| 1. |
- Abzhandadze, Tamar, 1980, et al.
(author)
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LIFE SATISFACTION IN SPOUSES OF STROKE SURVIVORS AND CONTROL SUBJECTS: A 7-YEAR FOLLOW-UP OF PARTICIPANTS IN THE SAHLGRENSKA ACADEMY STUDY ON ISCHAEMIC STROKE
- 2017
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In: Journal of Rehabilitation Medicine. - : Medical Journals Sweden AB. - 1650-1977. ; 49:7, s. 550-557
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Journal article (peer-reviewed)abstract
- Objective: To investigate life satisfaction in spouses of middle-aged stroke survivors from the long-term perspective and to identify factors that explain their life satisfaction. Subjects: Cohabitant spouses of survivors of ischaemic stroke aged < 70 years at stroke onset (n = 248) and spouses of controls (n = 246). Methods: Assessments were made 7 years after inclusion to the study. Spouses' life satisfaction was assessed with the Fugl-Meyer's Life Satisfaction Check-List (LiSAT 11). Stroke-related factors were examined with the National Institutes of Health stroke scale, Mini-Mental State Examination, Barthel Index and modified Rankin Scale. Results: Spouses of stroke survivors had significantly lower satisfaction with general life, leisure, sexual life, partner relationship, family life, and poorer somatic and psychological health than spouses of controls. Caregiving spouses had significantly lower scores on all life domains except vocation and own activities of daily living than non-caregiving spouses. Spouses' satisfaction on different life domains was explained mainly by their age, sex, support given to the partner, and the survivor's level of global disability, to which both physical and cognitive impairments contributed. Conclusion: Seven years after stroke, spouses of stroke survivors reported lower life satisfaction compared with spouses of controls. Life satisfaction in stroke survivors' spouses was associated with spouses' age, sex, giving support, and the stroke survivors' level of global disability.
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| 2. |
- Blomgren, Charlotte, et al.
(author)
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Long-term performance of instrumental activities of daily living (IADL) in young and middle-aged stroke survivors: Results from SAHLSIS outcome
- 2018
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In: Scandinavian Journal of Occupational Therapy. - : Informa UK Limited. - 1103-8128 .- 1651-2014. ; 25:2, s. 119-126
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Journal article (peer-reviewed)abstract
- Background: Although stroke prevalence is increasing and large proportions of stroke survivors are expected to live many years after stroke onset, research on the long-term consequences of stroke for instrumental activities of daily living (IADL) is limited. Aim: To explore performance of IADL seven years post-stroke onset and identify predictors of long-term IADL performance based on commonly employed acute measures and demographic characteristics in young and middle-aged stroke survivors. Methods: Data on stroke survivors were collected from SAHLSIS. IADL performance was assessed at 7 years using the Frenchay Activities Index (FAI). Demographic data and baseline measures were assessed as predictors of FAI outcome, using logistic regression. Results: 237 stroke survivors with a median age of 63 at follow-up were included. Participants had predominantly suffered a mild stroke and > 90% lived at home with no community services. Mean FAI was 25.7(score range 0-45), indicating reduced levels of participation in IADL. Frequency of performance of IADL was lowest for work/leisure activities. Gender, cohabitation status, initial stroke severity and baseline score on mRS were independently associated with IADL outcome. Conclusions: Reduced levels of participation in IADL persist many years after stroke onset and indicate a need to adapt a long-term perspective on stroke rehabilitation.
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| 3. |
- Giese, A. K., et al.
(author)
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Design and rationale for examining neuroimaging genetics in ischemic stroke The MRI-GENIE study
- 2017
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In: Neurology-Genetics. - : Ovid Technologies (Wolters Kluwer Health). - 2376-7839. ; 3:5
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Journal article (peer-reviewed)abstract
- Objective: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI-GENetics Interface Exploration (MRI-GENIE) study.& para;& para;Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.& para;& para;Conclusions: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
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| 4. |
- Giese, Anne Katrin, et al.
