Risk Factors For Post-stroke Depression Research Articles

Trajectories of depressive symptoms 10 years after stroke and associated risk factors: a prospective cohort study

BackgroundPrevious studies have investigated the risk factors for post-stroke depression at only one timepoint, neglecting its dynamic nature. We aimed to identify trajectories of post-stroke depression from multiple assessments and explore their risk factors. MethodsWe did a population-based cohort study with the South London Stroke Register (1995–2019). All stroke patients with three or more measurements of the Hospital Anxiety and Depression Scale were included. We identified trajectories of post-stroke depression over a 10-year follow-up using group-based trajectory modelling. We determined the optimal number and shape of trajectories based on the lowest Bayesian information criterion, average posterior probability of assignment of each group over 0·70, and inclusion of at least 5% of participants within each group. We used multinomial logistic regression adjusted for age, sex, ethnicity, comorbidity, physical disability, stroke severity, history of depression and cognitive impairment to explore associations with different trajectories. FindingsThe analysis comprised 1968 participants (mean age 64·9 years [SD 13·8], 56·6% male and 43·4% female, 65·1% white ethnicity, 30·7% severe disability and 32·7% severe stroke). We identified four patterns of symptoms: no depressive symptoms (14·1%, n=277), low symptoms (41·7%, n=820), moderate symptoms and symptoms worsening early and then improving (34·6%, n=681), and high and increasing symptoms (9·7%, n=190). Compared with no depressive symptom trajectory, patients with severe disability, severe stroke, pre-stroke depression, and cognitive impairment were more likely to be in the moderate and high symptom groups (adjusted odds ratios [ORs] 2·26 [95% CI 1·56–3·28], 1·75 [1·19–2·57], 2·20 [1·02–4·74], and 2·04 [1·25–3·32], respectively). Female sex was associated with high depression (OR 1·65 [1·13–2·41]), while older age (≥65 years) was associated with moderate depression (OR 1·82 [1·36–2·45]). In men, the ORs for patients with severe disability, severe stroke, pre-stroke depression, and cognitive impairment being in the high depression group were 1·91 (1·01–3·60), 2·41 (1·26–4·60), 2·57 (0·84–7·88), and 2·68 (1·28–5·60), respectively. In women, the ORs were 1·08 (0·52–2·23), 1·30 (0·60–2·79), 19·2 (2·35–156·05), and 3·80 (1·44–10·01), respectively. InterpretationFemale sex and older age were associated with distinct courses of depressive symptoms. In men, high depressive symptom trajectory was associated with severe stroke and severe disability, which was not the case in women. These findings were limited to patients with three or more assessments, who tended to have less severe disabilities than excluded patients and might not generalise to all stroke survivors. FundingNational Institute for Health and Care Research (NIHR).

Risk factors of post-stroke depression after acute ischemic stroke - A prospective study from a tertiary care hospital in South India

Background: Post-stroke depression is a major cause for poor functional and rehabilitation recovery. Aims and Objectives: The aims of the study were to determine risk factors causing depression in acute ischemic stroke. Materials and Methods: Prospective cohort study was conducted in acute ischemic stroke patients between January 2023 and April 2023 at Travancore Medical College, Kerala. They were divided into – ischemic stroke patients with depression and without depression. Variables studied – age, gender, marital, educational, occupation, socioeconomic status, national institute of health stroke scale (NIHSS) at admission, modified Rankin Scale (mRS) at 1 month, stroke lateralization, risk factors, and lobe and site. Results: Among 270 patients, 164 (60.7%) were male, 254 (94.1%) were above 50 years, 250 (92.6%) had marriage partner, 164 (60.7%) unemployed, 138 (51.1%) belonged to middle socioeconomic status, and 172 (63.7%) from rural areas. About 91 (33.7%) were in ischemic stroke patients with depression group. In univariate analysis, marriage, socioeconomic status, subcortical location, left hemisphere, severe NIHSS, and high mRS were associated with post-stroke depression. In multivariate analysis, socioeconomic status, subcortical location, and left hemisphere were significant risk factors. Strongest predictor was subcortical location. Conclusion: Early identification of following risk factors – socioeconomic and marital status, subcortical location, left hemisphere lesion, severe NIHSS, and high mRS in acute stroke patients may help to identify those who are vulnerable for post-stroke depression.

