Purpose: The Swedish National Quality Register for bipolar affective disorder, BipoläR, was established in 2004 to provide nationwide indicators for quality assessment and development in the clinical care of individuals with bipolar spectrum disorder. An ancillary aim was to provide data for bipolar disorder research.
Participants: Inclusion criteria for registration in BipoläR is a diagnosis of bipolar spectrum disorder (ICD codes: F25.0, F30.1-F30.2, F30.8-F31.9, F34.0) and treatment at an outpatient clinic in Sweden. BipoläR collects data from baseline and annual follow-up visits throughout Sweden. Data is collected using questionnaires administered by healthcare staff. The questions cover sociodemographic, diagnostic, treatment, outcomes and patient reported outcome variables. The register currently includes 39 583 individual patients with a total of 75 423 baseline and follow-up records.
Findings To Date: Data from BipoläR has been used in several peer-reviewed publications. Studies have provided knowledge on effectiveness, side effects and use of pharmacological and psychological treatment in bipolar disorder. In addition, findings on the diagnosis of bipolar disorder, risk factors for attempted and completed suicide and health economics have been reported. The Swedish Bipolar Collection project has contributed to a large number of published studies and provides important information on the genetic architecture of bipolar disorder, the impact of genetic variation on disease characteristics and treatment outcome.
Future Plans: Data collection is ongoing with no fixed end date. Currently, approximately 5000 new registrations are added each year. Cohort data are available via a formalised request procedure from Centre of Registers Västra Götaland (e-mail: registercentrum@vgregion.se). Data requests for research purposes require an entity responsible for the research and an ethical approval.
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http://dx.doi.org/10.1136/bmjopen-2022-064385 | DOI Listing |
Neuroradiology
January 2025
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.
Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.
Transl Psychiatry
January 2025
Department of Psychology, Goldsmiths University of London, London, UK.
Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes.
View Article and Find Full Text PDFNeuropharmacology
January 2025
Department of Psychiatry and Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA. Electronic address:
Bipolar disorder (BD) is a severe mental illness characterized by recurrent episodes of depression and mania. Lithium is the gold standard pharmacotherapy for BD, but outcomes are variable, and the relevant therapeutic mechanisms underlying successful treatment response remain uncertain. To identify synaptic markers of BD and lithium response, we measured the effects of lithium on induced pluripotent stem cell-derived neurons from BD patients and controls.
View Article and Find Full Text PDFFront Psychiatry
January 2025
Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Introduction: Unipolar and bipolar mood disorders in older adults are accompanied by cognitive impairment, including executive dysfunction, with a severe impact on daily life. Up and till now, strategies to improve cognitive functioning in late-life mood disorders (LLMD) are sparse. Therefore, we aimed to assess the efficacy of adaptive, computerized cognitive training (CT) on executive and subjective cognitive functioning in LLMD.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!