Depressive Episodes In Bipolar Disorder Research Articles

Aripiprazole/Sertraline Combination: Clinical and Cost-Effectiveness in Comparison With Quetiapine for the Treatment of Bipolar Depression (ASCEnD Trial)-Protocol for a Nested Qualitative Study.

Bipolar disorder is a recurrent mental health disorder with a prevalence rate of 1.4%. On average, there can be a delay of 9.5 years from the initial presentation of symptoms to a confirmed diagnosis. Individuals living with bipolar disorder have a reduced life expectancy. There is limited evidence regarding the effectiveness of antidepressants in treating bipolar disorder. The ASCEnD clinical trial will test the clinical and cost-effectiveness of the aripiprazole/sertraline combination in comparison with quetiapine for the treatment of bipolar depression (individuals who suffer from depressive episodes in bipolar disorder) and will include a nested qualitative study. The qualitative study will use semi-structured interviews to explore pilot trial participants' and clinicians' perspectives on recruitment procedures, the acceptability of the intervention, the management of bipolar disorder and attitudes to medication combinations. Findings will inform recruitment strategies and optimise training for the participating sites in the ASCEnD full trial. They will also help to illuminate the lived experience of people with bipolar disorder and the clinicians who work with people with bipolar disorder. The discussion will explore perspectives on the delay in diagnosis, having a diagnosis, the impact of living with bipolar disorder and attitudes to treatment, including drug combinations. A Lived Experience Advisory Panel (LEAP) has been convened with the support of the McPin Foundation, which will contribute to the ASCEnD trial and its nested qualitative study to provide input on the design and delivery of the trial and qualitative study, analysis of qualitative data and dissemination of findings.

Machine Learning-Driven Comparative Analysis of Quetiapine and Olanzapine for Managing Depressive Episodes in Bipolar Disorder

Background Bipolar disorder (BD) necessitates effective management of both manic and depressive episodes. Quetiapine and olanzapine are antipsychotic medications commonly used in the treatment of BD, but their relative efficacy as antidepressants is a topic of ongoing research. Objective This case series aims to evaluate the greater efficacy of quetiapine compared to olanzapine as an antidepressant in the treatment of bipolar disorder. Methods Two patients with bipolar disorder were treated with either quetiapine or olanzapine. Clinical assessments were conducted using the Mood Disorder Questionnaire (MDQ), Clinical Global Impression-Severity (CGI-S), Hamilton Depression Rating Scale (HDRS), and Global Assessment of Functioning (GAF) before and after the treatment. Results Quetiapine showed greater efficacy in reducing depressive symptoms and improving overall functioning compared to olanzapine. MDQ scores decreased, CGI-S scores improved, HDRS scores reduced, and GAF scores increased more significantly in the patient treated with quetiapine. Conclusion Quetiapine appears to be a more effective antidepressant than olanzapine in the treatment of bipolar disorder. These findings suggest that quetiapine could be considered a preferred option for managing depressive episodes in BD patients.

The mediating effects of school bullying victimization in the relationship between childhood trauma and NSSI among adolescents with mood disorders

BackgroundNonsuicidal self-injury (NSSI) is a serious problem in the adolescent population worldwide. Childhood trauma and bullying have been identified as risk factors for NSSI. We explored the relationships among Childhood trauma, Bullying victimization and the severity of NSSI behaviours, and test the effect of Bullying victimization in mediating the association between Childhood trauma and the NSSI behaviours.MethodsA total of 123 adolescents were recruited. They were diagnosed with depression or depressive episodes of bipolar disorder and had experienced NSSI in the last year. They were assessed using the Chinese version of the Childhood Trauma Questionnaire (CTQ-C), the Revised Olweus Bullying Victimization Questionnaire (OBVQ-R), and the Adolescent Self-Harm Questionnaire (ASHQ).ResultsFemales presented a significantly greater prevalence of sexual abuse and relationship bullying than boys. Individuals in the younger age group (10–14 years) presented a greater incidence of emotional neglect, verbal bullying, relationship bullying, and total bullying, and their NSSI score was also higher than that of those in the older age group (15–19 years). Only children show a greater prevalence of sexual abuse than nononly children. Single-parent families scored higher on emotional abuse, emotional neglect, physical neglect and physical bullying than two-parent families. There was a significant positive correlation between each dimension of childhood trauma and all the dimensions of bullying, between childhood trauma and NSSI, and between bullying and NSSI. Childhood trauma can not only directly affect the severity of NSSI but also indirectly aggravate the severity of NSSI through bullying victimization. The mediating effects of bullying victimization on emotional abuse, physical abuse, emotional neglect and physical neglect were 14%, 21%, 20%, 13% and 20%, respectively.ConclusionThere was a significant positive correlation between childhood trauma and bullying, between childhood trauma and NSSI, and between bullying and NSSI. Childhood trauma can not only directly affect the severity of NSSI but also indirectly aggravate the severity of NSSI through bullying victimization. Bullying victimization played the partial mediating effects between Childhood trauma and NSSI.

