The classification of brain network for major depressive disorder patients based on deep graph convolutional neural network

IntroductionThe early diagnosis of major depressive disorder (MDD) is very important for patients that suffer from severe and irreversible consequences of depression. It has been indicated that functional connectivity (FC) analysis based on functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers for clinical diagnosis. However, previous studies mainly focus on brain disease classification in small sample sizes, which may lead to dramatic divergences in classification accuracy.MethodsThis paper attempts to address this limitation by applying the deep graph convolutional neural network (DGCNN) method on a large multi-site MDD dataset. The resting-state fMRI data are acquired from 830 MDD patients and 771 normal controls (NC) shared by the REST-meta-MDD consortium.ResultsThe DGCNN model trained with the binary network after thresholding, identified MDD patients from normal controls and achieved an accuracy of 72.1% with 10-fold cross-validation, which is 12.4%, 9.8%, and 7.6% higher than SVM, RF, and GCN, respectively. Moreover, the process of dataset reading and model training is faster. Therefore, it demonstrates the advantages of the DGCNN model with low time complexity and sound classification performance.DiscussionBased on a large, multi-site dataset from MDD patients, the results expressed that DGCNN is not an extremely accurate method for MDD diagnosis. However, there is an improvement over previous methods with our goal of better understanding brain function and ultimately providing a biomarker or diagnostic capability for MDD diagnosis

Stigmatizing attitudes toward mental illness among caregivers of patients with mental disorders in China

ObjectiveThis study aimed to investigate stigmatizing attitudes toward depression, schizophrenia, and general anxiety disorder (GAD) among caregivers of patients with mental disorders in China.MethodsA cross-sectional study was conducted among 607 caregivers in China, using vignettes that described three mental illnesses. Data on the caregivers’ attitudes and other people’s attitudes toward individuals with mental disorders and their willingness to come in contact with people with mental disorders were collected.ResultsIn the three vignettes, caregivers agreed that positive outcomes outnumbered negative outcomes. The top two statements endorsing the stigma were “the person could snap out of the problem” and “people with this problem are dangerous.” In the section for perceived stigma, caregivers in the GAD vignette agreed that most people believed this problem is not a real medical illness, compared to schizophrenia. The rates of the statement endorsing unpredictability were significantly different in the schizophrenia (57.2%) and depression (45.5%) vignette, in comparison to the GAD (45.6%) vignette. For personal stigma, the caregivers tended to avoid people described in the depression vignette more often than in the GAD vignette. The caregivers were most unwilling to let the person described in the vignettes marry into their family, especially in the schizophrenia vignette.ConclusionDespite the stigma and desire for social distance associated with schizophrenia, depression, and GAD, caregivers often expect positive outcomes. Actions should be taken to improve caregivers’ knowledge about mental health and reduce the stigma

An Algorithm of Building Extraction in Urban Area Based on Improved Top-hat Transformations and LBP Elevation Texture

Classification of building and vegetation is difficult solely by LiDAR data and vegetation in shadows can't be eliminated only by aerial images. The improved top-hat transformations and local binary patterns (LBP) elevation texture analysis for building extraction are proposed based on the fusion of aerial images and LiDAR data. Firstly, LiDAR data is reorganized into grid cell, the algorithm removes ground points through top-hat transform. Then, the vegetation points are extracted by normalized difference vegetation index (NDVI). Thirdly, according to the elevation information of LiDAR points, LBP elevation texture is calculated and achieving precise elimination of vegetation in shadows or surrounding to the buildings. At last, morphological operations are used to fill the holes of building roofs, and region growing for complete building edges. The simulation is based on the complex urban area in Vaihingen benchmark provided by ISPRS, the results show that the algorithm affording higher classification accuracy

Inter-relationships of insomnia and psychiatric symptoms with suicidal ideation among patients with chronic schizophrenia: A network perspective

