ObjectiveTo explore the clinical characteristics of epilepsy and depression patients, and provide guidance for clinical intervention of epilepsy and depression patients.MethodsPatients with epilepsy (epilepsy group) were prospectively enrolled in Emeishan People’s Hospital from 2015 to 2017, and healthy controls (control group) were enrolled in the same period. Clinical assessment of depression was conducted and compared between the two groups. In the epilepsy group, the severity and incidence of depression were analyzed and compared among different subgroups according to the epileptic seizure type, frequency and course.ResultsA total of 120 patients and 70 healthy controls were enrolled. The Hamilton Depression Scale score of epilepsy group was higher than that of the control group (t=7.430, P<0.001), and the depression degree of epilepsy group was significantly higher than that of the control group (Z=−4.371, P< 0.001). There was no significant difference in depression rating between convulsive epilepsy patients and partial epilepsy patients (Z=−1.591, P=0.112); there was no significant difference in depression rating among patients with different epilepsy course (χ2=1.943, P=0.584); there was significant difference in depression rating among patients with different seizure frequency (χ2=27.575, P<0.001). Patients with high frequency of seizures were more likely to suffer from depression and severe depression, with the lowest proportion of normal neuropsychological state. Conversely, patients with low frequency of epileptic seizures had a lower proportion of depression and severe depression.ConclusionsThe incidence of depression in epilepsy patients is higher than that in normal people. Timely detection and treatment of depression in clinical work have a positive impact on the prognosis of patients.
目的 探讨糖耐量异常患者的焦虑抑郁状况及其与生活质量的相关性，为糖尿病相关心理问题的早期识别与干预提供参考。 方法 以2010年1月－2012年6月糖耐量异常患者145例为试验组，健康人群147例作为对照组，两组分别填写焦虑自评量表（SAS）和抑郁自评量表（SDS），试验组还需填写世界卫生组织生活质量测定量表简表（WHOQOL-BREF）并对其焦虑、抑郁得分与WHOQOL-BREF的各因子的相关性进行分析。 结果 145例患者中有51例（35.2%）存在抑郁情绪，47例（32.4%）存在焦虑情绪，焦虑合并抑郁情绪者29例（20%）。糖耐量异常患者焦虑、抑郁评分明显高于对照组（P＜0.01），其生活质量多个领域评分低于对照组（P＜0.01），且生活质量与焦虑、抑郁情绪存在负相关（P＜0.05）。 结论 糖耐量异常患者焦虑、抑郁情绪明显高于正常人群，其生活质量偏低，提示了对在该人群进行早期心理干预的必要性。
ObjectiveTo investigate the status of quality of life and influencing factors among newly diagnosed epilepsy patients with co-morbid anxiety and depression. MethodsA total of 180 newly diagnosed epilepsy patients from June 2022 to December 2022 in a district of Shanghai were selected as the study subjects. The Quality of Life in Epilepsy-31 (QOLIE-31), Hamilton Depression Rating Scale (HAMD-24), Hamilton Anxiety Rating Scale (HAMA), and Epilepsy Self-Management Scale (ESMS) were used to assess patients' quality of life, depression levels, anxiety levels, and self-management abilities, respectively. Patients were divided into the co-morbid depression group (HAMA≥14 and HAMD>17) and the control group (HAMA<14 and HAMD≤17), and their general characteristics and scale scores were compared. Spearman correlation, Pearson correlation, and multiple linear regression analysis were used to identify influencing factors of quality of life in epilepsy patients with co-morbid depression. ResultsCompared to the control group, the anxiety comorbid with depression group of older adults had a higher proportion, higher unemployment rate, lower personal and family annual income in the past year, higher frequency of epileptic seizures, and lower medication adherence (P<0.05). The correlational analysis revealed a negative correlation between the quality of life abilities of epilepsy patients with comorbid anxiety and depression and the severity of anxiety and depression. (r=−0.589, −0.620, P<0.05). The results of multiple linear regression analysis showed that the frequency of seizures in the past year (β=−1.379, P<0.05), severity of anxiety (β=−0.279, P<0.05), and severity of depression (β=−0.361, P<0.05) have an impact on the ability to quality of life in epilepsy patients with co-morbid anxiety and depression. These factors account for 44.1% of the total variability in quality of life (R2=0.4411, P<0.05). ConclusionThe frequency of seizures in the past year, as well as the severity of anxiety and depression, are important factors that influence the ability to quality of life in epilepsy patients with comorbid anxiety and depression. For these patients, it is crucial to take into account these factors and provide appropriate support and interventions.
ObjectiveTo investigate the fatigue of asthma patients, and to analyze its influencing factors, and provide a reference for clinical intervention.MethodsThe convenience sampling method was adopted to select asthma patients who were in clinic of the First Affiliated Hospital of Guangxi Medical University from November 2018 to March 2019. The patients’ lung function were measured. And questionnaires were conducted, including general data questionnaire, Chinese version of Checklist Individual Strength-Fatigue, Asthma Control Test, Chinese version of Self-rating Depression Scale. Relevant data were collected for multiple stepwise linear regression analysis.ResultsFinally, 120 patients were enrolled. The results of multiple stepwise linear regression analysis showed that age, education level, place of residence, time period of frequent asthma symptoms, degree of small airway obstruction, Asthma Control Test score and degree of depression were the influencing factors of fatigue in asthma patients (P≤0.05). Multivariate linear stepwise regression analysis showed that degree of small airway obstruction, degree of depression and time period of frequent asthma symptoms were the main influencing factors of fatigue in asthma patients, which could explain 51.8% of the variance of fatigue (ΔR2=0.518).ConclusionsThe incidence of fatigue in asthma patients is at a relatively high level. Medical staff should pay attention to the symptoms of fatigue in asthma patients. For asthma patients, it is recommended to strengthen standardized diagnosis and treatment, reduce the onset of symptoms at night and eliminate small airway obstruction. Psychological intervention methods are needed to improve patients’ depression, reduce fatigue symptoms, and improve quality of life.
