ObjectiveTo integrate person imagery from drawing tests in screening for mental disorders through meta-analysis to identify indicators that can effectively predict mental disorders. MethodsA computerized search of CNKI, WanFang Data, VIP, PubMed, Web of Science, and EBSCO databases was conducted to collect studies related to mental disorders and drawing tests, with a search timeframe of the period from the creation of the database to May 8, 2023. Meta-analysis was performed using CMA 3.0 after two researchers independently screened the literature, extracted information, and assessed the risk of bias. ResultsA total of 43 studies were included, with 791 independent effect sizes and 8 444 subjects. Meta-analysis revealed that a total of 29 person imagery traits significantly predicted mental disorders, which could be categorized into 7 types according to the features: absent, bizarre, blackened, simplified, static, detailed, and holistic. The subgroup analysis revealed that the specific indicators of affective disorders included "excessive separation among items", "oversimplified person", "rigid and static person" and "hands behind the back". The specific indicators of thought disorders were "absence of limbs", "absence of facial features" and "disproportionate body proportions". Moreover, there were seven common indicators of mental disorders, including "oversimplified drawing", "very small drawing", "very small person", "weak or intermittent lines", "single line limb", "absence of hands or feet" and "no expression or dullness''. ConclusionThe findings could provide a reference standard for selection and interpretation of drawing indicators, promote standardization of the drawing test, and enhance the accuracy of results in screening for mental disorders.
目的:探讨被误诊为功能性精神障碍的麻痹性痴呆患者的临床特点和诊治要点。方法:回顾性分析10例被误诊为功能性精神障碍的麻痹性痴呆患者的临床资料。结果:被误诊为功能性精神障碍的麻痹性痴呆均以精神症状为首发，多表现为精神病性症状、类躁狂、抑郁、类神经症、人格的改变及进行性痴呆等不典型症状群，本研究显示误诊率高达71.4%，误诊例次率以精神分裂症最高（47.3%），其次为躁狂症或躁狂状态（37.5%）。抗精神病药物能有效改善精神症状，青霉素驱梅能阻止病情进展使病情得到缓解，两者缺一不可。结论:被误诊为功能性精神障碍的麻痹性痴呆均以精神症状为首发且症状不典型而易被误诊，早期鉴别诊断十分重要，抗精神病药物和青霉素治疗可以有效控制症状。
The causes of mental disorders are complex, and early recognition and early intervention are recognized as effective way to avoid irreversible brain damage over time. The existing computer-aided recognition methods mostly focus on multimodal data fusion, ignoring the asynchronous acquisition problem of multimodal data. For this reason, this paper proposes a framework of mental disorder recognition based on visibility graph (VG) to solve the problem of asynchronous data acquisition. First, time series electroencephalograms (EEG) data are mapped to spatial visibility graph. Then, an improved auto regressive model is used to accurately calculate the temporal EEG data features, and reasonably select the spatial metric features by analyzing the spatiotemporal mapping relationship. Finally, on the basis of spatiotemporal information complementarity, different contribution coefficients are assigned to each spatiotemporal feature and to explore the maximum potential of feature so as to make decisions. The results of controlled experiments show that the method in this paper can effectively improve the recognition accuracy of mental disorders. Taking Alzheimer's disease and depression as examples, the highest recognition rates are 93.73% and 90.35%, respectively. In summary, the results of this paper provide an effective computer-aided tool for rapid clinical diagnosis of mental disorders.
The interaction mechanism between mental disorders and diabetes is complex, involving genetics, endocrine metabolism, inflammation, oxidative stress and other aspects, which makes it difficult to treat patients with mental disorders complicated by diabetes. Such patients mostly use drugs and non-drug interventions to relieve symptoms of mental disorders and improve blood sugar levels, but the mechanism of mental disorders and diabetes needs to be systematically summarized and needs practical means to intervene. This article starts with the pathogenesis of diabetes and then describes the interaction mechanism of schizophrenia, bipolar disorder, depression and diabetes in detail. Finally, the intervention measures for patients with mental disorders complicated by diabetes are summarized, which aims to provide a reference for medical staff engaged in related work.
ObjectiveTo explore the related factors and nursing countermeasures for psychonosema in postoperative laryngeal cancer patients. MethodsWe retrospectively analyzed the clinical data of eight patients who accepted laryngectomy and developed psychonosema from January 2008 to April 2013. The related factors for psychonosema in these patients were analyzed and nursing countermeasures were summarized. ResultsEight patients had different degree of psychonosema, and it was correlated with psychological factors, various channels of undesirable stimulation, sleep disorders, drug and other factors. After treatment and careful nursing, within three to seven days, all patients' abnormal mental symptoms were alleviated, and all of them were discharged. ConclusionThere are many factors which can cause psychonosema after laryngectomy for laryngeal carcinoma. Medical staff should try to reduce or avoid inducing factors. Once it happens, medical staff should carry out psychiatric treatment in time to avoid accidents and promote the rehabilitation of patients.
Mental disorders are a type of behavioral, emotional, cognitive, or thinking disorder that cause pain and social dysfunction, and are one of the top ten global disease burdens. Cannabidiol (CBD) is one of the main components of cannabis, with high safety and tolerability, and is a hot topic in drug research. CBD has a wide range of therapeutic effects, and research has found that CBD has neuropsychiatric effects such as anti-addiction, anti-depression, anti-anxiety, and anti-stress, making it one of the candidate drugs for mental disorders. This article summarizes the mechanism and research progress of CBD for major mental disorders, in order to provide useful references for CBD-related compounds in the treatment of mental disorders.
ObjectiveTo compare the application of self-made tumble risk factors assessment scale before and after its revision in patients with mental disorder, in order to guide the clinical work. MethodsWe retrospectively analyzed the clinical data of 2 209 patients with mental disorders who were discharged from the hospital between January 1, 2012 and December 31, 2013. All the patients in our hospital underwent the assessment by "table of tumble risk factors for hospitalized patients and nursing measures" within one hour of admission. A total score of 4 or higher meant high tumble risk, and the standardized intervention measures were taken immediately. In 2013, the assessment scale was revised, and binocular vision disorder, low compliance or communication disorders, restlessness were added as risk factors for tumble. The difference among patients with a tumble score of 4 or higher between the year of 2012 and 2013 was compared and analyzed. ResultsIn 2012, 52 patients had a tumble score of 4 or higher, among whom there were 16 males and 36 females; 35 were younger than 65 years old and 17 were older than 65 years. There were 25 patients with organic mental disorders, 10 with spirit obstacle caused by active substance, 12 with schizophrenia, and 5 other cases. In 2013, 154 patients' tumble score was 4 or higher, among whom there were 58 males and 96 females; 142 were younger than 65 years old and 12 were older than 65. Organic mental disorders occurred in 22 patients, 8 had spirit obstacle caused by active substance, 120 had schizophrenia, and there were 4 other cases. In 2013, the number of patients with a tumble score of 4 or higher were significantly more than that in 2012 and young patients with schizophrenia were also significantly more than in 2012 (P<0.05). There were two cases of tumble adverse events, while no adverse events occurred in tumble in 2013. ConclusionCognitive impairment, low compliance, communication barriers and restlessness are high risk factors for tumble in patients with mental disorders. Correct evaluation and early intervention can effectively prevent the occurrence of tumble.