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      Cognitive ability, education and socioeconomic status in childhood and risk of post-stroke depression in later life: A systematic review and meta-analysis

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          Abstract

          Background

          Depression after stroke is common and is associated with poorer recovery. Risk factors such as gender, age and stroke severity are established, but it is unclear whether factors from earlier in life might also contribute.

          Methods

          We searched MEDLINE, PsycINFO, EMBASE and meta-analysed all available evidence on childhood (premorbid) IQ, socioeconomic status (SES), education and stroke in adulthood. We included all studies reporting data on >50 patients, calculating overall odds ratios (OR), mean difference, correlation, 95% confidence intervals (CI) and 95% predictive intervals (PI) using random effects methods. We quality assessed all studies, performed sensitivity analyses, assessed heterogeneity and publication bias.

          Results

          We identified 33 studies including 2,664 participants with post-stroke depression and 5,460 without (314 participants not classified). Low education (< = 8 years) was associated with post-stroke depression in studies which defined depression as score of mild and above on a depression rating scale (OR 1.47 95% CI 1.10–1.97, p<0.01) but not in studies where depression was defined as severe depressive symptoms or a clinical diagnosis of major depression (OR 1.04 95% CI 0.90–1.31, p = 0.60). Low education was not associated with an increased risk for post-stroke depression in studies that adjusted for age and sex (OR 0.86 95% CI 0.50–1.48 p = 0.58). Those with post-stroke depression had fewer years of education than those without post-stroke depression (MD 0.68 95% CI 0.05–1.31 p = 0.04). Few studies adjusted for vascular risk factors or stroke severity. Heterogeneity between studies was moderate and was partly explained by severity of depression. In the one study identified premorbid IQ did not differ between those with post-stroke depression (mean IQ 10.1.8 SD 9.8) vs those without (mean IQ 104 SD 10.1). There were no studies that examined childhood socioeconomic status and risk of post-stroke depression.

          Conclusions

          Having less education is associated with an increased risk of post-stroke depressive symptoms but with large confidence intervals and heterogeneity. Future studies should explore the relationship between early and late life risk factors to improve risk identification and to target prevention and treatment strategies.

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          Most cited references34

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          The effects of socioeconomic status on stroke risk and outcomes.

          The latest evidence on socioeconomic status and stroke shows that stroke not only disproportionately affects low-income and middle-income countries, but also socioeconomically deprived populations within high-income countries. These disparities are reflected not only in risk of stroke but also in short-term and long-term outcomes after stroke. Increased average levels of conventional risk factors (eg, hypertension, hyperlipidaemia, excessive alcohol intake, smoking, obesity, and sedentary lifestyle) in populations with low socioeconomic status account for about half of these effects. In many countries, evidence shows that people with lower socioeconomic status are less likely to receive good-quality acute hospital and rehabilitation care than people with higher socioeconomic status. For clinical practice, better implementation of well established treatments, effective management of risk factors, and equity of access to high-quality acute stroke care and rehabilitation will probably reduce inequality substantially. Overcoming barriers and adapting evidence-based interventions to different countries and health-care settings remains a research priority.
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            Early cognitive impairment predicts long-term depressive symptoms and quality of life after stroke.

            The aim of the present study was to examine the predictive value of cognitive impairment in the acute phase after stroke as a risk factor for long-term (six to ten months after stroke) depressive symptoms (DS) and a reduced quality of life (QOL), independent of demographic and neurological predictors. We evaluated 143 patients within the first 3 weeks post-stroke. Predictor variables included domain-specific cognitive function, demographic data, vascular risk factors, lesion characteristics, and clinical factors. Predictor variables associated with long-term DS (Montgomery Asberg Depression Rating Scale >or=7) and QOL (Stroke-Specific Quality of Life Scale) were identified with multiple logistic and linear regression. Long-term DS were independently predicted by cognitive impairment at baseline, DS at baseline, female sex, diabetes mellitus, and previous TIA(s). Cognitive impairment, increasing age, and functional dependence predicted a reduced QOL, whereas hypercholesterolaemia predicted a better QOL. Among all cognitive disorders, unilateral neglect was the greatest risk factor for DS after 6 months, whereas a disorder in visual perception and construction affected QOL the most. Cognitive impairment and vascular risk factors are important predictors of long-term DS and QOL after stroke. The prognostic value of cognition suggests a reactive component in the development or continuation of long-term DS.
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              Poststroke depression and emotional incontinence: correlation with lesion location.

