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首发精神病患者精神分裂症的预测因子。

Predictors of schizophrenia in patients with a first episode of psychosis.

机构信息

Department of Psychiatry, Hospital San Rafael, Barcelona, Spain.

出版信息

Psychiatry Res. 2010 Jan 30;175(1-2):11-4. doi: 10.1016/j.psychres.2009.03.013.

Abstract

Early identification of schizophrenia in patients with a first episode of psychosis (FEP) may help to avoid inappropriate treatment and may enhance long-term outcome by addressing issues such as family network, treatment adherence and functional and symptomatic outcome. It was the aim of the study to determine baseline variables that significantly predicted a diagnosis of schizophrenia in patients with FEP. The sample consisted of 133 FEP patients hospitalized for at least 6 weeks, in whom a DSM-IV diagnosis was confirmed after 1 year follow-up. Patients were divided into two groups, those with a diagnosis of schizophrenia (Schizophrenia group, n=63; 47.8%), and those with other psychosis, who were grouped under Non-Schizophrenic Psychosis (NSP, n=70; 52.2%). Sociodemographic (marital status, educational level) and clinical variables were recorded for each patient. Substance use (alcohol, cannabis and cocaine) did not statistically differ between the two groups. Absence of characteristics defined as criteria for good prognosis, lack of > or = 20% improvement in the total Positive and Negative Syndrome Scale score at 6 weeks, and a poor premorbid adjustment as determined by the Premorbid Adjustment Scale score significantly predicted the presence of schizophrenia. The regression model including these three variables achieved a predictive value of 76.3%, with a sensitivity of 74.6% and a specificity of 77.9%.

摘要

首发精神病患者(FEP)的精神分裂症早期识别有助于避免不适当的治疗,并通过解决家庭网络、治疗依从性以及功能和症状结果等问题来改善长期预后。本研究旨在确定基线变量,这些变量可显著预测 FEP 患者的精神分裂症诊断。该样本包括 133 名至少住院 6 周的 FEP 患者,在 1 年随访后,通过 DSM-IV 诊断得到确认。将患者分为两组,一组诊断为精神分裂症(精神分裂症组,n=63;47.8%),另一组诊断为其他精神病,归为非精神分裂症精神病组(NSP,n=70;52.2%)。记录每位患者的社会人口统计学(婚姻状况、教育程度)和临床变量。两组之间的物质使用(酒精、大麻和可卡因)无统计学差异。缺乏被定义为预后良好标准的特征、6 周时阳性和阴性综合征量表总分改善程度>或=20%、以及通过前病调整量表评分确定的前病调整不良,这些都显著预测了精神分裂症的存在。包括这三个变量的回归模型达到了 76.3%的预测值,灵敏度为 74.6%,特异性为 77.9%。

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