Área de Psiquiatría, Universidad de Oviedo, Oviedo, Spain.
Servicio de Salud del Principado de Asturias (SESPA), Oviedo, Spain.
Eur Psychiatry. 2022 Jun 10;65(1):e33. doi: 10.1192/j.eurpsy.2022.25.
Network analysis has been used to explore the interplay between psychopathology and functioning in psychosis, but no study has used dedicated statistical techniques to focus on the bridge symptoms connecting these domains. The current study aims to estimate the network of depressive, negative, and positive symptoms, general psychopathology, and real-world functioning in people with first-episode schizophrenia or schizophreniform disorder, focusing on bridge nodes.
Baseline data from the OPTiMiSE trial were analyzed. The sample included 446 participants (age 40.0 ± 10.9 years, 70% males). The network was estimated with a Gaussian graphical model, using scores on individual items of the positive and negative syndrome scale (PANSS), the Calgary depression scale for schizophrenia, and the personal and social performance scale. Stability, strength centrality, expected influence (EI), predictability, and bridge centrality statistics were computed. The top 20% scoring nodes on bridge strength were selected as bridge nodes.
Nodes from different rating scales assessing similar psychopathological and functioning constructs tended to cluster together in the estimated network. The most central nodes (EI) were Delusions, Emotional Withdrawal, Depression, and Depressed Mood. Bridge nodes included Depression, Conceptual Disorganization, Active Social Avoidance, Delusions, Stereotyped Thinking, Poor Impulse Control, Guilty Feelings, Unusual Thought Content, and Hostility. Most of the bridge nodes belonged to the general psychopathology subscale of the PANSS. Depression (G6) was the bridge node with the highest value.
The current study provides novel insights for understanding the complex phenotype of psychotic disorders and the mechanisms underlying the development and maintenance of comorbidity and functional impairment after psychosis onset.
网络分析已被用于探索精神病学中的精神病理学和功能之间的相互作用，但尚无研究使用专门的统计技术来关注连接这些领域的桥梁症状。本研究旨在估计首发精神分裂症或分裂情感障碍患者的抑郁、阴性和阳性症状、一般精神病学和现实世界功能的网络，重点关注桥梁节点。
对 OPTiMiSE 试验的基线数据进行了分析。该样本包括 446 名参与者（年龄 40.0±10.9 岁，70%为男性）。使用阳性和阴性症状量表（PANSS）、精神分裂症的卡尔加里抑郁量表和个人和社会表现量表的个体项目得分，使用高斯图形模型估计网络。计算了稳定性、强度中心度、预期影响（EI）、可预测性和桥梁中心度统计数据。选择得分在前 20%的桥梁强度节点作为桥梁节点。
来自评估相似精神病理和功能结构的不同评分量表的节点倾向于在估计的网络中聚集在一起。最中心的节点（EI）是妄想、情感退缩、抑郁和抑郁情绪。桥梁节点包括抑郁、概念性思维障碍、主动社交回避、妄想、刻板思维、冲动控制差、内疚感、异常思维内容和敌意。大多数桥梁节点属于 PANSS 的一般精神病学子量表。抑郁（G6）是具有最高值的桥梁节点。
本研究为理解精神病障碍的复杂表型以及精神病发作后共病和功能障碍发展和维持的机制提供了新的见解。
