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临床试验/NCT05905705
NCT05905705招募中不适用

Disruptions of Brain Networks and Sleep by Electroconvulsive Therapy

Washington University School of Medicine1 个研究点 分布在 1 个国家目标入组 50 人开始时间: 2023年3月7日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
50
试验地点
1
主要终点
Slow wave activity (SWA) during non-rapid eye movement sleep (NREM) stage N2/N3

研究概览

简要总结

Electroconvulsive therapy (ECT) alleviates treatment-resistant depression (TRD) through repeated generalized seizures. The goal of this study is to evaluate how ECT impacts sleep-wake regulation and efficiency of information transfer in functional networks in different states of arousal.

详细描述

Graph-based network analyses of electroencephalographic (EEG) signals allow characterization of functional networks. The robustness of local networks to disruption is quantified as local efficiency (Elocal), while network integration is quantified as global information transfer (Eglobal).

Aim 1: Assess relationships between sleep slow-wave activity (SWA) and awake Elocal over the course of ECT.

Aim 2: Quantify relationships between depression severity and awake Elocal over the course of ECT.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
21 Years 至 65 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Referral for initial ECT index course for Treatment-Resistant Depression (TRD), unipolar major depressive disorder or bipolar depression. Historic failure of response or remission to at least two antidepressant medications of sufficient dose and duration will be used for TRD diagnostic.

排除标准

  • Diagnoses of schizophrenia or schizoaffective disorders.
  • Subjects who are unable to tolerate the Dreem device for sleep recordings will be excluded from the study.

结局指标

主要结局

Slow wave activity (SWA) during non-rapid eye movement sleep (NREM) stage N2/N3

时间窗: Up to 4 weeks during patients ECT treatment course

Total power of EEG slow waves per minute present during N2/N3 sleep

Graph-based neural connectivity measure of local efficiency of information transfer (Elocal) during wakefulness

时间窗: Up to 4 weeks during patients ECT treatment course

Elocal will be calculated as the average inverse shortest path length among neighbors of a node within the network. Nodes will be constructed based on 5-minute recordings of eyes closed wakefulness theta band (4-8 Hz) EEG.

Graph-based neural connectivity measure of global information transfer (Eglobal) during ECT-induced seizure

时间窗: Up to 4 weeks during patients ECT treatment course

Eglobal will be calculated as the average inverse shortest path length between node pairs in the networks. Nodes will be constructed based on ECT-induced seizure EEG data within the alpha band (8-13 Hz).

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

MohammadMehdi Kafashan

Instructor

Washington University School of Medicine

研究点 (1)

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