The Transition Between Depressive Episode and Manic Episode During the Treatment of Bipolar Disorder

Bipolar disorder (BD) is characterized by periodic alternations between depressive and manic episodes. It belongs to a complex group of severe and persistent conditions. This category includes bipolar I disorder (BDI) and bipolar II disorder (BDII). The definition of BDI hinges primarily on the manifestation of a syndromal manic episode. Conversely, BDII is characterized by the occurrence of both a syndromal hypomanic episode and a major depressive episode, which jointly constitute its defining features. BDI is the most common type in clinics. The duration of episodes and the time spent in the manic phases and depressive periods of bipolar disorder are not clearly defined for subtypes of the disorder. This paper analyzes the duration of manic episodes and depressive episodes in bipolar disorder, and explores the switch from major depression to bipolar depression. By analyzing and comparing the data and results in essays, it is still hard to tell the exact duration and the occurrence of the episodes. But the effects of drugs can be summarized during the treatment of bipolar disorders. At the same time, it discovers that during treatment of major depression, bipolar disorder occurs. In conclusion, the duration is different for different people, and it depends on many subjective influences. During treatment of major depression, the transition from major depression to bipolar depression will happen indeed, but the probability is very small. This research may provide a new concern that doctors and scientists should pay more attention to the treatment of such mental diseases and keep an eye on the switch.

A large-scale study on uric acid-related biomarkers in patients with bipolar disorder

Objective: Recent research has provided strong evidence supporting the use of uric acid-related ratios as potential biomarkers for disease diagnosis. Notable ratios among these include uric acid-to-albumin ratio (UAR), uric acid-to-creatinine ratio (UCR), uric acid-to-high-density lipoprotein ratio (UHR), and uric acid-to-lymphocyte ratio (ULR). The aim of the study is to analyze these biomarkers in bipolar disorder (BD) patients. Methods: 5465 BD patients were enrolled in this study and 6629 healthy subjects served as controls. We compared differences of the above ratio indicators among different BD diagnostic groups and analyzed factors leading to the onset of BD. Results: BD-M (manic episodes of BD) group had higher ULR, UHR, UCR, UAR than HC (Heathy Controls) and BD-D (depressive episodes of BD) groups, while BD-D group showed lower ULR and UCR than HC group. P-BD-M (BD-M with psychotic symptoms) group displayed higher ULR, UHR, UCR, UAR than HC group, while even higher ULR, UHR, UAR than NP-BD-M (BD-M without psychotic symptoms) group. High UAR was risk factor in BD-M. Conclusions: Our study suggests BD-M has more intense inflammatory response than BD-D. Furthermore, there is heterogeneity in the pathogenesis of psychotic symptoms between BD-M and BD-D. Additionally, High UAR was risk factor in BD-M.

Up-to-Date on clinical and preclinical studies of psilocybin therapy

Major Depressive Disorder (MDD) poses a significant global health burden, with 30-40% patients developing resistance to standard clinical antidepressants, such as selective serotonin reuptake inhibitors and tricyclic antidepressants. In 2016, Carhart-Harris and colleagues reported that psilocybin, the hallucinogenic compound derived from magic mushrooms, exhibits rapid and enduring antidepressant effects in patients with treatment-resistant depression. Subsequent clinical studies have found the therapeutic potential of psilocybin in MDD, depressive episode in bipolar disorder, anorexia, and drug addiction. In 2018 and 2019, the U.S. Food and Drug Administration designated psilocybin as a "breakthrough medicine" for treatment-resistant depression and MDD, respectively. Notably, the side effects of psilocybin are limited to transient and mild issues, such as headache and fatigue, suggesting its safety. In 2023, we published a review on the role of serotonin 5-HT2A receptors in the antidepressant effects of serotonergic psychedelics (Nihon Yakurigaku Zasshi, Volume 158, Issue 3, Page 229-232). Here, we present our study alongside the latest clinical and preclinical research on the antidepressant effects of psilocybin and provide an overview of the potential and issues related to psilocybin therapy.

