Post-Stroke Depression and Estimated Glomerular Filtration Rate: A Prospective Stroke Cohort

Effects of lavender essential oil inhalation aromatherapy on depression and sleep quality in stroke patients: A single-blind randomized controlled trial

BACKGROUND AND PURPOSE

Post-stroke depression (PSD) has major implications for rehabilitation, motor recovery, activities of daily living, social and interpersonal functioning, and mortality. In view of the side effects of antidepressants, aromatherapy, a widely used non-pharmacological therapy, has received growing attention in recent years for its benefits of reduced complications, accessibility, and effectiveness. This study was designed to assess the effects of inhalation aromatherapy with lavender essential oil on depression and sleep quality in patients with PSD.

MATERIALS AND METHODS

Forty patients with PSD were enrolled and randomized into experimental and placebo groups. Experimental-group patients inhaled microencapsulated lavender essential oil every night at bedtime over a period of 4 weeks. A nonwoven bag containing 2.3 g of microcapsules with about 1.5 g of lavender essential oil was placed on or under the patient's pillow, depending on the patient's scent sensitivity. Placebo-group patients used the empty nonwoven bags for the same period as the experimental group. The 17-item Hamilton Rating Scale for Depression (HAMD-17), the Zung Self-Rating Depression Scale (SDS), and the Pittsburgh Sleep Quality Index (PSQI) were used to measure outcomes.

RESULTS

The HAMD-17 score, SDS score, and PSQI score showed statistically significant differences between both groups before and after intervention (P ≤ 0.01). The improvement in the experimental group was more marked than in the placebo group (P < 0.05).

CONCLUSION

Lavender essential oil inhalation aromatherapy may help reduce depression and improve sleep quality in patients with PSD.

Machine learning algorithms assisted identification of post-stroke depression associated biological features

Objectives

Post-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynamic changes in metabolism and hemodynamics, however, there is still a lack of metabolism-associated effective and reliable diagnostic markers and therapeutic targets for PSD. Our study was dedicated to the discovery of metabolism related diagnostic and therapeutic biomarkers for PSD.

Methods

Expression profiles of GSE140275, GSE122709, and GSE180470 were obtained from GEO database. Differentially expressed genes (DEGs) were detected in GSE140275 and GSE122709. Functional enrichment analysis was performed for DEGs in GSE140275. Weighted gene co-expression network analysis (WGCNA) was constructed in GSE122709 to identify key module genes. Moreover, correlation analysis was performed to obtain metabolism related genes. Interaction analysis of key module genes, metabolism related genes, and DEGs in GSE122709 was performed to obtain candidate hub genes. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. Expression of signature genes was validated in GSE140275, GSE122709, and GSE180470. Gene set enrichment analysis (GSEA) was applied on signature genes. Based on signature genes, a nomogram model was constructed in our PSD cohort (27 PSD patients vs. 54 controls). ROC curves were performed for the estimation of its diagnostic value. Finally, correlation analysis between expression of signature genes and several clinical traits was performed.

Results

Functional enrichment analysis indicated that DEGs in GSE140275 enriched in metabolism pathway. A total of 8,188 metabolism associated genes were identified by correlation analysis. WGCNA analysis was constructed to obtain 3,471 key module genes. A total of 557 candidate hub genes were identified by interaction analysis. Furthermore, two signature genes (SDHD and FERMT3) were selected using LASSO and random forest analysis. GSEA analysis found that two signature genes had major roles in depression. Subsequently, PSD cohort was collected for constructing a PSD diagnosis. Nomogram model showed good reliability and validity. AUC values of receiver operating characteristic (ROC) curve of SDHD and FERMT3 were 0.896 and 0.964. ROC curves showed that two signature genes played a significant role in diagnosis of PSD. Correlation analysis found that SDHD (r = 0.653, P &lt; 0.001) and FERM3 (r = 0.728, P &lt; 0.001) were positively related to the Hamilton Depression Rating Scale 17-item (HAMD) score.

Conclusion

A total of 557 metabolism associated candidate hub genes were obtained by interaction with DEGs in GSE122709, key modules genes, and metabolism related genes. Based on machine learning algorithms, two signature genes (SDHD and FERMT3) were identified, they were proved to be valuable therapeutic and diagnostic biomarkers for PSD. Early diagnosis and prevention of PSD were made possible by our findings.

Serum Cystatin C is Associated with Depression After Intracerebral Hemorrhage

Purpose

Cystatins are associated with neuronal degeneration and nervous system healing. Cystatin C (Cys C) has recently been linked to brain injury and immunological inflammation. This study aimed to determine the relationship between serum Cys C levels and depression following intracranial hemorrhage (ICH).