Objective Depression is a common consequence after stroke and has become a significant issue in clinical practice and research. The aim of this study was to explore associated factors of post-stroke depression among first-ever stroke patients in Hong Kong. Methods A longitudinal study was conducted to collect data in face-to-face interviews and by physical assessment at two time points: T1, within 48 hours of admission to a rehabilitation hospital; and T2, 6 months after the first interview. T2 interviews and assessments were conducted in the participant’s current place of residence. Participants were first-ever stroke patients in Hong Kong. Post-stroke depression was measured using the Center of Epidemiological Study-Depression (CES-D) Scale. Backward linear regression analysis was performed to examine factors associated with level of post-stroke depression at T2. Results Our findings showed that 69% of participants exhibited clinically relevant levels of depressive symptoms at T1 and 48% at T2. Regression analysis revealed complex relationships between the level of depressive symptoms, demographic characteristics and variations in perceived levels of social support. Five variables were found to explain 55% of the variance in depressive symptoms at T2. The variables with significant standardized regression coefficients (β) were: companionship (P=0.001), informational support (P=0.025), baseline level of depressive symptoms (Plt;0.001), ADL dependence level (Plt;0.001) and being a homemaker before the stroke (P=0.039). Conclusions We have followed a group of stroke patients over a 6-month period. Our findings suggest that when screening for post-stroke depression, health professionals must take into consideration of the clinical, socio-personal characteristics that might increase a stroke patient’s vulnerability to develop depression after stroke.
Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.
To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (P < 0.05). Next, using the relationship between multiple thresholds and network parameters, the area under the curve (AUC) of each network parameter was extracted as new features (P < 0.05). Finally, support vector machine (SVM) was used to classify the two groups with the network parameters and their AUC as features. The study results show that with strength, average characteristic path length, and average clustering coefficient as features, the classification accuracy in the θ band is increased from 69% to 71%, 66% to 77%, and 50% to 68%, respectively. In the α band, the accuracy is increased from 72% to 79%, 69% to 82%, and 65% to 75%, respectively. And from overall view, when AUC of network parameters was used as a feature in the α band, the classification accuracy is improved compared to the network parameter feature. In the θ band, only the AUC of average clustering coefficient was applied to classification, and the accuracy is improved by 17.6%. The study proved that based on graph theory, the method of feature optimization of brain function network could provide some theoretical support for the computer-aided diagnosis of adolescent depression.
Objectives To evaluate the effectiveness of different antidepressant drugs in addition to standard clinical care in the prevention of postnatal depression. To compare the effectiveness of different antidepressant drugs and with any other form of intervention for postnatal depression i.e. hormonal, psychological or social support. To assess any adverse effects of antidepressant drugs in either the mother or the foetus/infant.Methods The register of clinical trials maintained and updated by the Cochrane Depression, Anxiety and Neurosis Group and the Cochrane Pregnancy and Childbirth Group.Randomised studies of antidepressants alone or in combination with another treatment, compared with placebo or a psychosocial intervention in non-depressed pregnant women or women who had given birth in the previous six weeks (i.e. women at risk of postnatal depression). Data were extracted independently from the trial reports by the authors.Missing information was requested from investigators wherever possible. Data were sought to allow an intention to treat analysis.Results Two trials fullled the inclusion criteria for this review. Both looked at women with a past history of postpartum depression.Nortriptyline (n=26) did not show any benefit over placebo (n=25). Sertraline (n=14) reduced the recurrence of postnatal depression and the time to recurrence when compared with placebo (n=8). Intention to treat analyses were not carried out in either trial.Conclusions It is not possible to draw any clear conclusions about the effectiveness of antidepressants given immediately postpartum in preventing postnatal depression and, therefore, cannot be recommended for prophylaxis of postnatal depression, due to the lack of clear evidence. Larger trials are needed which also include comparisons of antidepressant drugs with other prophylactic treatments to reect clinical practice, and examine adverse effects for the foetus and infant, as well as assess womens’ attitudes to the use of antidepressants at this time.
ObjectiveTo systematically review the effect of different psychological intervention methods on depressive symptoms in patients with inflammatory bowel disease. MethodsPubMed, Embase, Cochrane Library, Web of Science, CNKI, WanFang Data, VIP and CBM databases were electronically searched to collect randomized controlled trials(RCTs) on psychological interventions on depression of patients with inflammatory bowel disease from inception to January 12, 2023. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. Network meta-analysis was then conducted by using software Stata and GeMTC. ResultsA total of 18 articles, 1 567 patients and 6 psychological intervention methods were included. The results of the network meta-analysis showed that, compared with conventional nursing, music therapy, mindfulness therapy and cognitive behavioral therapy had statistically significant differences in the intervention effect of depression in patients with inflammatory bowel disease (P<0.05); Among the six psychological intervention methods included, there was a statistically significant difference in relaxation therapy compared with music therapy, writing expression and mindfulness therapy (P<0.05); The difference between cognitive behavioral therapy and music therapy and mindfulness therapy was statistically significant (P<0.05), while there was no statistically significant difference in other interventions (P>0.05). The SUCRA ranking probability chart showed that music therapy was the best intervention method for depression in patients with inflammatory bowel disease, followed by mindfulness therapy and cognitive behavioral therapy. ConclusionThe current evidence suggests that music therapy has an advantage in relieving depression in patients with inflammatory bowel disease, followed by mindfulness therapy or cognitive behavioral therapy. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.