Risk factors for post-stroke depression in patients with mild and moderate strokes.

To determine the possible risk factors for post-stroke depression in patients with mild and moderate acute strokes. A cross-sectional descriptive study was conducted involving 129 patients with mild and moderate acute strokes. The patients were divided into post-stroke depression and non-depressed stroke groups according to the Hamilton Depression Rating Scale for Depression-17 item and Patient Health Questionnaire-9 item assessments. All participants were evaluated based on clinical characteristics and a battery of scales. Patients with post-stroke depression had an increased stroke frequency, severe stroke symptoms and poor performance in activities of daily living (ADL), cognitive function, sleep quality, interest in pleasurable activities, negative life events, and utilization of social support compared to stroke patients without depression. The Negative Life Event Scale (LES) score was significantly and independently associated with an increased probability of depression in stroke patients. Negative life events were shown to be independently associated with the incidence of depression in patients with mild and moderate acute strokes, likely mediating the influence of other predictors of depression, such as a history of stroke, decreased ADL ability, and utilization of support.

Scientometric analysis of post-stroke depression research based on CiteSpace.

Post-stroke depression (PSD) has served as a severe and common complication leading to a higher level of mortality. Though various studies have been focused on PSD, limited research endeavor has been dedicated to bibliometric analysis in the past. In view of this, the current analysis serves to elucidate the latest status of global research and pinpoint the emerging area of interest for PSD, in order to support further investigation of the field. Publications related to PSD were retrieved from the Web of Science Core Collection database on September 24, 2022, and included in the bibliometric analysis. VOSviewer and CiteSpace software were used to visually analyze publication outputs, scientific cooperation, highly-cited references, and keywords to identify the current status and future trends in PSD research. A total of 533 publications were retrieved. The annual number of publications showed an increasing trend from 1999 to 2022. In terms of country and academic institution, the USA and Duke University have topped the list of PSD research respectively. Meanwhile, Robinson RG and Alexopoulos GS have been the most representative investigators of the field. In the past, researchers focused on the risk factors of PSD, late-life depression, and Alzheimer disease. In recent years, further research effort has been placed on meta-analysis, ischemic stroke, predictor, inflammation, mechanism, and mortality. In conclusion, in the past 20 years, PSD research has been progressing and gaining more attention. The bibliometric analysis successfully unveiled the field's major contributing countries, institutions, and investigators. Furthermore, current hot spots and future trends in the field of PSD were identified, which included meta-analysis, ischemic stroke, predictor, inflammation, mechanism, and mortality.

Establishment and verification of a nomogram model for predicting the risk of post-stroke depression.

The purpose of this study was to establish a nomogram predictive model of clinical risk factors for post-stroke depression (PSD). We used the data of 202 stroke patients collected from Xuanwu Hospital from October 2018 to September 2020 as training data to develop a predictive model. Nineteen clinical factors were selected to evaluate their risk. Minimum absolute contraction and selection operator (LASSO, least absolute shrinkage and selection operator) regression were used to select the best patient attributes, and seven predictive factors with predictive ability were selected, and then multi-factor logistic regression analysis was carried out to determine six predictive factors and establish a nomogram prediction model. The C-index, calibration chart, and decision curve analyses were used to evaluate the predictive ability, accuracy, and clinical practicability of the prediction model. We then used the data of 156 stroke patients collected by Xiangya Hospital from June 2019 to September 2020 for external verification. The selected predictors including work style, number of children, time from onset to hospitalization, history of hyperlipidemia, stroke area, and the National Institutes of Health Stroke Scale (NIHSS) score. The model showed good prediction ability and a C index of 0.773 (95% confidence interval: [0.696-0.850]). It reached a high C-index value of 0.71 in bootstrap verification, and its C index was observed to be as high as 0.702 (95% confidence interval: [0.616-0.788]) in external verification. Decision curve analyses further showed that the nomogram of post-stroke depression has high clinical usefulness when the threshold probability was 6%. This novel nomogram, which combines patients' work style, number of children, time from onset to hospitalization, history of hyperlipidemia, stroke area, and NIHSS score, can help clinicians to assess the risk of depression in patients with acute stroke much earlier in the timeline of the disease, and to implement early intervention treatment so as to reduce the incidence of PSD.

In-Hospital Symptoms of Depression and Anxiety are Strong Risk Factors for Post-Stroke Depression 90 Days After Ischemic Stroke.

