The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder.
ABSTRACT Recent studies have shown overall accuracy rates of 72% and 88% using baseline and/or 1-week change in QEEG biomarkers to predict clinical outcome to treatment with various antidepressant medications. In some cases, findings have been replicated across academic institutions and have been studied in the context of randomized, placebo-controlled trials. Recent EEG findings are corroborated by studies that use techniques with greater spatial resolution (eg, PET, MEG) in localizing brain regions pertinent to clinical response. As such, EEG measurements increasingly are validated by other physiologic measurements that have the ability to assess deeper brain structures. Continued progress along these lines may lead to the realized promise of QEEG biomarkers as predictors of antidepressant treatment outcome in routine clinical practice. In the larger context, use of QEEG technology to predict antidepressant response in major depression may mean that more patients will achieve response and remission with less of the trial-and-error approach that currently accompanies antidepressant treatment.
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ABSTRACT: Current studies suggest that an early improvement of depressive symptoms and the reduction of prefrontal theta cordance value predict the subsequent response to antidepressants. The aim of our study was (1) to compare the predictive abilities of early clinical improvement defined as ≥20 % reduction in Montgomery and Åsberg Depression Rating Scale (MADRS) total score at week 1 and 2, and the decrease of prefrontal theta cordance at week 1 in resistant depressive patients and (2) to assess whether the combination of individual predictors yields more robust predictive power than either predictor alone. Eighty-seven subjects were treated (≥4 weeks) with various antidepressants chosen according to the judgment of attending psychiatrists. Areas under curve (AUC) were calculated to compare predictive effect of defined single predictors (≥20 % reduction in MADRS total score at week 1 and 2, and the decrease of cordance at week 1) and combined prediction models. AUCs of all three predictors were not statistically different (pair-wise comparison). The model combining all predictors yielded an AUC value 0.91 that was significantly higher than AUCs of each individual predictor. The results indicate that the combined predictor model may be a useful and clinically meaningful tool for the prediction of antidepressant response in patients with resistant depression.European Archives of Psychiatry and Clinical Neuroscience 05/2014; 265(1). · 3.36 Impact Factor
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ABSTRACT: This article explores the science surrounding neurofeedback. Both surface neurofeedback (using 2-4 electrodes) and newer interventions, such as real-time z-score neurofeedback (electroencephalogram [EEG] biofeedback) and low-resolution electromagnetic tomography neurofeedback, are reviewed. The limited literature on neurofeedback research in children and adolescents is discussed regarding treatment of anxiety, mood, addiction (with comorbid attention-deficit/hyperactivity disorder), and traumatic brain injury. Future potential applications, the use of quantitative EEG for determining which patients will be responsive to medications, the role of randomized controlled studies in neurofeedback research, and sensible clinical guidelines are considered.Child and adolescent psychiatric clinics of North America. 07/2014; 23(3):427-464.
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ABSTRACT: The effectiveness of prefrontal theta cordance and early reduction of depressive symptoms in the prediction of antidepressant treatment outcome in patients with resistant depression: analysis of naturalistic dataEuropean Archives of Psychiatry and Clinical Neuroscience 01/2014; · 3.36 Impact Factor