| 51. |
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| 52. |
- Van Hoecke, Annelies, et al.
(författare)
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EPHA4 is a disease modifier of amyotrophic lateral sclerosis in animal models and in humans
- 2012
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Ingår i: Nature Medicine. - New York : Nature Publishing Group. - 1078-8956 .- 1546-170X. ; 18:9, s. 1418-
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Tidskriftsartikel (refereegranskat)abstract
- Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting motor neurons. Disease onset and progression are variable, with survival ranging from months to decades. Factors underlying this variability may represent targets for therapeutic intervention. Here, we have screened a zebrafish model of ALS and identified Epha4, a receptor in the ephrin axonal repellent system, as a modifier of the disease phenotype in fish, rodents and humans. Genetic as well as pharmacological inhibition of Epha4 signaling rescues the mutant SOD1 phenotype in zebrafish and increases survival in mouse and rat models of ALS. Motor neurons that are most vulnerable to degeneration in ALS express higher levels of Epha4, and neuromuscular re-innervation by axotomized motor neurons is inhibited by the presence of Epha4. In humans with ALS, EPHA4 expression inversely correlates with disease onset and survival, and loss-of-function mutations in EPHA4 are associated with long survival. Furthermore, we found that knockdown of Epha4 also rescues the axonopathy induced by expression of mutant TAR DNA-binding protein 43 (TDP-43), another protein causing familial ALS, and the axonopathy induced by knockdown of survival of motor neuron 1, a model for spinomuscular atrophy. This suggests that Epha4 generically modulates the vulnerability of (motor) neurons to axonal degeneration and may represent a new target for therapeutic intervention.
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| 53. |
- van Meel, Evelien R., et al.
(författare)
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Early-life respiratory tract infections and the risk of school-age lower lung function and asthma: a meta-analysis of 150 000 European children
- 2022
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Ingår i: European Respiratory Journal. - : EUROPEAN RESPIRATORY SOC JOURNALS LTD. - 0903-1936 .- 1399-3003. ; 60:4
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Tidskriftsartikel (refereegranskat)abstract
- Background Early-life respiratory tract infections might affect chronic obstructive respiratory diseases, but conclusive studies from general populations are lacking. Our objective was to examine if children with early-life respiratory tract infections had increased risks of lower lung function and asthma at school age. Methods We used individual participant data of 150 090 children primarily from the EU Child Cohort Network to examine the associations of upper and lower respiratory tract infections from age 6 months to 5 years with forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, forced expiratory flow at 75% of FVC (FEF75%) and asthma at a median (range) age of 7 (4-15) years. Results Children with early-life lower, not upper, respiratory tract infections had a lower school-age FEV1, FEV1/FVC and FEF75% (z-score range: -0.09 (95% CI -0.14- -0.04) to -0.30 (95% CI -0.36- -0.24)). Children with early-life lower respiratory tract infections had a higher increased risk of school-age asthma than those with upper respiratory tract infections (OR range: 2.10 (95% CI 1.98-2.22) to 6.30 (95% CI 5.64-7.04) and 1.25 (95% CI 1.18-1.32) to 1.55 (95% CI 1.47-1.65), respectively). Adjustment for preceding respiratory tract infections slightly decreased the strength of the effects. Observed associations were similar for those with and without early-life wheezing as a proxy for early-life asthma. Conclusions Our findings suggest that early-life respiratory tract infections affect development of chronic obstructive respiratory diseases in later life, with the strongest effects for lower respiratory tract infections.
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| 54. |
- Wiedmann, Silke, et al.