Acute ischemic stroke (AIS) and depression are the major causes of disability and decreased quality of life worldwide. Psychiatric disorders are common after stroke, especially post-stroke depression (PSD), which affects one-third of survivors. Although frequent, little is known about the real complexity of the pathophysiology and the factors associated with PSD. This research aimed to provide data about risk factors and predictors of PSD 90days after AIS. A cohort study was conducted in a tertiary stroke center located in southern Brazil. We interviewed 148 patients with AIS who were consecutively hospitalized between January 2020 and January 2021. The Hospital Anxiety and Depression Scale (HADS) was applied during hospitalization and at follow-up 90days after AIS. Furthermore, sociodemographic, clinical, and radiological variables were investigated. Predictive factors were assessed using univariate and multivariate linear regression. The impact of the COVID-19 pandemic on the data was also evaluated. The frequency of PSD 90days after AIS was 33.9%. In-hospital symptoms of depression and anxiety each represented a 2-fold risk for PSD at follow-up. Furthermore, the HADS - anxiety score 90days after AIS was strongly associated with the HADS - depression value 90days after stroke (R: .71; B: .56; P < .01). The present study highlighted a noteworthy frequency of PSD 90days after AIS. Psychiatric variables during hospitalization and in the follow-up appeared to be the leading associated factors with PSD. These data might support the determination of which patients require more psychiatric management.

Association between homocysteine levels in acute stroke and poststroke depression: A systematic review and meta-analysis.

BackgroundHomocysteine (Hcy) has been confirmed to be associated with depression, but its relationship with poststroke depression (PSD) remains controversial. So far, there is no meta‐analysis of the correlation between Hcy level in acute stroke and PSD.MethodsA systematic search of a sub‐database of studies reporting the level of Hcy in the acute phase of ischemic stroke and PSD as of November 2021 was performed. Data extraction was performed strictly according to the inclusion and exclusion criteria. All data were analyzed using STATA 11.0. The standardized root mean square difference (SMD) and 95% confidence interval (CI) were used to compare continuous variables.ResultsA total of 11 studies were included in this study, including 2789 participants. The results of this meta‐analysis showed that admission the levels of Hcy were significantly higher in PSD survivors, compared to non‐PSD survivors (SMD = 0.37, 95%CI = 0.07–0.66, P ＜ .001). Subgroup analysis showed that survivors with PSD diagnosed more than 3 months after stroke had significantly different the levels of from non‐PSD survivors (6 months: SMD = 0.61, 95%CI = 0.40–0.82, 9 months: SMD = 1.00, 95%CI = 0.59–1.41).ConclusionThe level of Hcy in the acute phase of ischemic stroke is a risk factor for PSD.

Prevalence and Associated Factors of Poststroke Depression among Outpatient Stroke Patients Who Have a Follow-Up at the Outpatient Neurology Clinic of Zewditu Memorial Hospital in Addis Ababa, Ethiopia.

Background Poststroke depression is the most common and burdensome poststroke psychiatric complication. Studies showed discrepancies in reporting frequencies and risk factors for poststroke depression. Updated local data are relevant for efficient strategies of poststroke depression screening and prevention. Objectives To determine the prevalence and associated factors of poststroke depression among outpatient stroke patients from the outpatient neurology clinic of Zewditu Memorial Hospital in Addis Ababa, Ethiopia. Methods An institution-based cross-sectional study was conducted on 249 stroke patients. Data was collected through structured questionnaire using interviews and a review of medical charts. PHQ-9 depression questionnaire was used to diagnose poststroke depression. Descriptive analysis was used to see the nature of the characteristics of interests. Bivariate analysis was used to sort out variables at p values less than 0.05 for multivariate logistic regression. Significance level was obtained using an odds ratio with 95% CI and p value < 0.05. Results Point prevalence for poststroke depression was 27.5 percent. Female gender, unemployment, low social support level, diabetes mellitus, and poststroke period under 2 years were statistically significant and independent predictors for poststroke depression. Conclusions The point prevalence estimate of poststroke depression was comparable with other studies. Low social support levels increased the odds for poststroke depression by more than eight folds. It appeared that external factors are more important in the pathogenesis of poststroke depression in the African population. Detection and prevention programs should consider disparities of poststroke depression incidence and risk factors.

