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Predictors of remission during acute treatment of first‐episode schizophrenia patients involuntarily hospitalized and treated with algorithm‐based pharmacotherapy: Secondary analysis of an observational study

机译:急性治疗急性治疗急性治疗患者的缓解预测因素,并用基于算法的药物治疗方法:次要观察研究的二次分析

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Aim Early clinical response predicts symptomatic remission and recovery in the maintenance treatment phase of first‐episode schizophrenia (FES). However, little is known about predictors of symptomatic remission during acute treatment of severely ill patients with FES. Here, we conducted a secondary analysis of our retrospective observational study, which examined response, remission and treatment‐resistance rates in seriously ill patients with FES spectrum disorders involuntarily hospitalized and treated with algorithm‐based pharmacotherapy. Methods We performed a retrospective chart review of 131 involuntarily admitted patients with schizophrenia or schizoaffective disorder. Our algorithm aimed to delay olanzapine treatment, standardize medications and suggest initiation of clozapine after failure of third‐line antipsychotic treatment. The duration of each adequate antipsychotic treatment at an optimal dosage was 4 weeks or more. Remission was defined using the symptom‐severity component of consensus remission criteria. A logistic regression model was applied to identify significant predictors of remission at discharge. Results Overall, 74 patients (56%) were in remission at discharge. Non‐remitters were hampered from becoming remitters mainly by the presence of negative symptoms. There were no differences in first‐line antipsychotics, dosage of antipsychotics at time of response and adherence rates to algorithm‐based pharmacotherapy between remitters and non‐remitters. Shorter duration of untreated psychosis, favourable early response and less negative symptoms at baseline were identified as independent predictors of remission at discharge. Conclusions The importance of early intervention and specific and adequate treatments of negative symptoms is highlighted.
机译:目的早期临床反应预测第一发表精神分裂症(FES)的维持治疗阶段的症状缓解和恢复。然而,对于急性治疗FES患者的急性治疗期间,对症状缓解的预测因子很少。在这里,我们对我们的回顾性观察研究进行了次要分析,其研究了严重病患患者的反应,缓解和治疗抵抗率,其FES Spectrum患者不由自主地住院治疗和用算法的药物治疗治疗。方法我们执行了131名不由自主地录取的精神分裂症或精神分裂症患者的回顾图审查。我们的算法旨在延迟奥氮平治疗,标准化药物,并在第三线抗精神病药治疗失败后表达氯氮平的启动。在最佳剂量下每种足够的抗精神病药治疗的持续时间为4周或更长时间。使用共识缓解标准的症状严重组成部分定义缓解。应用逻辑回归模型来确定放电缓解的重要预测因子。结果总体而言,74名患者(56%)在排出时进行了缓解。非汇总者因存在消极症状而被阻碍成为瑞士植物学系。一线抗精神病药物没有差异,在乳渣和非汇总的算法的算法的药物治疗时,抗精神病药剂量没有差异。未经治疗的精神病持续时间较短,有利的早期反应和基线的阴性症状被鉴定为放电缓解的独立预测因子。结论突出了早期干预和特异性和充分治疗的负面症状的重要性。

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