222 research outputs found

    A review of quetiapine in combination with antidepressant therapy in patients with depression

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    Ella J Daly, Madhukar H TrivediMood Disorders Program, Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, USABackground: Atypical antipsychotics are increasingly used in the treatment of a broad spectrum of psychiatric disorders. There is evidence that in addition to treating the positive and negative symptoms of schizophrenia, as well as mania in bipolar disorder, these agents may have a potential role to play in the treatment of depressive disorders. In the following article we review the literature regarding the role of atypical antipsychotics, and specifically, quetiapine, in the treatment of major depressive disorder.Materials and methods: In March 2007 the authors performed a Medline search (English-language) using the keywords quetiapine and depression, revealing a total of 47 articles published. We also looked for cross-references in the published articles, obtained data-on-file from AstraZeneca Pharmaceutical L.P., and included abstracts presented at conferences and recent meetings.Results: From our review we found that there is increasing literature supporting the efficacy of add-on quetiapine in the treatment of major depressive disorder.Conclusion: There is a need, however, for further well-designed, adequately powered, randomized, controlled trials to confirm this finding, specifically in unipolar depression.Keywords: depression, adjunctive treatment, atypical antipsychotics, quetiapin

    Men and women from the STRIDE clinical trial: An assessment of stimulant abstinence symptom severity at residential treatment entry

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    Background and Objectives Gender‐specific factors associated with stimulant abstinence severity were examined in a stimulant abusing or dependent residential treatment sample (N = 302). Method Bivariate statistics tested gender differences in stimulant abstinence symptoms, measured by participant‐reported experiences of early withdrawal. Multivariate linear regression examined gender and other predictors of stimulant abstinence symptom severity. Results Women compared to men reported greater stimulant abstinence symptom severity. Anxiety disorders and individual anxiety‐related abstinence symptoms accounted for this difference. African American race/ethnicity was predictive of lower stimulant abstinence severity. Discussion and Conclusions Women were more sensitive to anxiety‐related stimulant withdrawal symptoms. Scientific Significance Clinics that address anxiety‐related abstinence symptoms, which more commonly occur in women, may improve treatment outcome. (Am J Addict 2015;XX:XX –XX

    Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity

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    Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71‐channel EEG recorded from 35 healthy adults at two sessions (1‐week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal‐to‐noise ratio, participant‐level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait‐multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one low‐variance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component‐based identification of spectral activity (CSD/eLORETA‐fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.Magnitude of frontal theta (rostral ACC eLORETA source amplitude) and posterior alpha (spectral components of scalp current source density) at rest have been considered candidate EEG biomarkers of depression outcomes. Given inconsistent findings, we examined the discriminant and convergent validity of these measures in healthy adults. Unlike theta, two distinct alpha components constituted reliable, convergent, and discriminant biometrics. While results have marked implications for clinical utility, we make several recommendations for improving the psychometric properties of resting frontal theta.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153675/1/psyp13483.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153675/2/psyp13483_am.pd

    Functional Connectivity of Brain Structures Correlates with Treatment Outcome in Major Depressive Disorder

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    Identifying biosignatures to assess the probability of response to an antidepressant for patients with major depressive disorder (MDD) is critically needed. Functional connectivity MRI (fcMRI) offers the promise to provide such a measure. Previous work with fcMRI demonstrated that the correlation in signal from one region to another is a measure of functional connectivity. In this pilot work, a baseline non-task fcMRI was acquired in 14 adults with MDD who were free of all medications. Participants were then treated for 8 weeks with an antidepressant and then clinically re-evaluated. Probabilistic anatomic regions of interest (ROI) were defined for 16 brain regions (eight for each hemisphere) previously identified as being important in mood disorders. These ROIs were used to determine mean time courses for each individual's baseline non-task fcMRI. The correlations in time courses between 16 brain regions were calculated. These calculated correlations were considered to signify measures of functional connectivity. The degree of connectivity for each participant was correlated with treatment outcome. Among 13 participants with 8 weeks follow-up data, connectivity measures in several regions, especially the subcallosal cortex, were highly correlated with treatment outcome. These connectivity measures could provide a means to evaluate how likely a patient is to respond to an antidepressant treatment. Further work using larger samples is required to confirm these findings and to assess if measures of functional connectivity can be used to predict differential outcomes between antidepressant treatments
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