View clinical trials related to Bipolar Disorder II.
Filter by:Most psychiatric research is based on the nosographic classifications used in current practice. At present, there is no diagnostic or prognostic biomarker for psychiatric pathologies commonly used in clinical practice. The study hypothesis is that peripheral inflammatory biomarkers could be common to several psychiatric disorders, in particular psychotic disorders (bipolar disorder, schizophreniform disorder, schizophrenia, depressive episode with psychotic features). The aim of this project is to set up a bio-collection of biological samples (peripheral blood samples) with associated phenotypic data (assessment of various symptoms using standardized scales in patients whose blood is sampled). The setting up of this cohort follows on from work carried out on a PsyCourse cohort also using a transdiagnostic approach in psychiatry, in order to be able to collaborate within a European research project.
The main aim of this research is to explore the effects that ketamine has on the functional connectivity of the brain in participants with treatment resistant depression (TRD). This study will investigate the relationship between these changes and response to treatment as measured by clinical scales, as well as examining drug induced changes in reward and emotion based brain activity, structural connectivity, cerebral blood flow, cognition, metabolism and blood markers of brain plasticity.
This is a study of the efficacy and safety of BXCL501 in children and adolescents with acute agitation and either bipolar disorder or schizophrenia.
Mood disorders are associated with significant financial and health costs for the United States, partially due to cognitive problems in these patients that can worsen disease course and impair treatment response. This study proposes to use smartphone-based technology to monitor cognitive problems in patients with mood disorders by linking brain network changes with predicted worsening of mood symptoms. The proposed study will provide evidence for using smartphone-based passive sensing as a cost-effective way to predict illness course and treatment response.
For the moment, the detection of a mood episode in Bipolar Disorder (BD) relies on the appearance of the first clinical signs that the clinician detect or that the patient becomes aware of and reports to the clinician. Since physiological parameters such as cardiac rhythms, respiratory rate, voice characteristics and actigraphy seem to be related to the onset of a mood episode, information collected through the combined monitoring of multiple selected physiological parameters (such as cardiac rhythms, respiratory rate, movements, voice) during wake and sleep time, using wearable user friendly systems included into garments as well as with a smartphone, may offer a new perspective in the long-term treatment of BD.