Abstract TP86: Depression And Anxiety After Stroke In A Young Adult Population

Background and Objectives: We aimed to determine the prevalence of poststroke depression (PSD) and anxiety as well as to identify their predictors in a population of young Filipino adults. Methods: We performed a cross-sectional epidemiologic study in the largest tertiary hospital in the Philippines. The study involved the administration of a structured survey tool and review of medical records. The Hospital Anxiety and Depression Score was used to screen for anxiety and depression. Chi-square tests and Fisher’s exact tests were used to compare between groups with anxiety or depression and those without. Multivariable logistic regression analysis was performed to determine significant socio-economic and clinical risk factors of PSD and anxiety. Results: In our study population of 114 young adult stroke patients, the prevalence of depression was 20.2% while the prevalence of anxiety was 34.2%. Significant predictors of PSD were the presence of anxiety (OR 1.84; CI 1.05-3.22), lower mRS scores (mRS 3-5 OR 5.52; 95% CI 1.09-8.03) and diabetes (OR 2.09; 95% CI 1.67-6.26). Meanwhile, significant predictors of poststroke anxiety included depression (OR 7.5; 95% CI 5.02-21.94) and dependence (Barthel Index scores 95-100; OR 0.32; 95% CI 0.14-0.71). Relationship status, educational attainment, stroke subtype and stroke location were not found to be significant predictors of PSD and anxiety. Conclusion: Our study showed that young adult patients who suffer from stroke are at risk for adverse socio-economic and psychiatric consequences. A significant proportion of the population had depression and anxiety after stroke. Clinicians should be aware of these conditions that influence the outcomes of young adult stroke patients.

Post-Stroke Depression: Prevalence, Associated Factors, and Relationship to Disability in a Tertiary Care Center in Sri Lanka.

Background and Objectives The prevalence of stroke in urban Sri Lanka is estimated at 10.4 per 1000 and is expected to rise. Post-stroke depression (PSD) is an independent predictor of poor long-term outcomes. It leads to suboptimal rehabilitation, decreased quality of life, and increased mortality and is under-recognized. The main objectives of this study were to estimate the prevalence of depression in stroke, assess factors associated with PSD, and assess the relationship of PSD to disability. Materials and Methods A descriptive cross-sectional study was conducted at the Neurology and Medical Ward, National Hospital of Sri Lanka. Non-probability, consecutive sampling was used to collect data from patients with ischemic stroke admitted from January 2019 to January 2020. Patients with significant pre-existing depression, cognitive impairment, and language deficits were excluded. A structured, pre-tested interviewer-administered questionnaire was used to assess the prevalence and associated factors of PSD. Beck's Depression Inventory (BDI) was administered 3 months following the stroke to screen for depression. Modified Rankin Score (MRS) was used to assess disability on admission, discharge, and at 3 months. Results Eighty-one stroke patients were screened. The mean age was 66.6 years (±standard deviation [SD]: 12.5). Male:female ratio was 1.2:1. Depression at 3 months of follow-up was observed in 35.8% (95% confidence interval [CI]: 25.4–47.2%) of participants. Following bivariate analysis, large vessel stroke ( p < 0.001), cortical stroke ( p < 0.001), frontal lobe lesions ( p < 0.001), history of past stroke ( p = 0.014), and sexual dysfunction ( p = 0.026) were associated with increased risk of PSD. The odds of a person with severe disability developing PSD was 7.9 times more than a person with a less severe disability at discharge from hospital and at 3 months of follow-up (odds ratio [OR] =7.9; 95% CI: 2.7–23.3, p = 0.000). Conclusions PSD occurs in one-third of strokes, keeping with previous studies. The risk of having PSD is higher among patients with severe disabilities. The difference in risk factors identified compared with previous studies can be attributable to differences in methodology. Identifying risk factors for post-stroke depression is essential to mitigate the poor outcome.

Depressive-, Cognitive- or Stroke-Related Risk Factors of Post-Stroke Depression: Which One Could Better Help Clinicians and Patients?

