Key Factors Associated with Major Depression in a National Sample of Stroke Survivors

Does Self-Reported BMI Modify the Association Between Stroke and Depressive Symptoms?

BACKGROUND

Depressive symptoms are common in stroke survivors. While obesity has been associated with stroke and depression, its influence on the association between stroke and depressive symptoms is unknown.

METHODS

Cross-sectional data from 2015 to 2016 Canadian Community Health Survey was used. History of stroke was self-reported and our outcome of interest was depressive symptoms in the prior 2 weeks, measured using the 9-item Patient Health Questionnaire. Self-reported body mass index (BMI) was modeled as cubic spline terms to allow for nonlinear associations. We used multivariable logistic regression to evaluate the association between stroke and depressive symptoms and added an interaction term to evaluate the modifying effect of BMI.

RESULTS

Of the 47,521 participants, 694 (1.0%) had a stroke and 3314 (6.5%) had depressive symptoms. Those with stroke had a higher odds of depressive symptoms than those without (aOR = 3.13, 95% CI 2.48, 3.93). BMI did not modify the stroke-depressive symptoms association (P interaction = 0.242) despite the observed variation in stroke-depressive symptoms association across BMI categories,: normal BMI [18.5-25 kg/m2] (aOR† = 3.91, 95% CI 2.45, 6.11), overweight [25-30 kg/m2] (aOR† = 2.63, 95% CI 1.58, 4.20), and obese [>30 kg/m2] (aOR† = 2.76, 95% CI 1.92, 3.94). Similar results were found when depressive symptoms were modeled as a continuous measure.

CONCLUSION

The association between stroke and depressive symptoms is not modified by BMI, needing additional work to understand the role of obesity on depression after stroke.

Racial Variation in the Association Between Domains of Depressive Symptomatology and Functional Recovery in Stroke Survivors

OBJECTIVE

The purpose of the study was to investigate the relationships between various domains of depressive symptomatology and functional recovery in Black and White stroke survivors.

METHODS

Black (n = 181) and White (n = 797) stroke survivors from the Stroke Recovery in Underserved Population database were included. Four domains of depressive symptomatology (depressed affect, positive affect, somatic symptoms, interpersonal difficulties) were measured by the Center for Epidemiologic Studies Depression Scale at discharge; functional recovery was measured by the Functional Independence Measure at discharge and 3-month follow-up. Multivariable linear regression analyses examined the relation between race and functional recovery, and the association between depressive symptomatology and functional recovery by race.

RESULTS

Three-month functional recovery was greater among White stroke survivors than Black survivors. Affective symptoms of depression predicted poorer functional recovery of White survivors; whereas somatic symptoms predicted poorer functional recovery of Black survivors.

CONCLUSIONS

Domains of depressive symptomatology were differentially associated with poorer functional recovery in Black and White stroke survivors. Psychosocial interventions aimed at alleviating depressive symptomatology have the potential to improve functional recovery in Black and White stroke survivors and should be addressed in planning rehabilitation post-stroke.

Prevalence, awareness, and treatment of depression among community-dwelling stroke survivors in Korea

Post-stroke depression (PSD), a prevalent complication of stroke, causes poor outcomes. However, little is known about its prevalence and management among community-dwelling stroke survivors. Thus, we investigated the prevalence, awareness, and treatment of PSD in a community setting. A cross-sectional study was performed using representative data from the Korea National Health and Nutrition Surveys 2014, 2016, and 2018. A total of 11,122 participants aged ≥ 40 years were categorized, including 343 stroke survivors and 10,779 non-stroke survivors. We then calculated and compared the prevalence, awareness (formal diagnosis of depression by a doctor), and treatment rates of depression between the two groups. Depression was defined as a score ≥ 10 in the nine-item Patient Health Questionnaire (PHQ-9). Depression was significantly more prevalent among stroke survivors than in non-stroke survivors (22.2% vs. 8.5%, respectively), while the differences in the awareness and treatment rates were insignificant. However, only 46.8% of stroke survivors with PSD were aware of their condition, and only 20.5% were receiving treatment. These results suggest that clinicians should more actively screen for and treat depression among stroke survivors.

Development and validation using NHANES data of a predictive model for depression risk in myocardial infarction survivors

Background

Depression after myocardial infarction (MI) is associated with poor prognosis. This study aimed to develop and validate a nomogram to predict the risk of depression in patients with MI.

Methods

This retrospective study included 1615 survivors of MI aged >20 years who were selected from the 2005–2018 National Health and Nutrition Examination Survey database. The 899 subjects from the 2005–2012 survey comprised the development group, and the remaining 716 subjects comprised the validation group. Univariate and multivariate analyses identified variables significantly associated with depression. The least absolute shrinkage and selection operator (LASSO) binomial regression model was used to select the best predictive variables.

