Risk factors for post-stroke depression in Sohag University Hospital

Development, validation, and visualization of a novel nomogram to predict depression risk in patients with stroke

BACKGROUND

This study aimed to develop and validate a predictive nomogram model applicable to depression risk in stroke patients.

METHODS

Participants from the NHANES database (n = 1097) were enrolled from 2005 to 2018; 767 subjects were randomly assigned to the training cohort, and the remaining subjects composed the testing cohort. A nomogram containing the optimal predictors identified by the least absolute shrinkage and selection operator (LASSO) and logistic regression methods was constructed to estimate the probability of depression in stroke patients. To evaluate the performance of the nomogram, the area under the receiver operating characteristic curve (AUC), calibration plot, decision curve analysis (DCA) and internal validation were utilized.

RESULTS

Age, family income, trouble sleeping, coronary heart disease, and total cholesterol were included in the nomogram after filtering predictive variables. The AUCs of the nomogram for the training and testing cohorts were 0.782 (95 % CI = 0.742-0.821) and 0.755 (95 % CI = 0.675-0.834), respectively. The calibration plot revealed that the predicted probability was extremely close to the actual probability of depression occurrence in both the training and testing cohorts. DCA revealed that the nomogram model in the training and testing cohorts had a net benefit when the risk thresholds were 0-0.59 and 0-0.375, respectively.

LIMITATIONS

This study was limited by the absence of clinical external validation, which hindered the estimation of the nomogram's external applicability. In addition, this study has a cross-sectional design.

CONCLUSIONS

A novel nomogram was successfully constructed and proven to be beneficial for identifying individuals at high risk for depression among stroke patients.

Electroacupuncture versus Escitalopram for mild to moderate Post-Stroke Depression: A randomized non-inferiority trial

Objective

To explore the efficacy of electroacupuncture in treating post-stroke depression (PSD) by modulating the inflammatory response pathway.

Methods

One hundred and fifty participants with mild or moderate PSD were randomly divided into 75 cases each in the electroacupuncture group (EA group) and escitalopram group (ESC group). In the EA group, 30 sessions of electroacupuncture were performed on the Baihui (GV 20), Yintang (GV 29), and the ipsilateral Taichong (LR 3) and Hegu (LI 4), simultaneous oral placebo for 40 days. The ESC group received oral escitalopram oxalate tablets 10mg to 20mg for 40 days, plus 30 sessions of sham electroacupuncture. The effectiveness of the treatment was evaluated by the Hamilton Depression Scale (HAMD-17), Self-Depression Scale (SDS), Modified Barthel Index Score (MBI), and the serum levels of IL-1β, IL-6, IL-10, TNF-α, and INF-γ.

Results

There was no statistically significant difference in the baseline data, HAMD-17, SDS, MBI scores, and serum IL-1β, IL-6, IL-10, TNF-α, and INF-γ levels between the two groups of participants before the intervention (P >0.05). After treatment, HAMD-17 and SDS scores continued to decrease and MBI scores continued to increase in both groups. The differences were statistically significant at the 6th week and baseline, the 10th week and baseline, and the 10th week and the 6th week (all P <0.001). The differences in HAMD-17, SDS, and MBI scores between the two groups at the 6th week were not statistically significant (P=0.110, 0.115, 0.516, respectively); HAMD-17 scores and SDS scores in the EA group were lower than those in the ESC group at the 10th week, and the differences were statistically significant (P=0.002,0.026, respectively). In the 6th week, the serum levels of pro-inflammatory factors such as IL-1β, IL-6, TNF-α, and INF-γ were significantly lower in both groups compared with the baseline, while the level of anti-inflammatory factor IL-10 was significantly higher. The difference between the pre-and post-intervention intra-group comparisons was statistically significant (P <0.001), and the difference between the inter-group comparisons was not statistically significant (P >0.05). No serious adverse events occurred throughout the trial. Both therapies could safely and effectively improve HAMD-17, SDS, and MBI scores and modulate neuroinflammatory responses in PSD participants. After the treatment was stopped, some parameters were better in the EA group than the ESC group in a short time.