PurposePost-stroke depression (PSD) affects one third of stroke survivors, with multiple severe negative consequences. We aim to assess the weight of four different types of clinical risk factors for PSD.Patients and MethodsWe conducted a prospective cohort study in a stroke centre. After stroke, patients were assessed for cognitive performances, psychiatric standardized questionnaires and socio-demographic features. They were called three months after and assessed for major depressive episode using DSM criteria.ResultsPSD was diagnosed in 8 of the 59 (13.6%) patients enrolled in the study. After multivariate analysis, only “previous history of depressive episode” remained a significant predictive factor for PSD, the model explaining 19% of the total variance (OR=18.0; p=0.002). Patients with a previous history of depression had a 10-fold increased risk for PSD.ConclusionPrevious history of depression is confirmed as a strong risk factor for PDS and allow the identification of an at-risk sub-group of patients.

Incidence and risk factors of poststroke depression among acute stroke survival patients attending neurology outpatient department of a selected hospital in Kolkata

Background: Poststroke depression is consider as the most common emotional disorder of stroke survivors; it can affect one among three of stroke survivors at any time up to 5 years after stroke. Researcher chooses the topic to give focus on the emotional health of the stroke survivors after the stroke. This study was conducted to identify the incidence (short-term incidence) and risk factors of poststroke depression among acute stroke survival patients. Subjects and Methods: This descriptive survey design was conducted at neurology outpatient department of a selected hospital in Kolkata. Total 104 acute (within 3 months following stroke) stroke survival patients were selected by purposive sampling technique for this study purpose. Incidence of poststroke depression was identified by Montgomery–Asberg depression rating scale and for risk factors of poststroke depression; National Institutes of Health Stroke Scale, Barthel Index, and Mini-mental status examination were used. Tool was pretested before the final study. Results: The findings of the study showed that the incidence (short-term incidence) of poststroke depression was 52% (95% confidence interval: 42.2%–61.8%). The Chi-square value reveals that there is a significant association between poststroke depression and deterioration of disease condition from the onset of the disease, days of suffering from the disease, number of admission for the disease, severity of stroke, impairment of level of independence, and impairment of cognitive function. Conclusion: Identifying the risk factors of poststroke depression, the nurses can screen the stroke survival patients for early detection of depression following stroke.

Post-Stroke Depression and Stroke Rehabilitation: Literature Review

Post-Stroke Depression (PSD) is a common and disturbing complication of stroke that affects rehabilitation outcomes. A past history of depression and severe stroke are risk factors for PSD, and thus, more attention should be paid to such patients. Appropriately diagnosing and screening for PSD is important because proper treatment could improve depressive symptoms and disturbed abilities. Treatment for PSD includes psychological care, nutritional care, pharmacotherapy, and exercise. Pharmacotherapy is currently the leading treatment for PSD, but antidepressants are associated with various adverse effects. Psychological and nutritional care can help manage depressive symptoms and exercise has been proven to be an effective treatment associated with fewer contraindications than pharmacotherapy. These non-pharmacological approaches could be expected to expand in clinical practice.

Post-stroke depression: frequency, risk factors, and impact on quality of life among 103 stroke patients\u2014hospital-based study

BackgroundPost-stroke depression (PSD) has worse functional outcomes and quality of life. Despite the extensive literature on this topic, there is no agreement on the frequency or risk factors for post-stroke depression.ObjectivesTo establish the frequency and risk factors of post-stroke depression and its impact on quality of life.Patients and methodsOne hundred three stroke patients were recruited from the out-patient clinic of Qena University Hospital who satisfied the WHO definition for stroke, together with a control group of 50 age- and sex-matched healthy volunteers. A complete history, neurological examination, and CT brain were obtained for each patient. DSM-IV TR criteria were used for diagnosis of depressive disorders which was scored with the Hamilton depression rating scale (HAM-D); Barthel Index (BI), and quality of life were also measured.ResultsThirty-eight (36.9%) stroke patients had PSD which was significantly higher than in the normal population (control group 12%). Statistically significant risk factors for PSD included low educational level, low socioeconomic status, smoking, and post-stroke functional impairment. Post-stroke depression has an impact on quality of life.ConclusionPost-stroke depression is a relatively common complication of stroke and can affect the quality of life. Low educational level and socioeconomic status, as well as smoking and functional impairments, were considered as risk factors for the occurrence of post-stroke depression. Early detection of predictors of post-stroke depression may improve the outcome of stroke and prevent the psychiatric consequences.