Results

A full predictive model and a simplified model were developed using multivariate analysis and LASSO binomial regression results, respectively, and validated using data from the validation group. The receiver operator characteristic curve and Hosmer–Lemeshow goodness of fit test were used to assess the nomogram's performance. The full nomogram model included 8 items: age, BMI, smoking, drinking, diabetes, exercise, insomnia, and PIR. The area under the curve for the development group was 0.799 and for the validation group was 0.731, indicating that our model has good stability and predictive accuracy. The goodness of fit test showed a good model calibration for both groups. The simplified model includes age, smoking, PIR, and insomnia. The AUC of the simplified model was 0.772 and 0.711 in the development and validation groups, respectively, indicating that the simplified model still possessed good predictive accuracy.

Conclusion

Our nomogram helped assess the individual probability of depression after MI and can be used as a complement to existing depression screening scales to help physicians make better treatment decisions.

Factors Associated with Post-Stroke Depression in Chinese Stroke Survivors

OBJECTIVES

To explore the relationship between participation self-efficacy, sociodemographic and clinical characteristics, and post-stroke depression in stroke survivors and provide insights into the development of rehabilitation programmes.

MATERIALS AND METHODS

A cross-sectional descriptive study was conducted with 336 participants recruited from five hospitals in Kunming, China. Measures included the Chinese version of the Participation Strategies Self-Efficacy Scale (PS-SES-C), Geriatric Depression Scale (GDS), modified Barthel Index, Rivermead Mobility Index (RMI), Reintegration to Normal Living Index (RNLI), and the Social Support Questionnaire (SSQ6). Logistic regression analyses were performed using SPSS 25.0.

RESULTS

Nearly half (44.6%) of the sample was found to have depression. The mean participation self-efficacy score of stroke survivors with depression was significantly lower than that of those without depression. Logistic regression analyses suggested that participation self-efficacy is a constant and major factor negatively associated with depression, with every 10-pt increase in the PS-SES-C score associated with decreased odds of depression (p<0.001). Other features associated with depression prevalence to varying degrees included education level, marital status, pre-morbid financial role in family, stroke symptom severity, history of heart disease, frequency of stroke, lesion side, stroke type, and use of assistive aids.

CONCLUSIONS

Participation self-efficacy is negatively associated with depression in stroke survivors. Rehabilitation programmes might consider incorporating interventions aimed at boosting participation self-efficacy in order to promote positive recovery outcomes among survivors.

A systematic review of the effectiveness of machine learning for predicting psychosocial outcomes in acquired brain injury: Which algorithms are used and why?

Clinicians working in the field of acquired brain injury (ABI, an injury to the brain sustained after birth) are challenged to develop suitable care pathways for an individual client's needs. Being able to predict psychosocial outcomes after ABI would enable clinicians and service providers to make advance decisions and better tailor care plans. Machine learning (ML, a predictive method from the field of artificial intelligence) is increasingly used for predicting ABI outcomes. This review aimed to examine the efficacy of using ML to make psychosocial predictions in ABI, evaluate the methodological quality of studies, and understand researchers' rationale for their choice of ML algorithms. Nine studies were reviewed from five databases, predicting a range of psychosocial outcomes from stroke, traumatic brain injury, and concussion. Eleven types of ML were employed with a total of 75 ML models. Every model was evaluated as having high risk of bias, unable to provide adequate evidence for predictive performance due to poor methodological quality. Overall, there was limited rationale for the choice of ML algorithms and poor evaluation of the methodological limitations by study authors. Considerations for overcoming methodological shortcomings are discussed, along with suggestions for assessing the suitability of data and suitability of ML algorithms for different ABI research questions.

Family Functioning Mediates the Relationship Between Activities of Daily Living and Poststroke Depression

BACKGROUND

Poststroke depression is common and includes depressive and somatic symptoms. However, few studies have confirmed the influence of family functioning on poststroke depression or explored the association among daily activities, family functioning, and poststroke depression.

OBJECTIVES

We examined the independent risk factors of daily activities and family functioning for poststroke depression and identified the mediating effect of family functioning on the association between daily activities and poststroke depression.

METHODS

This cross-sectional study design used convenience sampling to recruit 422 stroke survivors from the neurology department of a hospital in Harbin, China, from February to July 2018. We assessed participants' demographic and clinical variables, including depression, daily activities, and family functioning. Pearson's correlations and multiple linear regression analyses were conducted, and a path analysis with bootstrapping was utilized to define direct/indirect effects.

RESULTS

Daily activities and family functioning had a significant and direct negative effect on participants' depression. The indirect effect of 1,000 bootstrap samples after bias correction with a 95% confidence interval was below zero, indicating that family function had a significant mediating effect on the association between depression and daily activities.

DISCUSSION

This study revealed the importance of family functioning in the association between depression and daily activities in stroke survivors. To the best of our knowledge, this study was the first to explore the mediating role of family functioning in poststroke depression, emphasizing the importance of family for the mental health of stroke patients. To reduce the incidence of poststroke depression, interventions that enhance daily activities and family functioning may include nurses, family therapists, rehabilitation physicians, and community workers.