(author)
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Design and rationale for examining neuroimaging genetics in ischemic stroke : The MRI-GENIE study
- 2017
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In: Neurology: Genetics. - 2376-7839. ; 3:5
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Journal article (peer-reviewed)abstract
- Objective: To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI-GENetics Interface Exploration (MRI-GENIE) study. Methods: MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributedMRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include themanual and automated assessments of established MRI markers. A high-throughputMRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.Conclusions: The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.
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| 5. |
- Holmegaard, Lukas, et al.
(author)
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Long-term progression of white matter hyperintensities in ischemic stroke
- 2018
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In: Acta Neurologica Scandinavica. - : Hindawi Limited. - 0001-6314. ; 138:6, s. 548-556
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Journal article (peer-reviewed)abstract
- Objectives Studies on long-term progression of white matter hyperintensities (WMH) after ischemic stroke are scarce. Here, we sought to investigate this progression and its predictors in a cohort presenting with ischemic stroke before 70 years of age. Materials and methods Participants in the Sahlgrenska Academy Study on Ischemic Stroke who underwent magnetic resonance imaging (MRI) of the brain at index stroke were examined by MRI again after 7 years (n = 188, mean age 53 years at index stroke, 35% females). WMH at index stroke and progression were assessed according to Fazekas' grades and the WMH change scale. Stroke subtype was classified according to TOAST. Results Marked WMH at index stroke were present in 20% of the participants and were significantly associated with age, hypertension, and subtype. Progression of WMH after 7 years was observed in 63% and 35% of the participants for subcortical and periventricular locations, respectively. Significant independent predictors of progression were age and marked WMH at baseline for both locations, whereas no significant associations were detected for vascular risk factors or subtype in multivariable analyses. In participants with no or only mild WMH at baseline, 20% showed marked WMH at follow-up. Age and hypertension, but not subtype, were independently associated with this acquisition of marked WMH. Conclusions Age and marked WMH at index stroke, but not stroke subtype, predicted long-term WMH progression after ischemic stroke before 70 years of age, whereas age and hypertension predicted acquisition of marked WMH in those with no or only mild WMH at baseline.
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| 6. |
- Pedersen, Annie, 1981, et al.
(author)
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Circulating neurofilament light in ischemic stroke: temporal profile and outcome prediction
- 2019
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In: Journal of Neurology. - : Springer Science and Business Media LLC. - 0340-5354 .- 1432-1459. ; 266:11, s. 2796-2806
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Journal article (peer-reviewed)abstract
- Background and purpose Neurofilament light chain (NfL) is a marker of neuroaxonal damage. We aimed to study associations between serum NfL (sNfL) concentrations at different time points after ischemic stroke and outcomes. Methods We prospectively included ischemic stroke cases (n=595, mean age 59 years, 64% males) and assessed outcomes by both the modified Rankin Scale (mRS) and the NIH stroke scale (NIHSS) at 3 months and by mRS at 2 years. In a subsample, long-term (7-year) outcomes were also assessed by both mRS and NIHSS. We used the ultrasensitive single-molecule array assay to measure sNfL in the acute phase (range 1–14, median 4 days), after 3 months and 7 years in cases and once in controls (n=595). Results Acute-phase sNfL increased by the time to blood-draw and highest concentrations were observed at 3 months post-stroke. High sNfL associated to stroke severity and poor outcomes, and both associations were strongest for 3-month sNfL. After adjusting for age, previous stroke, stroke severity, and day of blood draw, 3-month sNfL was significantly associated to both outcomes at all time points (p<0.01 throughout). For all main etiological subtypes, both acute phase and 3-month sNfL were significantly higher than in controls, but the dynamics of sNfL differed by stroke subtype. Conclusions The results from this study inform on sNfL in ischemic stroke and subtypes over time, and show that sNfL predicts short- and long-term neurological and functional outcomes. Our findings suggest a potential utility of sNfL in ischemic stroke outcome prediction.
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| 7. |
- Persson, Josefine, 1981, et al.
