View clinical trials related to Depressive Disorder.
Filter by:A prospective, multicenter, registered cohort study to observe the incidence of 1-year major adverse cardiac events in patients with coronary heart disease co-morbid depression treated with percutaneous coronary intervention and to clarify the predictors of 1-year major adverse cardiac events post PCI among these patients.
Repetitive pulse transcranial magnetic stimulation (rTMS) is a noninvasive treatment that involves stimulating the brain; however, treatment benefit depends on placing a TMS coil in the correct place on the head to reach critical brain regions below. Clinicians typically use scalp-based targeting, a process in which rather than using MRI guidance to target brain regions for stimulation, they use landmarks on the scalp. Several researchers, including the investigators' lab, showed that the current scalp-based targeting techniques do not position stimulation above the correct brain region, and patients fail to respond. The investigators propose to improve clinical scalp-based targeting by comparing it to MRI guided targeting. The most common clinical population receiving rTMS therapy is depressed patients. The investigators' plan is to study the accuracy of certain scalp-based rules in patients with depression. Accurate brain stimulation targeting is critical for effective rTMS therapy. For participants who are not undergoing rTMS therapy who have COVID-19 distress, we are offering a combined home-based neuromodulation (transcranial electrical stimulation) and focused psychotherapy program dedicated to improving the same outcome measure, quality of life. Transcranial electrical stimulation (tES) stimulates the brain over a large region; however, we are able to model with brain imaging which brain regions receive the strongest stimulation. Our goal is still to examine stimulation precision, but we will test whether strength of tES in the same brain regions that rTMS is targeting will also lead to improved quality of life. We will also carefully assess whether it is possible to measure healthy functioning, an outcome in the rTMS study, because sheltering in place may reduce activities and thus distort our measure. We will also test whether our psychotherapy intervention will mitigate this effect and, if so, we may make it available to all those depressed Veterans in whom we're studying the effect of neuromodulation on functioning.
This study investigates the relationships and differences in PET-MRI brain imaging biomarkers of abnormal aging and behavioral measures in late life depression compared to healthy controls, and evaluates relationships and differences in the same imaging and behavioral measures following electroconvulsive therapy. The study tests the hypotheses that late-life depression will be associated with higher levels of accelerated aging and brain disease biomarkers, and that electroconvulsive therapy works by stimulating the reorganization of brain tissue.The data collected with contribute to improved knowledge about the neurobiology of late-life psychopathology and its treatment.
Compelling evidence indicates inflammation plays a role in depression, but potential mechanisms linking inflammation to depression, such as dysregulated reward processing, are poorly understood. This study comprehensively evaluates effects of inflammation on reward across dimensions (e.g., anticipating versus receiving a reward) and types (e.g., money vs. smiling faces) in younger and older women. Characterizing how inflammation shapes the dynamic and multidimensional reward system, and how this may differ by age, may give insight into risk factors for depression and help identify critical points for intervention.
Major Depressive Disorder (MDD) is a common and debilitating illness. It affects a person's family and personal relationships, work, education, and life. It changes sleeping and eating habits and significantly impairs patients' general health. The disorder affects Veterans more than the general population, both as an isolated illness and in conjunction with posttraumatic stress disorder (PTSD) and suicidality. Symptoms in a notable proportion of patients (~30%) do not respond to behavioral and pharmacological interventions, and new treatments are in great need. One such treatment, transcranial magnetic stimulation (TMS), has been cleared by Food and Drug Administration for treatment in MDD. TMS is effective in around 60% of patients with treatment-resistant MDD but is associated with significant financial and time burden. Further insights into the neurobiological effects of TMS and markers for functional recovery prediction and treatment progression are of great value. The goal of this proposal is to use human electrophysiology (electroencephalography, hereafter EEG, in particular) and machine learning to predict treatment response in candidates for TMS treatment and also study TMS's mechanism of action. Doing so has several benefits for patients, as prediction of treatment helps providers in screening out the patients for whom TMS is ineffective and understanding the mechanism allows us to refine and individualize the treatment. The investigators will recruit 35 patients with treatment-resistant MDD and record resting state EEG signal with a dense electrode array before and after a 6-week clinical course of TMS treatment. The investigators will use machine learning (Sparse regressions) to predict treatment outcome using functional connectivity (Coherence) maps derived from the EEG signal. The investigators also will use classifiers to track changes in functional connectivity through the course of treatment. Based on our preliminary data, the investigators hypothesize that weaker functional connectivity between prefrontal cortex (where the stimulation is delivered) and parietal/posterior midline sites predict better response to treatment and that TMS treatment will enhance these connections. The data collected here would be used as a seed and preliminary data for future federal (NIH and the VA) career development awards which will focus on the use of EEG to better understand brain function and neuromodulation treatments.
This work will mark the first step in understanding the neural targets for rTMS in youth with difficult to treat depressive symptoms, creating benchmarks for optimizing the safety and efficacy of rTMS for pediatric populations through precision targeting, and encourage funding applications for larger sham- controlled randomized clinical studies.
DELPhI acquisition and analysis software, a QuantalX Neuroscience development, which is designed to measure, analyze, and display brain electrical activity of human electroencephalogram (EEG), to transcranial magnetic stimulation (TMS), will be used to evaluate different psychiatric conditions.
Cardiovascular disease increases the risk of depression and vice versa. Many cardiovascular patients are subjected to percutaneous coronary intervention (PCI). Potential biomarkers for the development, the course and the recovery of both diseases are in the focus of interest of many studies. One of the biomarkers that stands out is brain derived neurotrophic factor (BDFN). BDNF plays a significant role in regulating vascular growth and repair but also stimulates the survival, differentiation, and conservation of neurons. The aim of the study is to detect the depression in patients undergoing PCI and to determine the impact of psychiatric treatment on the functional recovery and on the changes of BDNF.
This protocol will test the hypothesis that Acceptance and Commitment Therapy (ACT) is effective in reducing anxiety and depressive symptoms during the perinatal and postpartum periods. Participants should expect their participation in the study to last 9-12 months.
The study will evaluate effectiveness of flexible dose vortioxetine 10-20 mg/day on emotional functioning in patients with MDD with an inadequate response to SSRIs/SNRIs.