Background: Insomnia is common in patients with schizophrenia, which contributes to worsening psychiatric symptoms and suicidality. We aimed to assess the inter-relationships of insomnia and psychopathology with suicidal ideation (SI) among 1407 Chinese patients with chronic schizophrenia via the network approach.Method: We used Positive and Negative Syndrome Scale, Insomnia Severity Index, and Beck Scale for Suicidal Ideation to assess psychiatric symptoms, insomnia, and SI, respectively. Lifetime suicidal attempts (SA) were collected.Results: (1) The incidence of insomnia, lifetime SI, lifetime SA, and current SI was 13.5% (n = 190), 22.8% (n = 321), 13.5% (n = 190), and 9.7% (n = 136), respectively. (2) Patients with insomnia had worse clinical symptoms and higher suicidal risk. (3) Daytime dysfunction, sleep-related distress, conceptual disorganization, delusions, anxiety, and poor rapport were the core symptoms, while late sleep onset and sleep dissatisfaction emerged as bridge symptoms connecting insomnia and psychopathology. (4) Depressive mood, hallucinations, poor impulse control, guilty feelings, insomnia-related impaired quality of life, and sleep dissatisfaction were directly associated with SI.Conclusion: Our findings called for formal assessment of insomnia in patients with schizophrenia, which should cover both nocturnal and daytime insomnia symptoms. Targeted interventions for key symptoms may help reduce insomnia, psychiatric symptoms, and SI in patients with schizophrenia

Association between thyroid hormones and comorbid psychotic symptoms in patients with first-episode and drug-na?ve major depressive disorder

Thyroid dysfunction is common in major depressive disorder (MDD) patients; however, its relationship with psychotic depression (PD) remains unclear. We aimed to assess thyroid hormones in 1718 first episode drug naive (FEND) MDD patients and to determine their association with PD. The positive subscale of the Positive and Negative Symptom Scale (PANSS-P), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD) were used to detect clinical symptoms. The serum levels of free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH), anti-thyroglobulin (TgAb), and thyroid peroxidases anti-body (TPOAb) were assessed. The logistic regression model was conducted to determine risk factors for PD, and the Area Under the Curve (AUC) was used to test the performance of this model. 171 (10%) patients were identified as having PD. Serum levels of TSH, TgAb, and TPOAb displayed small-to-moderate associations with PANSS-P. HAMA score, HAMD score, and TSH levels were independently associated with PD. The regression model had excellent power to distinguish PD patients from non-PD patients with an AUC value of 0.93. Our study suggests TSH levels and severity of depression and anxiety symptoms were independent risk factors for PD. Regular thyroid function tests may help early detect PD.</p

Association between thyroid hormones and comorbid psychotic symptoms in patients with first-episode and drug-na?ve major depressive disorder

Thyroid dysfunction is common in major depressive disorder (MDD) patients; however, its relationship with psychotic depression (PD) remains unclear. We aimed to assess thyroid hormones in 1718 first episode drug naive (FEND) MDD patients and to determine their association with PD. The positive subscale of the Positive and Negative Symptom Scale (PANSS-P), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD) were used to detect clinical symptoms. The serum levels of free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH), anti-thyroglobulin (TgAb), and thyroid peroxidases anti-body (TPOAb) were assessed. The logistic regression model was conducted to determine risk factors for PD, and the Area Under the Curve (AUC) was used to test the performance of this model. 171 (10%) patients were identified as having PD. Serum levels of TSH, TgAb, and TPOAb displayed small-to-moderate associations with PANSS-P. HAMA score, HAMD score, and TSH levels were independently associated with PD. The regression model had excellent power to distinguish PD patients from non-PD patients with an AUC value of 0.93. Our study suggests TSH levels and severity of depression and anxiety symptoms were independent risk factors for PD. Regular thyroid function tests may help early detect PD

The prevalence and clinical correlates of anxiety in Chinese patients with first-episode and drug-naive major depressive disorder at different ages of onset

