Negative psychotic symptoms and impaired role functioning predict transition outcomes in the at-risk mental state: a latent class cluster analysis study
Negative psychotic symptoms and impaired role functioning predict transition outcomes in the at-risk mental state: a latent class cluster analysis study
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DOI：
10.1017/s0033291713000251
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发表时间：
2013-11-01
影响因子：
6.9
通讯作者：
McGuire, P. K.
中科院分区：
文献类型：
--
作者：
Valmaggia, L. R.;Stahl, D.;McGuire, P. K.
背景许多研究小组试图预测哪些具有精神病风险精神状态（ARMS）的个体以后会发展为精神病性障碍。然而，很难根据个体症状评分来预测病程和结局。从318 ARMS个人从两个专业服务ARMS科目的数据进行了分析，使用潜在类聚类分析（LCCA）。采用危险心理状态综合评定量表（CAARMS）评分，探讨潜在类别的数量、规模和症状特征。LCCA产生了四个高风险类别，在2年随访后删失：1类（轻度）具有最低的转换风险（4.9%）。该组受试者在所有CAARMS项目上的得分最低，他们更年轻，更有可能是学生，并且具有最高的整体功能评估（GAF）得分。2级（中度）受试者的转换风险为10.9%，在所有CAARMS项目中得分中等，更有可能就业。3级（中度-重度）患者的转换风险为11.4%，CAARMS评分为中度重度。4级（严重）的受试者有最高的过渡风险（41.2%），他们在CAARMS上得分最高，GAF得分最低，更有可能失业。总的来说，4级是最好的区别于其他类的失语症，无意志/冷漠，快感缺乏，社会孤立和受损的角色功能。不同类型的症状与2年随访时过渡风险的显著差异相关。症状聚类比单个症状更能预测预后。
Background. Many research groups have attempted to predict which individuals with an at-risk mental state (ARMS) for psychosis will later develop a psychotic disorder. However, it is difficult to predict the course and outcome based on individual symptoms scores.Method. Data from 318 ARMS individuals from two specialized services for ARMS subjects were analysed using latent class cluster analysis (LCCA). The score on the Comprehensive Assessment of At-Risk Mental States (CAARMS) was used to explore the number, size and symptom profiles of latent classes.Results. LCCA produced four high-risk classes, censored after 2 years of follow-up: class 1 (mild) had the lowest transition risk (4.9%). Subjects in this group had the lowest scores on all the CAARMS items, they were younger, more likely to be students and had the highest Global Assessment of Functioning (GAF) score. Subjects in class 2 (moderate) had a transition risk of 10.9%, scored moderately on all CAARMS items and were more likely to be in employment. Those in class 3 (moderate-severe) had a transition risk of 11.4% and scored moderately severe on the CAARMS. Subjects in class 4 (severe) had the highest transition risk (41.2%), they scored highest on the CAARMS, had the lowest GAF score and were more likely to be unemployed. Overall, class 4 was best distinguished from the other classes on the alogia, avolition/apathy, anhedonia, social isolation and impaired role functioning.Conclusions. The different classes of symptoms were associated with significant differences in the risk of transition at 2 years of follow-up. Symptomatic clustering predicts prognosis better than individual symptoms.