scholarly journals Use of long acting antipsychotics and relationship to newly diagnosed bipolar disorder: a pragmatic longitudinal study based on a Canadian health registry

2020 ◽  
Vol 10 ◽  
pp. 204512532095711
Author(s):  
Emmanuel Stip ◽  
Syed Javaid ◽  
Jonathan Bayard-Diotte ◽  
Karim Abdel Aziz ◽  
Danilo Arnone
Keyword(s):  
Bipolar Disorder ◽  
Newly Diagnosed ◽  
Limited Data ◽  
Major Depressive ◽  
Haloperidol Decanoate ◽  
Number Of Patients ◽  
Prescribing Trends ◽  
Canadian Health ◽  
Long Acting ◽  
Health Registry

Background: There is limited data from large naturalistic studies to inform prescribing of long-acting injectable medication (LAIs). Guidance is particularly rare in the case of primary mood disorders. Methods: This study describes prescribing trends of LAIs in 3879 patients in Quebec, Canada, over a period of 4 years. Health register data from the Quebec provincial health plan were reviewed. Results: In this specific registry, 32% of patients who received LAIs drugs for schizophrenia had a confirmed diagnosis of bipolar disorder and 17% had a diagnosis of major depressive disorder. Non-schizophrenia syndromes were preferentially prescribed risperidone long-acting antipsychotic, whereas patients with schizophrenia were prescribed an excess of haloperidol decanoate. Patients with non-schizophrenia disorders prescribed long-acting antipsychotics were more frequently treated in primary care compared with patients with schizophrenia. Conclusion: Data from a large number of patients treated naturalistically in Quebec with long-acting antipsychotics suggests that these compounds, prescribed to treat symptoms of schizophrenia and schizoaffective disorders, were maintained when mood symptoms emerged, even in cases when the diagnosis changed to bipolar disorder. This pragmatic study supports the need to explore this intervention as potential treatment for affective disorders.

scholarly journals Estimation of Years Lived with Disability Using a Prevalence-Based Approach: Application to Major Psychiatric Disease in Korea

2021 ◽  
Vol 18 (17) ◽  
pp. 9056
Author(s):  
Chae-Bong Kim ◽  
Minsu Ock ◽  
Yoon-Sun Jung ◽  
Ki-Beom Kim ◽  
Young-Eun Kim ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Disability Weight ◽  
Psychiatric Disease ◽  
Major Depressive ◽  
Number Of Patients ◽  
Icd 10 ◽  
International Statistical Classification ◽  
Years Lived With Disability

To help develop policies concerning the prevention of psychiatric disease in Korea, we reviewed the literature on this topic in different countries and used a prevalence-based approach to estimate the years lived with disability (YLDs) in Korean patients with major psychiatric diseases. We calculated YLDs by extracting data on the number of patients with mild, moderate, and severe cases of schizophrenia, bipolar disorder, and major depressive disorder, as classified by International Statistical Classification of Disease (ICD) codes. YLDs were highest for patients with major depressive disorder (1190.6; 73.9%), schizophrenia (303.3; 18.8%) and bipolar disorder (117.9; 7.3%). Men had higher YLDs for schizophrenia, 2502 (20–24 years); bipolar disorder, 477 (40–44 years); and major depressive disorder, 2034 (75–79 years). Women had higher YLDs for schizophrenia, 484 (45–49 years); bipolar disorder, 214 (≥80 years); and major depressive disorder, 3541 (75–79 years). The prevalence-based approach and severity distribution is useful for estimating long-term psychiatric disease burden and YLDs. However, YLD-estimation studies must compensate for the shortcomings of the ICD-10 by referencing the Diagnostic and Statistical Manual of Mental Disorders 5th edition, as well as updating the disability weight score according to disease severity.

scholarly journals The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldassarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

Predictors of conversion of major depressive disorder to bipolar disorder

2021 ◽  
pp. 113939
Author(s):  
Satish Suhas ◽  
Abha Thakurdesai ◽  
Amal Jolly Joseph ◽  
Chittaranjan Andrade
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Major Depressive

scholarly journals Impact of modification to DSM-5 criterion A for hypomania/mania in newly diagnosed bipolar patients: findings from the prospective BIO study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Mette U. Fredskild ◽  
Sharleny Stanislaus ◽  
Klara Coello ◽  
Sigurd A. Melbye ◽  
Hanne Lie Kjærstad ◽  
...  
Keyword(s):  
Rating Scale ◽  
Newly Diagnosed ◽  
Young Mania ◽  
Dsm 5 ◽  
Criterion A ◽  
Number Of Patients ◽  
Bipolar Type ◽  
Dsm Iv ◽  
Bipolar Patients