(author)
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Long- term cost of spouses’ informal support for dependent midlife stroke survivors
- 2017
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In: Brain and Behavior. - : Wiley. - 2162-3279. ; 7:6
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Journal article (peer-reviewed)abstract
- Objectives: Stroke is a major global disease that requires extensive care and support from society and relatives. The aim of this study was to identify and quantify the long- term informal support and to estimate the annual cost of informal support provided by spouses to their stroke surviving partner. Method: Data were based on the 7- year follow- up of the Sahlgrenska Academy Study on Ischemic Stroke. One- third of the spouses stated that they provided support to their stroke surviving partner. The magnitude of the support was assessed with a study- specific time- diary and was estimated for independent and dependent stroke survivors based on the scores of the modified Rankin Scale. To deal with skewed data, a two- part econometric model was used to estimate the annual cost of informal support. Result: Cohabitant dyads of 221 stroke survivors aged <70 at stroke onset were in- cluded in the study. Spouses of independent stroke survivors ( n = 188) provided on average 0.15 hr/day of practical support and 0.48 hr/day of being available. Corresponding figures for spouses of dependent stroke survivors ( n = 33) were 5.00 regarding practical support and 9.51 regarding being available. The mean annual cost of informal support provided for independent stroke survivors was estimated at €991 and €25,127 for dependent stroke survivor. Conclusion: The opportunity cost of informal support provided to dependent midlife stroke survivors is of a major magnitude many years after stroke onset and should be considered in economic evaluations of health care.
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| 8. |
- Persson, Josefine, 1981, et al.
(author)
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Long-term QALY-weights among spouses of dependent and independent midlife stroke survivors.
- 2017
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In: Quality of Life Research. - : Springer Science and Business Media LLC. - 0962-9343 .- 1573-2649. ; 26:11, s. 3059-3068
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Journal article (peer-reviewed)abstract
- PURPOSE: The aim of this study was to investigate whether the dependency of midlife stroke survivors had any long-term impact on their spouses' QALY-weights. METHOD: Data on stroke survivors, controls, and spouses were collected from the 7-year follow-up of the Sahlgrenska Academy Study on Ischemic Stroke. Health-related quality of life was assessed by the SF-36, and the preference-based health state values were assessed with the SF-6D. Spouses of dependent and independent stroke survivors were categorized according to their scores on the modified Rankin Scale. An ordinary least squares regression analysis was used to evaluate whether the dependency of the stroke survivors had any impact on the spouses' QALY-weights. RESULT: Cohabitant dyads of 247 stroke survivors aged <70 at stroke onset and 245 dyads of controls were included in the study. Spouses of dependent stroke survivors (n = 50) reported a significant lower mean QALY-weight of 0.69 in comparison to spouses of independent stroke survivors (n = 197) and spouses of controls, (n = 245) who both reported a mean QALY-weight of 0.77. The results from the regression analysis showed that higher age of the spouse and dependency of the stroke survivor had a negative association with the spouses' QALY-weights. CONCLUSION: The QALY-weights for spouses of dependent midlife stroke survivors were significantly reduced compared to spouses of independent midlife stroke survivors. This indicates that the inclusion of spouses' QALYs in evaluations of early treatment and rehabilitation efforts to reduce stroke patients' dependency would capture more of the total effect in dyads of stroke survivors.
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| 9. |
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| 10. |
- Persson, Josefine, 1981, et al.