Pre-stroke sleep duration and post-stroke depression

ObjectiveSleep disturbance and depression are common in stroke patients, however, little is known about the role of sleep in post-stroke depression. This study examined the association between pre-stroke sleep duration and depression at 90 days post-stroke in a population-based bi-ethnic sample. MethodsThe study included 1369 stroke patients from the Brain Attack Surveillance in Corpus Christi project who survived 90 days post-stroke. Depression at 90 days post-stroke was assessed by the 8-item Patient Health Questionnaire, and pre-stroke sleep duration was self-reported shortly after stroke in reference to the pre-stroke state. Multiple imputation and inverse probability weighting were used to deal with missing data and attrition. Weighted logistic regression models were fit to examine the association between pre-stroke sleep duration and post-stroke depression. ResultsThe mean age was 68.2 years, and 63.6% were Mexican American. The prevalence of post-stroke depression was highest among participants reporting less than 6 hours of sleep before stroke (52.4%, 95% confidence interval = 45.7%–59.0%). Compared with participants reporting 7–8 hours of sleep before stroke, those with short sleep duration had significantly increased odds for post-stroke depression (odds ratio = 1.96; 95% confidence interval = 1.38–2.79), after adjustment for sociodemographic, stroke and pre-stroke characteristics including pre-stroke depression. ConclusionsPre-stroke short sleep duration may be an independent risk factor for post-stroke depression.

Abstract TMP79: Pre-Stroke Sleep Apnea and Post-Stroke Depression

Introduction: Sleep apnea is an independent risk factor for stroke and strongly associated with depression; however, little is known about its role in predicting depression after stroke among stroke survivors. This study examined the association between pre-stroke sleep apnea risk and depression at 90 days post-stroke in a population-based sample. Methods: Data were obtained from the Brain Attack Surveillance in Corpus Christi (BASIC) project, a population-based stroke study in south Texas. The study sample consisted of 1,383 participants who had ischemic or hemorrhagic stroke between August 2010 and December 2016. Depression after stroke was measured by the 8-item Patient Health Questionnaire (range: 0-24). Participants scoring 10 or above were classified as having depression. Pre-stroke sleep apnea risk assessed at stroke onset was classified as high or low based on Berlin Questionnaire scores (high risk: 2 or more categories with a positive score; low risk: 0-1 category with a positive score). Inverse probability weighting and multiple imputation were used to deal with attrition and missing covariate data. Weighted logistic regression models were used to examine the association between pre-stroke sleep apnea risk and post-stroke depression. Results: Mean age of participants was 68.1 years (SD=12.3), men and women were evenly distributed, 59.4% were Mexican American, and 59.2% were at high risk for sleep apnea before stroke. High-risk participants were significantly more likely to be men, Mexican American, obese and on medication for depression at the time of stroke. Pre-stroke sleep apnea risk was associated with post-stroke depression (Odds Ratio [OR]=1.78, 95% Confidence Interval [CI]=1.38-2.29), even after adjustment for sociodemographic characteristics, smoking, obesity, pre-stroke depression status and stroke severity (OR=1.60, 95% CI=1.19-2.14). Conclusions: Pre-stroke sleep apnea may be an independent risk factor for post-stroke depression. Treatment of sleep apnea before or perhaps even after stroke may reduce risk for depression after stroke.

Post-stroke depression and related factors analysis

Objective To investigate the incidence of post-stroke depression (PSD) and its risk factors, so as to provide the theoretical reference for the prevention of community PSD. Methods A total of 300 stroke patients hospitalized in the department of neurology in the First Bethune Hospital of Jilin University from July 2016 to May 2017 were selected and assessed by Self-rating Depression Scale (SDS) and Hamilton Depression Scale (HAMD) on their depression. The incidence of PSD was analyzed and after controlling the confounding factors, the relation between PSD and relevant influencing factors were indicated by the Odds Ratio (OR) and 95% Confidence Interval (CI) . Results The incidence of PSD was 31.6% (95/300) in the 300 stroke patients. After controlling the confounding factors, it was found that marital status, occupational status, decreased activity ability, muscle strength, neurological impairment and diabetes were closely related to PSD (P<0.05) . Conclusions The prevalence of PSD is high and closely related to marital status, occupational status, decreased activity ability, muscle strength, neurological impairment and diabetes. Understanding the risk factors of PSD is necessary to provide intervention for the prevention and treatment of PSD, which has a certain effects in reducing PSD and improving the PSD patients' physical function. Key words: Stroke; Depression; Prevalence; Related factors

