精神分裂症(面向对象编程)
奎硫平
阳性与阴性症状量表
利培酮
心理学
精神科
非定型抗精神病薬
抗精神病药
临床心理学
精神病
作者
Yaoyao Sun,Yuyanan Zhang,Zhe Lu,Hao Yan,Liangkun Guo,Yundan Liao,Tianlan Lu,Lifang Wang,Jun Li,Wenqiang Li,Yongfeng Yang,Hao Yu,Luxian Lv,Dai Zhang,Wenjian Bi,Weihua Yue
标识
DOI:10.1093/schbul/sbac131
摘要
Complex schizophrenia symptoms were recently conceptualized as interactive symptoms within a network system. However, it remains unknown how a schizophrenia network changed during acute antipsychotic treatment. The present study aimed to evaluate the interactive change of schizophrenia symptoms under seven antipsychotics from individual time series.Data on 3030 schizophrenia patients were taken from a multicenter randomized clinical trial and used to estimate the partial correlation cross-sectional networks and longitudinal random slope networks based on multivariate multilevel model. Thirty symptoms assessed by The Positive and Negative Syndrome Scale clustered the networks.Five stable communities were detected in cross-sectional networks and random slope networks that describe symptoms change over time. Delusions, emotional withdrawal, and lack of spontaneity and flow of conversation featured as central symptoms, and conceptual disorganization, hostility, uncooperativeness, and difficulty in abstract thinking featured as bridge symptoms, all showing high centrality in the random slope network. Acute antipsychotic treatment changed the network structure (M-test = 0.116, P < .001) compared to baseline, and responsive subjects showed lower global strength after treatment (11.68 vs 14.18, S-test = 2.503, P < .001) compared to resistant subjects. Central symptoms and bridge symptoms kept higher centrality across random slope networks of different antipsychotics. Quetiapine treatment network showed improvement in excitement symptoms, the one featured as both central and bridge symptom.Our findings revealed the central symptoms, bridge symptoms, cochanging features, and individualized features under different antipsychotics of schizophrenia. This brings implications for future targeted drug development and search for pathophysiological mechanisms.
科研通智能强力驱动
Strongly Powered by AbleSci AI