Active clinical trials for "Depressive Disorder"

Despite significant advances in pharmacological treatment, the global burden of depression is increasing worldwide. The major challenge in antidepressant treatment is the clinicians' inability to predict the variability in individual response to the treatment. The development of biomarkers to predict treatment outcomes would enable clinician to find the right medication for a particular patient at the early stage of the treatment and thus could reduce prolonged suffering and ineffective protracted treatment. Brain imaging studies that examined brain predictors of treatment response based on group comparisons have limited value in classifying individuals as responders or non-responders. Machine learning classification techniques such as the support vector machine (SVM) method have proven useful in the classification of individual brain image observations into distinct groups or classes. However, studies that have applied the SVM method to structural and functional magnetic resonance scans (fMRI) involved small sample sizes and were confounded by placebo responses. Furthermore, a recent meta-analysis of clinical trials and EEG studies have shown that early clinical responses and brain changes at the early phase of antidepressant treatment may predict later clinical outcomes suggesting that neural markers measured in the early phase of antidepressant treatment may improve predictive accuracy. However, there is no fMRI study to date that has examined the predictive accuracy of data obtained in early phase of the treatment. We have preliminary fMRI data relating to early treatment response that form the basis of this proposed study. The main objective of this study is to use machine learning method to examine the predictive value (sensitivity, specificity, accuracy) of resting state and emotional task-related fMRI data collected at pre-treatment baseline (week 0) and in the early phase of antidepressant treatment (week 2) in the classification of remitters (< 10 MADRS scores after 12 weeks of treatment) and non-remitters in patients with major depressive disorder (MDD). A secondary objective is to determine which data set (week 0 or week 2) gives the best predictive value.

The purpose of the study is to evaluate the efficacy and safety of H1-Coil deep brain rTMS in subjects with bipolar depression, taking mood stabilizers and previously unsuccessfully treated with antidepressant medications.

The objective of this proposed study is to obtain data on the efficacy of Botox in reducing symptoms of MDD in male and female patients between the ages of 18 and 65 years old. The secondary object is to visually assess each patient's frown before and after the Botox injection to determine if there is a correlation between changes in the frown and changes in mood. The patients will be photographed at screening, visit 2 and 3. Their frown lines will be compared to determine if there is a visible improvement in the frown lines corresponding to an improvement in the efficacy rating scores.

Ketamine has been safely used for induction and maintenance of anesthesia for decades and more recently has been used for chronic pain. Ketamine is a noncompetitive, high-affinity antagonist of the N-methyl-D-aspartate type glutamate receptor, with additional effects on dopamine and μ-opioid receptors. During the last 9 years several uncontrolled reports have been published, showing a rapid and impressive effect of ketamine in TRD patients (Berman, Cappiello et al. 2000; Zarate, Singh et al. 2006; Mathew, Murrough et al. 2010; Aan Het Rot, Zarate et al. 2012; Mathew, Shah et al. 2012; Murrough, Iosifescu et al. 2013). Recently three placebo-controlled trials showed that a single dose of sub-anesthetic, (0.5 mg/kg) slow intravenous (IV) ketamine improves depressive symptoms dramatically. Across studies, a clinically significant antidepressant response was maintained for up to 72 hours in 12 of 25 patients. Nonetheless, all but two patients relapsed <2 weeks post-ketamine (Zarate, Singh et al. 2006; aan Het Rot, Zarate et al. 2012). Rot et al. showed that repeated IV ketamine infusions prolongs the duration of improvement. The investigators believe that the data presented above allows us to provide ketamine treatment here in the Sheba Medical Center for TRD patients.