Conclusion

Electroacupuncture is an effective, alternative to escitalopram for the treatment of mild-to-moderate PSD.

Clinical trial registration

Chinese Clinical Trial Registry (ChiCTR2300072576).

The Associated Factors of Quality of Life among Stroke Survivors: A Study in Indonesia

Background: The prevalence and burden of stroke are still high, especially in low and middle-income countries. Stroke affects the economy and physics related to the Quality of Life (QoL). Various QoL-associated factors, including sociodemographic, functional outcome, emotional, and cognitive function, were studied. However, there was very limited information about the QoL-associated factors among stroke survivors in Semarang, Indonesia.Purpose: This study aimed to identify the QoL-associated factors among stroke survivors in Semarang, Indonesia.Methods: This cross-sectional study was conducted in outpatient services and involved 57 ischemic stroke survivors using convenience sampling. Demographic and clinical information were obtained using medical records and questionnaires. The questionnaires were the Short Version of Specific Stroke Quality of Life (SS-QoL) to measure QoL, GRID-HAMD 17 to measure Post Stroke Depression (PSD), Mini-Mental Status Examination (MMSE) to measure cognitive impairment, Barthel–Index (BI) to measure functional outcome, Hamilton Anxiety Rating Scale (HAM-A) to measure anxiety, and Multidimensional Scale of Perceived Social Support (MSPSS) to measure social support. Linear regression was conducted in the model performance of QoL-associated factors.Results: The stroke duration was 155(18) days, and 50.9% of participants were males. The linear regression showed that age (-.164 95% CI -.412 - .084), marital status (3.937 95% CI 1.010 - 6.864), functional outcome (.127 95% CI .013 - .241), PSD (-1.090 95% CI -2.144 - -.036), cognitive function (.308 95% CI -.482 - 1.098) and anxiety (-.408 95% CI -1.125 - .268) were QoL-predictors (p<.001, adjusted R2=52.1). It is assumed that age, marital status, functional outcome, PSD, cognition, and anxiety significantly predict the QoL among ischemic stroke survivors.Conclusion: The QoL-associated factors were age, marital status, functional outcome, PSD, cognition, and anxiety. These associated factors of QoL should be considered as elements in formulating nursing interventions that aim to improve the good QoL among stroke survivors.

Poststroke depression among stroke survivors in Sub-Himalayan region

INTRODUCTION

Stroke is a leading cause of long-term disability and loss of productive life in developing countries, including India. Ischemic stroke accounts for 85% of all types of stroke with a prevalence of 5%-15% among acute stroke incidents. The prevalence of poststroke depression among acute stroke survivors is varied from 5 to 54%. The study focused on depression among stroke survivors who actively involved in a home-based rehabilitation.

MATERIALS AND METHODS

A descriptive cross-sectional survey was conducted by enrolling 138 stroke survivors consecutively at tertiary care public hospital, North India. A sociodemographic and clinical profile sheet was used to seek information on personal and clinical variables. Information on disability, depression, performance in the activity of daily living, and degree of stroke severity was ascertained by using the Modified Rankin Scale (MRS), Physical Health Questionnaire (PHQ-9), Barthel Index, and National Institutes of Health Stroke (NIHSS). After binary logistic regression model, a multivariate logistic regression was applied to detect the independent predictor of depression.

RESULTS

Over 86% (119) of the stroke survivors had no symptoms of depression, and only 14% (19) were reported to have symptoms of depression. Poststroke depression found significant association with disability (P = 0.029) and functional independence (P = 0.0001). A significant difference was observed in the gender (P = 0.018), types of stroke (P = 0.0001), and location of lesion (P = 0.0001) with depression. Binary logistic regression model shows that disability (MRS) status of stroke survivor (P < 0.0001; 95% CI 1.998-2.638) and functional independence (BI) (P < 0.0001; 95% CI -0.034-0.020) are same as independent predictors for depression.

CONCLUSION

Clinician should use the community reintegration, referral, and mandatory screening of the stroke survivors at follow-up visit to rule out the probability of occurrence of poststroke depression.