(author)
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Stroke survivors’ long-term QALY-weights in relation to their spouses’ QALY-weights and informal support: a cross-sectional study
- 2017
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In: Health and Quality of Life Outcomes. - : Springer Science and Business Media LLC. - 1477-7525. ; 15
-
Journal article (peer-reviewed)abstract
- Background: Healthcare interventions that have positive effects on the stroke survivors’ health-related quality of Life (HRQoL) and quality-adjusted life-years (QALYs) might also have positive effects for their spouses in terms of improved HRQoL and/or reduced spousal informal support. However, knowle dge about stroke survivors ’ HRQoL and QALY and the consequences for their spouses’ HRQoL and QALY is limited. Therefore, the aim of this study was to describe the HRQoL and QALY-weights in dyads of stroke survivors in comparison with dyads of healthy controls, and to study the relationship between the stroke survivors’ QALY-weights and consequences for spouses in terms of QALY-weight and annual cost of informal support, using a long-term perspective. Methods: Data on stroke survivors, controls, and spouses were collected from the seven-year follow-up of the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). HRQoL was assessed by the SF-36, and the preference-based health state values were assessed with the SF-6D. The magnitude of the support was assessed with a study specific time-diary. An ordinary least squares (OLS) regression was used to estimate the association between stroke survivors’ and spouses’ QALY-weights. A two-part econometri c model was used to estimate the association between stroke survivors’ QALY-weights and the time spent and cost of spouses’ informal support. Results: Cohabitant dyads of 248 stroke survivors’ aged <70 at stroke onset and 245 controls were included in the study. Stroke survivors had lower HRQoL in the SF-36 domains physical functioning, physical role, general health, vitality (P <0.001), and social functioning (P = 0.005) in comparison with their cohabitant spouses. There was no significant difference in HRQoL for the dyads of controls. The results from the regression analyses showed that lo wer QALY-weights of the stroke survivors were associated with lower QALY-weights of their spouses and increased annual cost of spousal informal support. Conclusion: Our results show that the QALY-weight s for stroke surv ivors had consequences for their spouses in terms of annual cost of spousal informal support and QALY-weights. Hence, economic evalu ation of interventions that improve the HRQoL of the stroke survivors but ignore the consequences for their spouses may underestimate the value of the intervention.
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| 11. |
- Schirmer, M. D., et al.
(author)
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White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts - The MRI-GENIE study
- 2019
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In: Neuroimage-Clinical. - : Elsevier BV. - 2213-1582. ; 23
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Journal article (peer-reviewed)abstract
- White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.
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| 12. |
- Wu, O., et al.
(author)
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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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In: Stroke. - : Ovid Technologies (Wolters Kluwer Health). - 0039-2499 .- 1524-4628. ; 50:7, s. 1734-1741
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Journal article (peer-reviewed)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 (rho=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm(3) (0.9-16.6 cm(3)). 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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| 13. |
- Wu, Ona, et al.
(author)
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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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In: Stroke. - 1524-4628. ; 50:7, s. 1734-1741
-
Journal article (peer-reviewed)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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| 14. |
- Åberg, Daniel, 1973, et al.
(author)
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Homeostasis model assessment of insulin resistance and outcome of ischemic stroke in non-diabetic patients - a prospective observational study
- 2019
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In: BMC Neurology. - : Springer Science and Business Media LLC. - 1471-2377. ; 19:1
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Journal article (peer-reviewed)abstract
- BackgroundInsulin resistance (IR) in relation to diabetes is a risk factor for ischemic stroke (IS), whereas less is known about non-diabetic IR and outcome after IS.MethodsIn non-diabetic IS (n=441) and controls (n=560) from the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS), IR was investigated in relation to IS severity and functional outcome. IR was evaluated acutely and after 3months using the Homeostasis model assessment of IR (HOMA-IR). Stroke severity was assessed by the National Institutes of Health Stroke Scale (NIHSS). Functional outcome was evaluated using the modified Rankin Scale (mRS) after 3months, 2 and 7years. Associations were evaluated by logistic regression.ResultsHigher acute and 3-month HOMA-IR was observed in IS compared to the controls (both p<0.001) and in severe compared to mild IS (both p<0.05). High acute HOMA-IR was associated with poor outcome (mRS 3-6) after 3months and 7years [crude Odds ratios (ORs), 95% confidence intervals (CIs) 1.50, 1.07-2.11 and 1.59, 1.11-2.30, respectively], but not after 2years. These associations lost significance after adjustment for all covariates including initial stroke severity. In the largest IS subtype (cryptogenic stroke), acute HOMA-IR was associated with poor outcome after 2years also after adjustment for age and stroke severity (OR 2.86, 95% CI 1.01-8.12).ConclusionsIn non-diabetic IS patients, HOMA-IR was elevated and related to stroke severity, but after adjustment for IS severity, the associations between HOMR-IR and poor outcome lost significance. This could suggest that elevated IR mostly is a part of the acute IS morbidity. However, in the subgroup of cryptogenic stroke, the associations with poor outcome withstood correction for stroke severity.
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