RESUMO
BACKGROUND: Post-stroke depression (PSD) is one of the most common psychiatric diseases afflicting stroke survivors. This study was conducted to assess the efficacy of ginkgo biloba extract as augmentation of venlafaxine in treating PSD. METHODS: The included PSD patients were randomly assigned into the experiment group (receiving ginkgo biloba extract plus venlafaxine) and control group (receiving venlafaxine alone). The treatment was continued for eight weeks. The Hamilton Depression Rating Scale (HDRS) and the Self-rating Depression Scale (SDS) were used to assess the depressive symptoms. The National Institutes of Health Stroke Scale (NIHSS) was used to assess the neurological defect, and the Activities of Daily Living (ADL) was used to assess recovery of abilities of patients after stroke. Meanwhile, the levels of serum 5-hydroxytryptamine (5-HT) and brain-derived neurotrophic factor (BDNF) were measured before and after treatment. The dose of venlafaxine used and adverse events were also recorded. RESULTS: Each group had 40 PSD patients. After treatment, the depressive symptoms, neurological defect and living function were significantly improved in both groups. But the patients receiving ginkgo biloba extract plus venlafaxine had the significantly lower average HDRS score (p=0.0008), SDS score (p<0.00001), NIHSS score (p=0.00001), and higher average ADL score (p=0.0005). Meanwhile, compared to the control group, patients in the experiment group had the significantly higher 5-HT (p<0.00001) level and BDNF level (p<0.00001), needed lower dose of venlafaxine (p=0.007), and experienced fewer adverse events. CONCLUSION: These results demonstrated that the ginkgo biloba extract was a good augmentation of venlafaxine in treating PSD and should be further investigated.
RESUMO
BACKGROUND: Depression can seriously affect the quality of life of type 2 diabetes mellitus (T2DM) patients after stroke. However, there were still no objective methods to diagnose T2DM patients with poststroke depression (PSD). Therefore, we conducted this study to deal with this problem. METHODS: Gas chromatography-mass spectroscopy (GC-MS)-based metabolomics profiling method was used to profile the urinary metabolites from 83 nondepressed T2DM patients after stroke and 101 T2DM patients with PSD. The orthogonal partial least-squares discriminant analysis was conducted to explore the metabolic differences in T2DM patients with PSD. The logistic regression analysis was performed to identify the optimal and simplified biomarker panel for diagnosing T2DM patients with PSD. The receiver operating characteristic curve analysis was used to assess the diagnostic performance of this biomarker panel. RESULTS: In total, 23 differential metabolites (7 decreased and 16 increased in T2DM patients with PSD) were found. A panel consisting of pseudouridine, malic acid, hypoxanthine, 3,4-dihydroxybutyric acid, fructose and inositol was identified. This panel could effectively separate T2DM patients with PSD from nondepressed T2DM patients after stroke. The area under the curve was 0.965 in the training set and 0.909 in the validation set. Meanwhile, we found that the galactose metabolism was significantly affected in T2DM patients with PSD. CONCLUSION: Our results could be helpful for future development of an objective method to diagnose T2DM patients with PSD and provide novel ideas to study the pathogenesis of depression.