Background: Major depressive disorder (MDD) with comorbid anxiety is very common and is associated with worse clinical outcomes. MDD patients at different ages of onset may have different clinical features and asso-ciated factors. The aim of this study was to investigate the prevalence of anxiety and related factors in MDD patients at different ages of onset.Methods: A total of 1718 first-episode and drug-naive (FEDN) MDD patients were recruited. The cutoff point for early-adulthood onset (EAO) and mid-adulthood onset (MAO) was the first depressive episode before or after age 45 years. Clinical features (depressive, anxiety and psychiatric symptoms) and some metabolic parameters were collected.Results: There was no significant difference in the prevalence of anxiety between EAO patients (50.7 %) and MAO patients (55.7 %). For EAO patients, regression analysis showed that TSH levels, TgAb levels, and TC levels were significantly associated with anxiety. For MAO patients, regression analysis showed that anxiety was associated with HDL-c levels and impaired glucose metabolism. Furthermore, suicide attempts, psychotic symptoms, and depression severity were correlated with anxiety in both groups. Limitations: Our cross-sectional study cannot explain the causal relationship between anxiety and related factors in MDD patients at different ages of onset. Conclusions: This study revealed that the clinical characteristics and factors associated with anxiety in MDD patients differed according to age of onset, and therefore age of onset needs to be considered while treating anxiety.</p

Workplace violence inflicted by patients or their family members/visitors and its relationship with suicidal ideation among undergraduate medical students during clinical training in China

AbstractBackground Workplace violence in healthcare settings is a significant public concern that profoundly impacts healthcare workers. However, there is a dearth of knowledge regarding the prevalence of workplace violence and its correlation with suicidal ideation among undergraduate medical students in China during their clinical training. The objective of this study was to evaluate the prevalence of workplace violence inflicted by patients or their family members/visitors and to assess its association with suicidal ideation among undergraduate medical students.Method The snowballing sampling technique was used to recruit Chinese medical students. A question designed by the research team was used to ask medical students about their encounters with workplace violence. Students’ basic demographic information and mental distresses (learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence, excessive daytime sleepiness and history of mental disorders) were also assessed. As appropriate, the data were analysed using descriptive statistics, chi-square tests, independent-sample t-tests and multiple logistic regression.Results Out of the 1402 undergraduate medical students who participated, 493 (35.2%) reported having experienced workplace violence inflicted by patients or their family members/visitors, of which 394 (28.1%) were verbal abuse, 14 (1.0%) were physical aggression, and 85 (6.1%) were suffered from both verbal abuse and physical aggression. Furthermore, students exposed to workplace violence were more likely to report suicidal ideation and had a higher prevalence of learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence and excessive daytime sleepiness. Depression symptoms, history of mental disorders, learning burnout and having a partner were significantly associated with suicidal ideation in this population.Conclusion The prevalence of workplace violence inflicted by patients or their family members/visitors was high among undergraduate medical students in China. This may be associated with their mental distress and suicidal ideation. Consequently, it is crucial to strengthen workplace safety measures and promptly implement interventions to mitigate the potentially serious consequences

The prevalence and clinical correlates of anxiety in Chinese patients with first-episode and drug-naive major depressive disorder at different ages of onset

Background: Major depressive disorder (MDD) with comorbid anxiety is very common and is associated with worse clinical outcomes. MDD patients at different ages of onset may have different clinical features and asso-ciated factors. The aim of this study was to investigate the prevalence of anxiety and related factors in MDD patients at different ages of onset.Methods: A total of 1718 first-episode and drug-naive (FEDN) MDD patients were recruited. The cutoff point for early-adulthood onset (EAO) and mid-adulthood onset (MAO) was the first depressive episode before or after age 45 years. Clinical features (depressive, anxiety and psychiatric symptoms) and some metabolic parameters were collected.Results: There was no significant difference in the prevalence of anxiety between EAO patients (50.7 %) and MAO patients (55.7 %). For EAO patients, regression analysis showed that TSH levels, TgAb levels, and TC levels were significantly associated with anxiety. For MAO patients, regression analysis showed that anxiety was associated with HDL-c levels and impaired glucose metabolism. Furthermore, suicide attempts, psychotic symptoms, and depression severity were correlated with anxiety in both groups. Limitations: Our cross-sectional study cannot explain the causal relationship between anxiety and related factors in MDD patients at different ages of onset. Conclusions: This study revealed that the clinical characteristics and factors associated with anxiety in MDD patients differed according to age of onset, and therefore age of onset needs to be considered while treating anxiety