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首页> 外文期刊>The Journal of neuropsychiatry and clinical neurosciences >Pilot Study of An Intracranial Electroencephalography Biomarker of Depressive Symptoms in Epilepsy.
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Pilot Study of An Intracranial Electroencephalography Biomarker of Depressive Symptoms in Epilepsy.

机译:癫痫抑郁症状颅骨脑脑血管术生物标志物的试验研究。

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摘要

Adult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy. The authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region. Principal component 3 was a statistically significant predictor of the presence of depressive symptoms (R~(2)=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power. These finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.
机译:成年患者癫痫患者对主要抑郁症(MDD)的流行增加了。在治疗抗性癫痫患者的延长住院监测期间捕获的颅内脑电图(IEEG)提供了一种研究癫痫中MDD网络的特别有希望的方法。作者使用了24小时的休息状态IEEG,以检查皮质胶质结构中的神经活动模式,反映了13名成人中的抑郁症状的存在,用药难治性癫痫。在一个区域内平均电极的五个标准频带中的五个标准频带中的Z刻度平均相对功率进行主成分分析。主成分3是抑郁症状存在的统计学显着的预测因子(R〜(2)= 0.35,p = 0.014)。使用主成分3的平衡物流分类机模型将78%的患者归类为属于抑郁症状或对照组的抑郁症状,具有最小抑郁症状(敏感性,75%;特异性,80%;地区曲线= 0.8,留下一交叉验证)。分类依赖于整个Corticolimbic网络的Beta电力和低频速率。这些发现是,这是第一次跨越癫痫中涉及的电路的神经特征可以区分那些没有抑郁症状的患者。需要较大的研究来验证这些调查结果并评估其在MDD中的诊断效用。

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