OBJECTIVE: Evaluate the effectiveness of quality of life score, a cognitive-behavioral intervention by psychologists in the field of primary care in anxiety-depressive patients, mild to moderate, compared with usual care. DESIGN: Clinical trial, multicenter, prospective, and randomized into two parallel groups. SCOPE AND SUBJECTS: We included a random sample of 246 patients anxious-depressive, mild / moderate, belonging to the target population of 41 doctors from several health centers. INTERVENTION: In the 246 patients randomly assigned to the intervention group, with a standardized program of cognitive behavioral therapy applied by psychologists, by the usual treatment or control group, which will be standard care. MEASUREMENTS: The main result will be changes in general health scores of the SF-36. It will also measure the change in frequency and intensity of anxiety-depressive symptoms on the scales HARS, HDRS, STAI and BDI at baseline and at 2, 6 and 12 months. In addition, also collected for drug use and health services. ANALYSIS: Analyses were performed by intention to treat, comparing the change obtained in both groups at the end of the 12 month follow up. Estimates of the effect attributable to the intervention by the difference in those changes, adjusting in addition to the baseline, the possible confounding covariates or effect modifiers of the intervention, using longitudinal mixed-effects models.

In this study the investigators use clinical, biological and imaging markers to develop predictive markers for remission from depression. The investigators compare individuals who have received placebo to individuals who have received 10 mg of escitalopram for one week. In this double-blind, randomized study the investigators a) compare the groups to observe the short-term effects of escitalopram and b) study the predictive value of these observations with respect to remission. Measures include, but are not restricted to, limbic emotional reactivity as assessed by fMRI, emotional processing, emotional memory, autobiographical memory.

The investigators are conducting this study to test the usefulness of a new type of analysis of electroencephalographic (EEG) recordings called brain network activation or BNA. BNA allows to identify patterns of activation in brain networks and to track their changes over time. The investigators want to examine the possible role of brain network activation (BNA) in the diagnosis of mood disorders and predicting improvement over time. The procedure conducted with patients diagnosed with a mood disorder will be compared to people who do not have a mood disorder.

Background: In Italy, several recent studies found that a large percentage of patients attending Primary Care (PC) clinics meet criteria for at least one common mental disorder, as they show high rates of depression, anxiety, and co-morbid anxiety and depression. These patients may experience significant functional impairment and suffer from unexplained somatic symptoms, and often remain undetected and untreated. Consistent evidence for the effectiveness of organized care programs for depression, by improving quality of care and treatment adherence, is now available. Fundamental elements of these programs include algorithms to prompt the proper and timely implementation of evidence-based treatments, structured outcome assessment and systematic outreach. Telemedicine tools may represent a valuable strategy for improving depression outcomes in PC. Aims: 1.To develop and employ computer-based assessment to more accurately and timely detect patient depression in PC settings; 2.To evaluate the feasibility and effectiveness of a care support program developed in conjunction with the PC-based assessment for patients suffering from depression, as based on two main objectives: 2a.To support GP decisions with treatment algorithms and improve the quality of GP and mental health service collaboration; 2b.To improve patient compliance and treatment adherence by using appropriate telecommunication tools and technologically advanced tools to conduct systematic routine assessment. Although much of this system will be computer-based, live telephonic and in-person contacts will also be included as needed. Study Design: The study is a randomized controlled trial, involving four PC group clinics (GCs) located in two areas of Northern Italy. Two PC clinics will use the experimental protocol; the other two will serve as controls. The study will compare two different conditions: Group 1 (experimental): GPs will use a Computer Decision Support System with treatment algorithms and advice and supervision from a consultant psychiatrist. Patients will receive reminders via mobile texting or automatic mobile (or landline) phone calls to improve adherence to the treatment prescribed. Group 2 (control): GPs will provide TAU, will make their own decisions and will therefore not use the CDSS. Patients will not receive any reminders. All enrolled patients will be administered and will fill in the IDS-SR at baseline, 3 and 6-months: the IDS-SR score will be used as a primary endpoint.

This is a quasi-experimental evaluation of psychoeducational course focusing on mindfulness and lifestyle changes for depression and anxiety; clients in active treatment group are compared to those in a treatment-as-usual wait-list control group. The primary hypothesis is that the psychoeducational course will result in lower levels of depression and anxiety as compared to the wait-listed treatment-as-usual comparison group.

The purpose of this study is to determine whether an oxytocin ad-on, or oxytocin and tibolone ad-on can induce a response to antidepressants in patients with treatment resistant depression.