Abstract Background DSM-IV states that criterion A for diagnosing hypomania/mania is mood change. The revised DSM-5 now states that increased energy or activity must be present alongside mood changes to diagnose hypomania/mania, thus raising energy/activity to criterion A. We set out to investigate how the change in criterion A affects the diagnosis of hypomanic/manic visits in patients with a newly diagnosed bipolar disorder. Results In this prospective cohort study, 373 patients were included (median age = 32; IQR, 27–40). Women constituted 66% (n = 245) of the cohort and 68% of the cohort (n = 253) met criteria for bipolar type II, the remaining patients were diagnosed bipolar type I. Median number of contributed visits was 2 per subject (IQR, 1–3) and median follow-up time was 3 years (IQR, 2–4). During follow-up, 127 patients had at least one visit with fulfilled DSM-IV criterion A. Applying DSM-5 criterion A reduced the number of patients experiencing a hypomanic/manic visit by 62% at baseline and by 50% during longitudinal follow-up, compared with DSM-IV criterion A. Fulfilling DSM-5 criterion A during follow-up was associated with higher modified young mania rating scale score (OR = 1.51, CL [1.34, 1.71], p < 0.0001) and increased number of visits contributed (OR = 1.86, CL [1.52, 2.29], p < 0.0001). Conclusion Applying the stricter DSM-5 criterion A in a cohort of newly diagnosed bipolar patients reduced the number of patients experiencing a hypomanic/manic visit substantially, and was associated with higher overall young mania rating scale scores, compared with DSM-IV criterion A. Consequently, fewer hypomanic/manic visits may be detected in newly diagnosed bipolar patients with applied DSM-5 criterion A, and the upcoming ICD-11, which may possibly result in longer diagnostic delay of BD as compared with the DSM-IV.

scholarly journals A machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jakub Tomasik ◽  
Sung Yeon Sarah Han ◽  
Giles Barton-Owen ◽  
Dan-Mircea Mirea ◽  
Nayra A. Martin-Key ◽  
...  
Keyword(s):  
Mental Health ◽  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Diagnostic Algorithm ◽  
Health Questionnaire ◽  
Major Depressive ◽  
Blood Biomarker ◽  
Mental Health Questionnaire ◽  
Biomarker Data

AbstractThe vast personal and economic burden of mood disorders is largely caused by their under- and misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. Here, we aimed to develop a diagnostic algorithm, based on an online questionnaire and blood biomarker data, to reduce the misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD). Individuals with depressive symptoms (Patient Health Questionnaire-9 score ≥5) aged 18–45 years were recruited online. After completing a purpose-built online mental health questionnaire, eligible participants provided dried blood spot samples for biomarker analysis and underwent the World Health Organization World Mental Health Composite International Diagnostic Interview via telephone, to establish their mental health diagnosis. Extreme Gradient Boosting and nested cross-validation were used to train and validate diagnostic models differentiating BD from MDD in participants who self-reported a current MDD diagnosis. Mean test area under the receiver operating characteristic curve (AUROC) for separating participants with BD diagnosed as MDD (N = 126) from those with correct MDD diagnosis (N = 187) was 0.92 (95% CI: 0.86–0.97). Core predictors included elevated mood, grandiosity, talkativeness, recklessness and risky behaviour. Additional validation in participants with no previous mood disorder diagnosis showed AUROCs of 0.89 (0.86–0.91) and 0.90 (0.87–0.91) for separating newly diagnosed BD (N = 98) from MDD (N = 112) and subclinical low mood (N = 120), respectively. Validation in participants with a previous diagnosis of BD (N = 45) demonstrated sensitivity of 0.86 (0.57–0.96). The diagnostic algorithm accurately identified patients with BD in various clinical scenarios, and could help expedite accurate clinical diagnosis and treatment of BD.

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