Ignite Creation Date:
2024-05-05 @ 11:52 AM
Last Modification Date:
2024-10-26 @ 9:15 AM
Study NCT ID:
NCT00157547
Status:
COMPLETED
Last Update Posted:
2008-05-28
First Post:
2005-09-08
Brief Title:
Quantitative EEG QEEG as a Predictor of Treatment Outcome in Depression
Sponsor:
Massachusetts General Hospital
Organization:
Massachusetts General Hospital
Study Overview
Official Title:
The Use of Quantitative EEG QEEG as a Predictor of Treatment Outcome in Major Depressive Disorder
Status:
COMPLETED
Status Verified Date:
2008-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The purpose of the study is to try to see if antidepressant medications cause changes in QEEG measurements in the brain QEEG is a mathematical analysis of electrical currents in the brain using electrodes placed on the scalp Previous studies have shown that mood improvement clinical response caused by antidepressant medications was preceded by changes in QEEG measurements in the brain
Detailed Description:
Despite the availability of effective clinical treatments for major depressive disorder MDD 30-40 of subjects with MDD still fail to respond significantly to antidepressant treatment Fava and Davidson 1996 In the absence of biological predictors of treatment outcome in MDD clinicians face a difficult dilemma in selecting an antidepressant treatment
Currently we have only preliminary knowledge on the mechanisms and the biological correlates of treatment response in MDD Mayberg et al 1997 and 1999 Functional neuroimaging studies have demonstrated decreased metabolism and glucose consumption in specific limbic and paralimbic brain areas which are related to affective regulation Quantitative EEG QEEG studies in subjects with MDD have revealed other functional brain abnormalities such as decreased power in the EEG theta wave band Studies with auditory evoked potentials have shown P300 latency in subjects with MDD Moreover some quantitative EEG parameters eg cordance appear to predict clinical response to antidepressants
The principal aim of this study is to identify by measuring QEEG predictors and correlates of treatment response in a group of patients with MDD We will also carry out exploratory analyses to identify correlations between QEEG metrics and multiple clinical parameters of depressed subjects gender age chronicity of depression age of onset comorbid anxiety atypical and melancholic depressive subtypes
Our understanding of the relationship between treatment outcome in MDD and EEG measurements promises to provide clinically useful information for selecting antidepressant treatments it can also provide important information useful in the early testing of new compounds with putative antidepressant efficacy Furthermore the knowledge gained and techniques used may help shed light on the pathophysiology of major depression and perhaps other neuropsychiatric disorders associated with depressed mood
Currently we have only preliminary knowledge on the mechanisms and the biological correlates of treatment response in MDD Mayberg et al 1997 and 1999 Functional neuroimaging studies have demonstrated decreased metabolism and glucose consumption in specific limbic and paralimbic brain areas which are related to affective regulation Quantitative EEG QEEG studies in subjects with MDD have revealed other functional brain abnormalities such as decreased power in the EEG theta wave band Studies with auditory evoked potentials have shown P300 latency in subjects with MDD Moreover some quantitative EEG parameters eg cordance appear to predict clinical response to antidepressants
The principal aim of this study is to identify by measuring QEEG predictors and correlates of treatment response in a group of patients with MDD We will also carry out exploratory analyses to identify correlations between QEEG metrics and multiple clinical parameters of depressed subjects gender age chronicity of depression age of onset comorbid anxiety atypical and melancholic depressive subtypes
Our understanding of the relationship between treatment outcome in MDD and EEG measurements promises to provide clinically useful information for selecting antidepressant treatments it can also provide important information useful in the early testing of new compounds with putative antidepressant efficacy Furthermore the knowledge gained and techniques used may help shed light on the pathophysiology of major depression and perhaps other neuropsychiatric disorders associated with depressed mood
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None