              To correlate the location of stroke with poststroke depression (PSD) and emotional incontinence (PSEI). The authors prospectively studied 148 patients (94 men and 54 women, mean age 62 years) with single, unilateral stroke (126 infarcts and 22 hemorrhages) at 2 to 4 months poststroke with regard to the presence of PSD (using Diagnostic and Statistical Manual of Mental Disorders IV criteria and Beck Depression Inventory) and PSEI. The lesion location was analyzed by CT or MRI. Twenty-seven patients (18%) had PSD and 50 (34%) had PSEI. The presence of PSD and PSEI was not related to the nature, laterality, or size of the lesion. The frequency of PSEI, but not of PSD, was higher in women than in men and in ischemic rather than hemorrhagic stroke (p < 0. 05). Although both PSD and PSEI were related to motor dysfunction and location (anterior versus posterior cortex) of the lesion, location was a stronger determinant for PSD (p < 0.05). The prevalence of PSD/PSEI in each location was 75%/100% in frontal lobe of anterior cerebral artery territory, 50%/0 in temporal lobe, 30%/40% in frontal-middle cerebral artery territory, 13%/0 in occipital lobe, 19%/45% in lenticulocapsular area, 11%/16% in thalamus, 16%/53% in pontine base, 36%/55% in medulla, and 0/22% in cerebellum. Parietal and dorsal pontine lesions were not associated with PSD or PSEI. PSEI was more closely associated with lenticulocapsular strokes than was PSD (p < 0.01). Development of PSD and PSEI is strongly influenced by lesion location, probably associated with the chemical neuroanatomy related to the frontal/temporal lobe-basal ganglia-ventral brainstem circuitry. Although the lesion distribution is similar, PSEI is more closely related to lenticulocapsular strokes than is PSD.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 July 2018
                2018
                : 13
                : 7
                : e0200525
                Affiliations
                [1 ] Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
                [2 ] Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
                [3 ] Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Scotland, United Kingdom
                [4 ] Geriatric Medicine, Department of Clinical and Surgical Sciences, The University of Edinburgh, Edinburgh, United Kingdom
                [5 ] UK Dementia Research Institute at The University of Edinburgh, Edinburgh Medical School, Edinburgh, United Kingdom
                Charite Universitatsmedizin Berlin, GERMANY
                Author notes

                Competing Interests: E Backhouse and CAM have no conflicts of interest. V Cvoro reports grants from NHS Research Scotland which funded the study. S Shenkin reports no conflicts of interest relevant to the manuscript. J Wardlaw reports grants from Chest Heart and Stroke Scotland, grants from the European Union Horizon 2020 project No 666881, 'SVDs@target' and the Fondation Leducq. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-9812-6642
                Article
                PONE-D-18-04403
                10.1371/journal.pone.0200525
                6047794
                30011299
                89abebff-703d-4b08-a400-2ab7bdedbd1b
                © 2018 Backhouse et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 12 February 2018
                : 28 June 2018
                Page count
                Figures: 6, Tables: 1, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003754, Dr. Mortimer and Theresa Sackler Foundation;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000369, Chest, Heart and Stroke Association Scotland;
                Award ID: R14/A157
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
                Award ID: 666881
                Award Recipient :
                Funded by: NHS Research Scotland
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001674, Fondation Leducq;
                Award ID: 16 CVD 05
                Award Recipient :
                E Backhouse is part-funded by the Sackler Foundation, C McHutchison is funded by Chest, Heart and Stroke Scotland [R14/A157] and European Union Horizon 2020 project No 666881, ‘SVDs@target’. V Cvoro is funded by NHS Research Scotland. Fondation Leducq Transatlantic Network of Excellence for the Study of Perivascular Spaces in Small Vessel Disease, ref no. 16 CVD 05. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Geriatric Depression
                Medicine and Health Sciences
                Geriatrics
                Geriatric Psychiatry
                Geriatric Depression
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Geriatric Psychiatry
                Geriatric Depression
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Social Sciences
                Sociology
                Education
                Educational Attainment
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Neuroscience
                Cognitive Neurology
                Cognitive Impairment
                Biology and Life Sciences
                Neuroscience
                Cognitive Neuroscience
                Cognitive Neurology
                Cognitive Impairment
                Medicine and Health Sciences
                Neurology
                Cognitive Neurology
                Cognitive Impairment
                Research and Analysis Methods
                Research Assessment
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