(författare)
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Variations in Quality Indicators of Acute Stroke Care in 6 European Countries The European Implementation Score (EIS) Collaboration
- 2012
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Ingår i: Stroke. - Philadelphia : Lippincott Williams & Wilkins. - 0039-2499 .- 1524-4628. ; 43:2, s. 458-463
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Tidskriftsartikel (refereegranskat)abstract
- Background and Purpose-Quality indicators serve as standards of care by which performance of individual hospitals is measured. Although several audits for monitoring quality of stroke care have been established in Europe, there is currently no consensus on quality indicators for acute stroke care or for methodology for collecting information on these measures. Methods-An up-to-date inventory on European stroke audits in place in 2006 was performed in the course of a project funded by the European Union (European Implementation Score Collaboration [EIS]). Two regional (Flanders, Belgium; Catalonia, Spain) and 4 national (Germany, Scotland, Sweden, England/Wales/Northern Ireland) stroke audits took part. Between November 2009 and July 2010, 2 standardized surveys and a series of interviews were performed to determine characteristics, methods, and content of these quality initiatives. For quality purposes, all summarized information was validated by representatives of the respective audits. Results-Overall, 123 quality indicators (91 process, 24 outcome, and 8 structural indicators) were identified. Anticoagulants in patients with atrial fibrillation and brain imaging were the only quality indicators used in all, whereas another 13 indicators were used in at least 2 of the quality initiatives. Substantial variations were found across the audits in terms of the development process of quality indicators, inclusion criteria, participation, population coverage, data documentation, follow-ups, benchmarking, and feedback of results to participants. Conclusions-There is a huge variety in measuring performance of acute stroke care in Europe, hampering valid comparisons of acute stroke care. Common standards for defining quality indicators and collecting information required for these measures should be defined in Europe. (Stroke. 2012;43:458-463.)
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| 55. |
- Wouters, Anke, et al.
(författare)
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Association between the perfusion/diffusion and diffusion/FLAIR mismatch: data from the AXIS2 trial.
- 2015
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Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : SAGE Publications. - 1559-7016 .- 0271-678X. ; 35:10, s. 1681-1686
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Tidskriftsartikel (refereegranskat)abstract
- The perfusion-/diffusion-weighted imaging (PWI/DWI) mismatch and the diffusion/fluid attenuated inversion recovery (DWI/FLAIR) mismatch are magnetic resonance imaging (MRI) markers of evolving brain ischemia. We examined whether the DWI/FLAIR mismatch was independently associated with the PWI/DWI mismatch. Furthermore, we determined whether the presence of the DWI/FLAIR mismatch in patients with the PWI/DWI mismatch would provide additional information regarding last seen normal time (LTM). We used data from the 'AX200 for ischemic stroke' trial (AXIS 2 study NCT00927836). We studied the association between the presence of the DWI/FLAIR and PWI/DWI mismatch, baseline National Institute of Health Stroke Scale (NIHSS), age, ischemic-core volume, gender, intravenous (IV) tissue plasminogen activator (tPA), and perfusion-mismatch volume in univariate analysis. Significant variables (P<0.05) were added into the final multivariate model. We analyzed 197 patients. Seventy-two (37%) had both the PWI/DWI and the DWI/FLAIR mismatch. Patients with the double mismatch pattern had a shorter LTM than patients with the PWI/DWI mismatch alone (Median difference 90 minutes, P<0.01). Multivariate analysis confirmed the independent association between the two mismatch patterns (odds ratio (OR) 2.6, 95% confidence interval (CI) 1.2 to 5.4). Our study implies that the DWI/FLAIR mismatch and PWI/DWI mismatch are strongly associated, independent from LTM. Furthermore, in the presence of the PWI/DWI mismatch, the DWI/FLAIR pattern indicates a shorter LTM. This could have implications in selecting patients for reperfusion therapy.Journal of Cerebral Blood Flow & Metabolism advance online publication, 3 June 2015; doi:10.1038/jcbfm.2015.108.
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| 56. |
- 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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| 57. |
- Wouters, Anke, et al.
(författare)
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Multimodal magnetic resonance imaging to identify stroke onset within 6 h in patients with large vessel occlusions
- 2018
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Ingår i: European Stroke Journal. - : SAGE Publications. - 2396-9873 .- 2396-9881. ; 3:2, s. 185-192
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods: A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results: We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79–0.96). In the validation cohort (N = 90), the area under the curve was 0.73 (P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69–0.95). Discussion: After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. Conclusion: In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.
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| 58. |
- 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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| 59. |
- 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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| 60. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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