Risk factors for post-stroke depression in Sohag University Hospital

BackgroundDepression is one of the important complications of stroke. Post-stroke depression is associated with more physical disability, especially in daily activities, poor functional outcome, and high mortality rate.ObjectiveOur study aimed to investigate the risk factors for development of post-stroke depression 3 months following stroke.MethodsThis is a comparative study, comparing stroke patients with and without depression 3 months after the onset. Hamilton Depression Rating Scale (HDRS), Mini-Mental State Examination (MMSE), Scandinavian Stroke Scale (SSS), and modified Rankin scale (mRS) were used to evaluate patients 3 months post-stroke for depression, cognition, and physical disability. The patients were divided into two groups: patients’ group with depression and patients’ group without depression according to DSM-IV criteria. The clinical characteristics and scores on the HDRS, MMSE, SSS, and mRS were compared between depressive group and non-depressive group. Logistic regression analysis was performed to identify risk factors for depression 3 months after stroke.ResultsA total 102 stroke patients were recruited. Of these, 62 patients (60.78%) had depression. Multivariate logistic regression indicated that smoking, hypertension, increased physical disability, and impaired cognitive function were associated with post-stroke depression.ConclusionImportant risk factors found for PSD included smoking, hypertension, increased physical disability, and impaired cognitive function.

Is Cognitive Impairment a Risk Factor for Post-Stroke Depression? A Meta-Analysis Study

Background: Depression is a psychiatric complication of stroke that often occurs and had a negative impact. Every year, 15 million people who experience strokes globally are at risk of developing depression. Cognitive disorders are often associated with the presence of depression. Understanding of risk factors for depression can help in clinical identification and provide early intervention to improve stroke rehabilitation better. Therefore, it is very important to identify patients at risk for depression. This study aims to analyze cognitive impairment factors in the incidence of depression. Subjects and Method: The meta-analysis was conducted from Pubmed, Science Direct, and Springer Link databases using stroke, post-stroke depression AND risk keywords. The article chosen was an article published from January 1, 2009 to September 30, 2018. The data were analyzed using RevMan 5 program. Results: 6 studies consisting of 3140 patients were selected for this study. The results of a meta-analysis showed that cognitive impairment was a risk factor for depression. Cognitive disorder was positively and significantly associated with depression (OR = 1.24; 95% CI= 1.03 to 1.49; p = 0.02). Conclusion: Cognitive disorder is a risk factor for depression. Keywords: depression, post-stroke, cognitive impairment, risk factor, meta-analysis Correspondence: Dinda Ika Pratiwi. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36 A, Surakarta 57126, Central Java. Email: dindaika.pratiwi@gmail.com.Mobile: +6281290610504. Journal of Epidemiology and Public Health (2019), 4(2): 81-87 https://doi.org/10.26911/jepublichealth.2019.04.02.03

Poster 80: Low Serum BDNF Levels as Risk Factor for Post-Stroke Depression

PM&RVolume 10, Issue 9S1 p. S32-S33 Poster 80: Low Serum BDNF Levels as Risk Factor for Post-Stroke Depression Zhenxiang Han MD, PhD, Zhenxiang Han MD, PhD Spaulding Rehabilitation Hospital; Shanghai Seventh People's Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Charlestown, MA, United StatesSearch for more papers by this authorYao Wang MD, Yao Wang MDSearch for more papers by this authorXun Luo MD, Xun Luo MDSearch for more papers by this authorYulong Wang MD, PhD, Yulong Wang MD, PhDSearch for more papers by this authorQing-Mei Wang MD, PhD, Qing-Mei Wang MD, PhDSearch for more papers by this author Zhenxiang Han MD, PhD, Zhenxiang Han MD, PhD Spaulding Rehabilitation Hospital; Shanghai Seventh People's Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Charlestown, MA, United StatesSearch for more papers by this authorYao Wang MD, Yao Wang MDSearch for more papers by this authorXun Luo MD, Xun Luo MDSearch for more papers by this authorYulong Wang MD, PhD, Yulong Wang MD, PhDSearch for more papers by this authorQing-Mei Wang MD, PhD, Qing-Mei Wang MD, PhDSearch for more papers by this author First published: 26 September 2018 https://doi.org/10.1016/j.pmrj.2018.08.106Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume10, Issue9S12018 AAPM&R Annual Assembly AbstractsSeptember 2018Pages S32-S33 RelatedInformation