, the intensity of a fluid-attenuated inversion recovery (FLAIR) lesion in the region of diffusion restriction is associated with time from symptom onset. We hypothesized that collateral status as assessed by the hypoperfusion intensity ratio could modify the association between time from stroke onset and FLAIR lesion intensity.METHODS:From the AX200 for ischemic stroke trial, 141 patients had appropriate FLAIR, diffusion-weighted imaging, and perfusion-weighted imaging. In the region of nonreperfused core, we calculated voxel-based relative FLAIR (rFLAIR) signal intensity. The hypoperfusion intensity ratio was defined as the ratio of the Tmax >10 s lesion over the Tmax >6 s lesion volume. A hypoperfusion intensity ratio threshold of ≤0.4 was used to dichotomize good versus poor collaterals. We studied the interaction between collateral status on the association between time from symptom onset and FLAIR intensity.RESULTS:Time from symptom onset was associated with the rFLAIR intensity in the region of nonreperfused core (B=1.05; 95% confidence interval, 1.0-1.1). We identified an interaction between this association and collateral status; an association was present between time and rFLAIR intensity in patients with poor collaterals (r=0.53), but absent in patients with good collaterals (r=0.17; P=0.04).CONCLUSIONS:Our findings show that the relationship between time from symptom onset and rFLAIR lesion intensity depends on collateral status. In patients with good collaterals, the development of an rFLAIR-positive lesion is less dependent on time from symptom onset compared with patients with poor collaterals.
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| 9. |
- Wouters, Anke, et al.
(författare)
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Prediction of Stroke Onset is Improved by Relative Fluid-Attenuated Inversion Recovery and Perfusion Imaging Compared to the Visual Diffusion-Weighted Imaging/Fluid-Attenuated Inversion Recovery Mismatch
- 2016
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Ingår i: Stroke: a journal of cerebral circulation. - 0039-2499. ; 47:10, s. 2559-2564
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose - Acute stroke patients with unknown time of symptom onset are ineligible for thrombolysis. The diffusion-weighted imaging and fluid-attenuated inversion recovery (FLAIR) mismatch is a reasonable predictor of stroke within 4.5 hours of symptom onset, and its clinical usefulness in selecting patients for thrombolysis is currently being investigated. The accuracy of the visual mismatch rating is moderate, and we hypothesized that the predictive value of stroke onset within 4.5 hours could be improved by including various clinical and imaging parameters. Methods - In this study, 141 patients in whom magnetic resonance imaging was obtained within 9 hours after symptom onset were included. Relative FLAIR signal intensity was calculated in the region of nonreperfused core. Mean T max was calculated in the total region with T max >6 s. Mean relative FLAIR, mean T max, lesion volume with T max >6 s, age, site of arterial stenosis, core volume, and location of infarct were analyzed by logistic regression to predict stroke onset time before or after 4.5 hours. Results - Receiver-operating characteristic curve analysis revealed an area under the curve of 0.68 (95% confidence interval 0.59-0.78) for the visual diffusion-weighted imaging/FLAIR mismatch, thereby correctly classifying 69% of patients with an onset time before or after 4.5 hours. Age, relative FLAIR, and T max increased the accuracy significantly (P<0.01) to an area under the curve of 0.82 (95% confidence interval 0.74-0.89). This new predictive model correctly categorized 77% of patients according to stroke onset before versus after 4.5 hours. Conclusions - In patients with unknown stroke onset, the accuracy of predicting time from symptom onset within 4.5 hours is improved by obtaining relative FLAIR and perfusion imaging.
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| 10. |
- Wu, Ona, et al.
(författare)
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Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data
- 2019
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Ingår i: Stroke. - 1524-4628. ; 50:7, s. 1734-1741
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm3 (0.9-16.6 cm3). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.
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