Patients and Methods

Between September 2020 and December 2022, 337 patients with ICH were sequentially recruited and followed up for three months. The post-stroke depression (PSD) and non-PSD groups were separated based on the 17-item Hamilton Depression Rating Scale (HAMD). The PSD diagnosis was established based on the DSM-IV criteria. Cys-C levels were documented within twenty-four hours of admission.

Results

Three months after ICH, 93 (27.6%) of 337 enrolled patients were diagnosed with depression. The Cys C levels were significantly higher in depressed patients than in nondepressed patients after ICH (1.32 vs 1.01; p<0.001). After adjusting for potential confounding variables, depression after ICH was associated with the highest quartile of Cys C levels (odds ratio (OR) = 3.195, 95% CI: 1.562-6.536; p=0.001). The receiver operating characteristic curve (ROC) curve predicted that the ideal cut-off for CysC levels as a predictor of depression after ICH would be 0.730, resulting in 84.5% sensitivity and 88.4% specificity, with an area under curve (AUC) of 0.880 (95% CI: 0.843-0.917; p< 0.0001).

Conclusion

Increased CysC concentrations were independently related to depression three months after ICH, highlighting that CysC levels at admission may be a potential biomarker for predicting the onset of depression following ICH.

Change in Depressive Symptoms During the First Month of Discharge and 1-Year Clinical Outcomes in Patients Hospitalized for Heart Failure

Background The patterns of depressive symptom change during the first month after discharge, as well as their prognostic implications, and predictors of persistent or new-onset depressive symptoms are not well characterized. Methods and Results We included patients hospitalized for heart failure undergoing Patient Health Questionnaire-2 before discharge and at 1 month after discharge in a multicenter prospective cohort. We characterized 4 patterns of change in depressive symptoms-persistent, new-onset, remitted depressive symptoms, and no depressive symptom-and examined the associations between the 4 patterns and 1-year clinical outcomes. We analyzed the factors associated with persistent or new-onset depressive symptoms. A total of 4130 patients were included. Among 1175 (28.5%) symptomatic patients and 2955 (71.5%) symptom-free patients before discharge, 817 (69.5%) had remission, and 366 (12.2%) had new-onset depressive symptoms, respectively. Compared with no depressive symptom, persistent depressive symptoms were associated with an increased risk of cardiovascular death (hazard ratio [HR], 2.10 [95% CI, 1.59-2.79]) and heart failure rehospitalization (HR, 1.56 [95% CI, 1.30-1.87]); new-onset depressive symptoms were associated with an increased risk of cardiovascular death (HR, 1.78 [95%CI, 1.32-2.40]) and heart failure rehospitalization (HR, 1.54 [95% CI, 1.29-1.83]). Remitted depressive symptoms were associated with a slightly increased risk of cardiovascular death but had no significant association with heart failure rehospitalization. Patients who were female or had poor socioeconomic status, stroke history, renal dysfunction, or poor health status had a higher risk of persistent or new-onset depressive symptoms. Conclusions Sex, socioeconomic status, clinical characteristics, and health status help identify patients with high risks of depressive symptoms at 1 month after discharge. Dynamic capture of depressive symptom change during this period informs long-term risk stratifications and targets patients who require psychological interventions and social support to improve clinical outcomes. Registration URL: https://www.clinicaltrials.gov; Unique identifier (NCT02878811).

Altered effective connectivity in the emotional network induced by immersive virtual reality rehabilitation for post-stroke depression

Post-stroke depression (PSD) is a serious complication of stroke that significantly restricts rehabilitation. The use of immersive virtual reality for stroke survivors is promising. Herein, we investigated the effects of a novel immersive virtual reality training system on PSD and explored induced effective connectivity alterations in emotional networks using multivariate Granger causality analysis (GCA). Forty-four patients with PSD were equally allocated into an immersive-virtual reality group and a control group. In addition to their usual rehabilitation treatments, the participants in the immersive-virtual reality group participated in an immersive-virtual reality rehabilitation program, while the patients in the control group received 2D virtual reality rehabilitation training. The Hamilton Depression Rating Scale, modified Barthel Index (MBI), and resting-state functional magnetic resonance imaging (rsfMRI) data were collected before and after a 4-week intervention. rsfMRI data were analyzed using multivariate GCA. We found that the immersive virtual reality training was more effective in improving depression in patients with PSD but had no statistically significant improvement in MBI scores compared to the control group. The GCA showed that the following causal connectivities were strengthened after immersive virtual reality training: from the amygdala, insula, middle temporal gyrus, and caudate nucleus to the dorsolateral prefrontal cortex; from the insula to the medial prefrontal cortex; and from the thalamus to the posterior superior temporal sulcus. These causal connectivities were weakened after treatment in the control group. Our results indicated the neurotherapeutic use of immersive virtual reality rehabilitation as an effective non-pharmacological intervention for PSD; the alteration of causal connectivity in emotional networks might constitute the neural mechanisms underlying immersive-virtual reality rehabilitation in PSD.

