Dominicus L S, Oranje B, Otte W M, Ambrosen K S, Düring S, Scheepers F E, Stam C J, Glenthøj B Y, Ebdrup B H, van Dellen E
Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands.
Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Copenhagen University Hospital, Mental Health Center Glostrup, Glostrup, Denmark.
Schizophrenia (Heidelb). 2023 Jan 23;9(1):5. doi: 10.1038/s41537-022-00329-6.
Electroencephalography in patients with a first episode of psychosis (FEP) may contribute to the diagnosis and treatment response prediction. Findings in the literature vary due to small sample sizes, medication effects, and variable illness duration. We studied macroscale resting-state EEG characteristics of antipsychotic naïve patients with FEP. We tested (1) for differences between FEP patients and controls, (2) if EEG could be used to classify patients as FEP, and (3) if EEG could be used to predict treatment response to antipsychotic medication. In total, we studied EEG recordings of 62 antipsychotic-naïve patients with FEP and 106 healthy controls. Spectral power, phase-based and amplitude-based functional connectivity, and macroscale network characteristics were analyzed, resulting in 60 EEG variables across four frequency bands. Positive and Negative Symptom Scale (PANSS) were assessed at baseline and 4-6 weeks follow-up after treatment with amisulpride or aripiprazole. Mann-Whitney U tests, a random forest (RF) classifier and RF regression were used for statistical analysis. Our study found that at baseline, FEP patients did not differ from controls in any of the EEG characteristics. A random forest classifier showed chance-level discrimination between patients and controls. The random forest regression explained 23% variance in positive symptom reduction after treatment in the patient group. In conclusion, in this largest antipsychotic- naïve EEG sample to date in FEP patients, we found no differences in macroscale EEG characteristics between patients with FEP and healthy controls. However, these EEG characteristics did show predictive value for positive symptom reduction following treatment with antipsychotic medication.
首次发作精神病（FEP）患者的脑电图检查可能有助于诊断及预测治疗反应。由于样本量小、药物影响和病程长短不一，文献中的研究结果存在差异。我们研究了未服用抗精神病药物的FEP患者的宏观静息态脑电图特征。我们测试了：（1）FEP患者与对照组之间的差异；（2）脑电图是否可用于将患者分类为FEP；（3）脑电图是否可用于预测对抗精神病药物的治疗反应。我们总共研究了62例未服用抗精神病药物的FEP患者和106名健康对照者的脑电图记录。分析了频谱功率、基于相位和基于幅度的功能连接以及宏观网络特征，得出四个频段的60个脑电图变量。在使用氨磺必利或阿立哌唑治疗后的基线及4 - 6周随访时评估阳性和阴性症状量表（PANSS）。采用曼 - 惠特尼U检验、随机森林（RF）分类器和RF回归进行统计分析。我们的研究发现，在基线时，FEP患者在任何脑电图特征方面与对照组均无差异。随机森林分类器显示患者与对照组之间的辨别率处于随机水平。随机森林回归解释了患者组治疗后阳性症状减轻方面23%的方差。总之，在迄今为止FEP患者中最大的未服用抗精神病药物的脑电图样本中，我们发现FEP患者与健康对照者在宏观脑电图特征方面无差异。然而，这些脑电图特征确实显示出对抗精神病药物治疗后阳性症状减轻的预测价值。