Depressive Symptoms After Ischemic Stroke: Population-Based Comparisons of Patients and Caregivers With Matched Controls

Background and Purpose- Persistent depression after ischemic stroke is common in stroke survivors and may be even higher in family caregivers, but few studies have examined depressive symptom levels and their predictors in patient and caregiver groups simultaneously. Methods- Stroke survivors and their family caregivers (205 dyads) were enrolled from the national REGARDS study (Reasons for Geographic and Racial Differences in Stroke) into the CARES study (Caring for Adults Recovering from the Effects of Stroke) ≈9 months after a first-time ischemic stroke. Demographically matched stroke-free dyads (N=205) were also enrolled. Participants were interviewed by telephone, and depressive symptoms were assessed with the 20-item Center for Epidemiological Studies-Depression scale. Results- Significant elevations in depressive symptoms (Ps<0.03) were observed for stroke survivors (M=8.38) and for their family caregivers (M=6.42) relative to their matched controls (Ms=5.18 and 4.62, respectively). Stroke survivors reported more symptoms of depression than their caregivers (P=0.008). No race or sex differences were found, but differential prediction of depressive symptom levels was found across patients and caregivers. Younger age and having an older caregiver were associated with more depressive symptoms in stroke survivors while being a spouse caregiver and reporting fewer positive aspects of caregiving were associated with more depressive symptoms in caregivers. The percentage of caregivers at risk for clinically significant depression was lower in this population-based sample (12%) than in previous studies of caregivers from convenience or clinical samples. Conclusions- High depressive symptom levels are common 9 months after first-time ischemic strokes for stroke survivors and family caregivers, but rates of depressive symptoms at risk for clinical depression were lower for caregivers than previously reported. Predictors of depression differ for patients and caregivers, and standards of care should incorporate family caregiving factors.

Analysis of Influencing Factors of Poststroke Depression: Is Higher Body Mass Index Always a Risk Factor of Poststroke Depression?

Poststroke depression (PSD) is a common complication of stroke. We sought to investigate the influencing factors of PSD and explored the association between body mass index (BMI) and PSD. A total of 397 stroke patients in a hospital in Qiqihar City, China, were included in this study in 2016. The order of independent variable importance was the score of the National Institute of Health Stroke Scale, frequency of stroke, age, BMI, and sleep duration. Sleep duration of 7 hours or more (compared with <7 hours) was negatively associated with the Self-Rating Depression Scale (SDS) score in all quantiles. BMI of 28.0 kg/m or more (compared with 24.0-28.0 kg/m) was negatively associated with SDS score, and the coefficients manifested a continuous increasing trend from P30 to P84.1 in patients aged 65 years or more. In addition, the relationship between BMI and SDS score demonstrated a "U"-shaped curve in patients aged less than 65 years. The National Institute of Health Stroke Scale score, the frequency of stroke, sleep duration, and BMI were the influencing factors of PSD. BMI played different roles in the two age groups.

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

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.

A Population-Based Cohort Study on the Ability of Acupuncture to Reduce Post-Stroke Depression

Objective: Post-stroke depression (PSD) is common and has a negative impact on recovery. Although many stroke patients in Taiwan have used acupuncture as a supplementary treatment for reducing stroke comorbidities, little research has been done on the use of acupuncture to prevent PSD. Accordingly, our goal is to investigate whether using acupuncture after a stroke can reduce the risk of PSD. Method: This population-based cohort study examined medical claims data from a random sample of 1 million insured people registered in Taiwan. Newly diagnosed stroke patients in the period 2000–2005 were recruited in our study. All patients were followed through to the end of 2007 to determine whether they had developed symptoms of depression. A Cox proportional hazard model was used to estimate the relative risk of depression in patients after being diagnosed as having had a stroke, with a focus on the differences in those with and without acupuncture treatment. Results: A total of 8487 newly-diagnosed stroke patients were included in our study; of these, 1036 patients received acupuncture more than five times following their stroke, 1053 patients received acupuncture 1–5 times following their stroke and 6398 did not receive acupuncture. After we controlled for potential confounders (e.g., age, sex, insurance premium, residential area, type of stroke, length of hospital stay, stroke severity index, rehabilitation and major illness–related depression), we found that acupuncture after stroke significantly reduced the risk of depression, with a hazard ratio (HR) of 0.475 (95% CI, 0.389–0.580) in frequent acupuncture users and 0.718 (95% CI, 0.612–0.842) in infrequent acupuncture users, indicating that acupuncture may lower the risk of PSD by an estimated 52.5% in frequent users and 28.2% in infrequent users. Conclusions: After we controlled for potential confounders, it appears that using acupuncture after a stroke lowers the risk of depression. Additional strictly-designed randomized controlled trials are needed to better understand the specific mechanisms relating acupuncture to health outcomes.