Natural Products for the Treatment of Post-stroke Depression

Post-stroke depression (PSD) is the most frequent and important neuropsychiatric consequence of stroke. It is strongly associated with exacerbated deterioration of functional recovery, physical and cognitive recoveries, and quality of life. However, its mechanism is remarkably complicated, including the neurotransmitters hypothesis (which consists of a monoaminergic hypothesis and glutamate-mediated excitotoxicity hypothesis), inflammation hypothesis, dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis, and neurotrophic hypothesis and neuroplasticity. So far, the underlying pathogenesis of PSD has not been clearly defined yet. At present, selective serotonin reuptake inhibitors (SSRIs) have been used as the first-line drugs to treat patients with PSD. Additionally, more than SSRIs, a majority of the current antidepressants complied with multiple side effects, which limits their clinical application. Currently, a wide variety of studies revealed the therapeutic potential of natural products in the management of several diseases, especially PSD, with minor side effects. Accordingly, in our present review, we aim to summarize the therapeutic targets of these compounds and their potential role in-clinic therapy for patients with PSD.

Differential expression analysis of microRNAs and mRNAs in the mouse hippocampus of post-stroke depression (PSD) based on transcriptome sequencing

To clarify the differential expressions of microRNAs and mRNAs in a PSD model, this study employed PSD mice for model construction by injecting vasoconstrictor ET-1 (angioendothelin-1) into the medial prefrontal cortex (mPFC) of mice. The animals underwent elevated plus maze test, open field test, tail suspension test, and forced swimming test subsequently. Transcriptome sequencing was performed to analyze the differentially expressed mRNAs and microRNAs. The results showed that open arm entries and time of PSD mice were markedly decreased. Times of the entry to center for mice in the model group were apparently decreased. The climbing time of mice in the model group was greatly decreased. The behavior of PSD mice indicated a marked change, and several indicators of the behavioral tests were significantly lower than those of the control group. Transcriptome sequencing analysis demonstrated that expressions of 1 206 genes and 21 microRNAs were markedly upregulated in model group, whereas expressions of 2 113 genes and 32 microRNAs were markedly downregulated. GO analysis revealed that the differentially expressed genes were mainly involved in regulatory pathways of single-multicellular organism process, developmental process, cell periphery, plasma membrane, and neuron projection. Meanwhile, KEGG analysis results indicated that the differentially expressed genes mostly participated in signaling pathways of neuroactive ligand-receptor interaction, calcium signaling pathway, and cytokine-cytokine receptor interaction. In conclusion, differentially expressed microRNAs and mRNAs were screened, which offers a theoretical foundation for further investigation of molecular mechanisms and novel insight for the early identification, prevention, and treatment of PSD.

The efficacy and safety of agomelatine, sertraline, and escitalopram for senile post-stroke depression: A randomized double-blind placebo-controlled trial

OBJECTIVES

This study aims to investigate the efficacy and safety of agomelatine, sertraline, and escitalopram for patients with senile post-stroke depression (SPSD, aged over 65 years).

PATIENTS AND METHODS

A total of 165 patients (aged over 65 years) with post-stroke depression (PSD) were recruited. These patients were randomly assigned to one of four groups and given an anti-depressant or a placebo as follows: group A (agomelatine in combination with conventional cerebrovascular disease medication) 48 patients; group B (sertraline in combination with conventional cerebrovascular disease medication) 47 patients; group C (escitalopram in combination with conventional cerebrovascular disease medication) 50 patients; and, a control group (conventional treatment alone) 20 patients. The efficacy of the different treatments was evaluated using the Hamilton Depression Scale (HAMD), the National Institute of Health Stroke Scale (NIHSS), and the Activities of Daily Living (ADL) Barthel index (BI) at one, two, four, and six weeks after treatment began.

RESULTS

According to the HAMD, NIHSS score, and BI index, the patients who received one of the three antidepressant treatments showed significant improvement compared with the control group (p < 0.05), but there was no significant difference between the three groups receiving anti-depressant medication (p > 0.05). Laboratory tests showed that the general adverse effects of the treatments were mild in all three groups, and patients generally tolerated the treatments.

CONCLUSION

A decrease of HAMD and NIHSS scores and an increase in the BI index could be observed in the patients receiving agomelatine, sertraline, or escitalopram treatment. Thus, it would appear that the condition of SPSD in older patients can be improved with the use of either agomelatine, sertraline, or escitalopram.