ObjectiveTo systematically review the efficacy of different drugs for patients with methamphetamine-induced psychotic disorders by network meta-analysis.MethodsAn electronical search was conducted in PubMed, The Cochrane Library, Web of Science, EMbase, CNKI, CBM, WanFang Data and VIP databases from inception to October 2016 to collect randomized controlled trials (RCTs) about different drugs for methamphetamine-induced psychotic disorders. Two reviewers independently screened literature, extracted data and assessed the risk bias of included studies, and then RevMan 5.3, R 3.3.2 and JAGS 4.2.0 softwares were used to perform network meta-analysis.ResultsA total of 16 RCTs involving 1 676 patients and 9 kinds of drugs were included. The results of network meta-analysis showed that: compared with the placebo group, olanzapine (OR=28.00, 95%CI 8.10 to 110.00), risperidone (OR=20.00, 95%CI 7.70 to 58.00), quetiapine (OR=30.00, 95%CI 6.60 to 160.00), ziprasidone (OR=28.00, 95%CI 3.70 to 230.00), chlorpromazine (OR=29.00, 95%CI 5.00 to 200.00), aripiprazole (OR=13.00, 95%CI 1.70 to 93.00), haloperidol (OR=19.00, 95%CI 2.10 to 190.00) could significantly improve the psychotic disorders of patients with methamphetamine, respectively, in which quetiapine was the best choice. There were no significant differences between any other pairwise comparisons of these different drugs.ConclusionFor the treatment of psychotic disorders caused by methamphetamine, quetiapine should be of a priority choice, follows by ziprasidone, chlorpromazine, olanzapine, risperidone, aripiprazole or haloperidol in a descending priority. Due to limited quality and quantity of the included studies, more high-quality studies are needed to verify above conclusion.
摘要:目的:探讨重型颅脑损伤后早期精神障碍临床特征及治疗方法,以提高患者的生活质量。方法:对我院48例重型颅脑损伤后早期精神障碍患者进行回顾性分析,观察精神障碍出现的时间、精神障碍的类型及预后及颅脑损伤的部位与精神障碍的关系。结果:重型颅脑损伤后精神障碍主要出现在伤后3周内,多继发于颞叶损伤,其次为额叶。临床上主要有躁狂型、抑郁型、痴呆型、精神分裂性等四型,其中以躁狂型为多见。通过治疗后,lt;1个月精神症状痊愈25例、lt;2个月痊愈13例、治疗gt;2个月仍有精神症状10例。结论:颅脑损伤后精神障碍在原发脑损伤的有效治疗前提下,辅以抗精神障碍药物治疗、心理治疗及高压氧治疗等可取得较好疗效。
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 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.
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.
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.