Bipolar disorder and Lewy body dementia: case report and literature review.

Depressive episodes with psychotic symptoms are prevalent among the older adults, emphasizing the need to differentiate them from dementia with Lewy bodies (DLB), in which depressive and psychotic symptoms commonly coexist. In contrast, psychotic symptoms occur more frequently in depressive episodes of bipolar disorder (BD) than in major depressive disorder (MDD). Although MDD is a significant risk factor for dementia, studies exploring the relationship between BD and dementia are lacking. This report details the case of a 74-year-old female who experienced severe psychotic depression that led to suicide attempts during a long-term course of young-onset BD. Ultimately, she was diagnosed with DLB based on her neurocognitive symptoms and results of the neuroimaging examination. She had experienced multiple relapses in the past, predominantly characterized by depressive episodes in her old age. Notably, she had never undergone lithium treatment, which is known for its potential efficacy in preventing relapse and dementia. Recent systematic reviews and meta-analyses have suggested that patients with BD have a higher risk of dementia than the general population, and that lithium usage is associated with a reduced risk. Moreover, patients with BD have been suggested to have an elevated risk of developing Parkinson's disease (PD), and the pathophysiological relationship between BD and PD may be attributed to dopamine dysregulation resulting from multiple relapses. Future research is imperative to identify strategies for preventing dementia in patients with BD and to develop interventions for the comorbidities of BD and DLB.

Acupuncture at five Zang-shu and Ge-shu for bipolar depression: study protocol for a randomized controlled pilot trial

Background: Bipolar disorder is a very common, often misdiagnosed mental disorder strongly associated with comorbidity, disability, and premature mortality. Bipolar depression (i.e., depressive episode in bipolar disorder) is poorly responsive to available treatments. Acupuncture at five Zang-shu and Ge-shu, a prescription from Dr. Leting Wang, is a popular therapy for depression in China. Its effectiveness and safety for bipolar depression is yet to be verified by clinical study. Methods/design: The study is a single-center, prospective, randomized controlled trial involving 72 patients diagnosed with bipolar depression. Participants will be randomized either to the study group or the control group in a 1:1 ratio. All participants will receive mood stabilizer therapy. In addition, the study group will receive acupuncture therapy at five Zang-shu and Ge-shu, three times per week. The control group will orally take the antidepressant bupropion. Observation and intervention will last for 8 consecutive weeks. Outcome measurements include Hamilton Depression Rating Scale-17 (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Clinical Global Impression Scale (CGI), Young Manic Rating Scale (YMRS), Treatment Emergent Symptom Scale (TESS), serum levels of anti-inflammatory cytokines (IL-4, IL-10, TGF-β), pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), brain-derived neurotrophic factor (BDNF) and C-Reactive Protein (CRP). Assessments will be conducted at baseline, 1st, 2nd, 4th and 8th week after randomization. Safety assessments will be performed throughout the study. Discussion: The results of this study are expected to verify the effectiveness and safety of acupuncture at five Zang-shu and Ge-shu for bipolar depression, and explore its therapeutic mechanisms from the point of anti- inflammation.

Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder

Study Design: A prospective study. BackgroundThis study aims to investigate the relationship between different states of bipolar disorder (BD) and plasma inflammatory proteins, which may be used as their biomarkers. Materials and methodsWe totally collected admission plasma from 16 healthy subjects and 32 BD patients, including 16 patients with BD manic episodes (BD-M) and 16 patients with BD depressive episodes (BD-D). Ten samples in each group were analyzed by proximity extension assays of 92 inflammation-related proteins, and all samples were verified by ELISA. Receiver-operating characteristic (ROC) curve analysis was performed to identify the diagnostic ability and cut-off values of potential biomarkers. ResultsOur findings showed that BD patients had significantly higher levels of IL6, MCP-1, TGF-α, IL8, and IL10-RB in comparison with healthy subjects, and their cut-off values were 0.531 pg/ml, 0.531 pg/ml, 0.469 pg/ml, 0.406 pg/ml, and 0.406 pg/ml, respectively. The levels of IL6, MCP-1, TGF-α, and IL8 in BD-M patients were significantly greater than in healthy individuals, and their cut-off values were 0.813 pg/ml, 0.688 pg/ml, 0.438 pg/ml, and 0.625 pg/ml, respectively. Moreover, we found cut-off values of 0.500 pg/mL and 0.688 ng/mL for TGF-α and β-NGF, respectively, even though the levels in the BD-D group were much higher than in the control group. Furthermore, BD-M patients had significantly higher levels of IL6, FGF-19, IFN-γ, and IL-17C in comparison with BD-D patients. Likewise, 0.687 pg/ml, 0.500 pg/ml, 0.438 pg/ml, and 0.375 pg/ml were their cut-off values, respectively. Our findings also showed that the combination of these proteins had the highest diagnostic accuracy. ConclusionsOur findings showed that plasma inflammatory proteins were related to BD and its subtypes, which may be utilized as potential biomarkers of different stages of BD. Furthermore, we also found their cut-off values and their combinations to have the highest diagnostic accuracy, providing clinicians with a new method to rapidly differentiate BD and its subtypes and manage early targeted interventions.

Clinical decision support for bipolar depression using large language models

Management of depressive episodes in bipolar disorder remains challenging for clinicians despite the availability of treatment guidelines. In other contexts, large language models have yielded promising results for supporting clinical decisionmaking. We developed 50 sets of clinical vignettes reflecting bipolar depression and presented them to experts in bipolar disorder, who were asked to identify 5 optimal next-step pharmacotherapies and 5 poor or contraindicated choices. The same vignettes were then presented to a large language model (GPT4-turbo; gpt-4-1106-preview), with or without augmentation by prompting with recent bipolar treatment guidelines, and asked to identify the optimal next-step pharmacotherapy. Overlap between model output and gold standard was estimated. The augmented model prioritized the expert-designated optimal choice for 508/1000 vignettes (50.8%, 95% CI 47.7–53.9%; Cohen’s kappa = 0.31, 95% CI 0.28–0.35). For 120 vignettes (12.0%), at least one model choice was among the poor or contraindicated treatments. Results were not meaningfully different when gender or race of the vignette was permuted to examine risk for bias. By comparison, an un-augmented model identified the optimal treatment for 234 (23.0%, 95% CI 20.8–26.0%; McNemar’s p < 0.001 versus augmented model) of the vignettes. A sample of community clinicians scoring the same vignettes identified the optimal choice for 23.1% (95% CI 15.7–30.5%) of vignettes, on average; McNemar’s p < 0.001 versus augmented model. Large language models prompted with evidence-based guidelines represent a promising, scalable strategy for clinical decision support. In addition to prospective studies of efficacy, strategies to avoid clinician overreliance on such models, and address the possibility of bias, will be needed.

Exploring hub genes and crucial pathways linked to oxidative stress in bipolar disorder depressive episodes through bioinformatics analysis.

Bipolar disorder (BD) is a complex and serious psychiatric condition primarily characterized by bipolar depression, with the underlying genetic determinants yet to be elucidated. There is a substantial body of literature linking psychiatric disorders, including BD, to oxidative stress (OS). Consequently, this study aims to assess the relationship between BD and OS by identifying key hub genes implicated in OS pathways. We acquired gene microarray data from GSE5392 through the Gene Expression Omnibus (GEO). Our approach encompassed differential expression analysis, weighted gene co-expression network analysis (WGCNA), and Protein-Protein Interaction (PPI) Network analysis to pinpoint hub genes associated with BD. Subsequently, we utilized Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to identify hub genes relevant to OS. To evaluate the diagnostic accuracy of these hub genes, we performed receiver operating characteristic curve (ROC) analysis on both GSE5388 and GSE5389 datasets. Furthermore, we conducted a study involving ten BD patients and ten healthy controls (HCs) who met the special criteria, assessing the expression levels of these hub genes in their peripheral blood mononuclear cells (PBMCs). We identified 411 down-regulated genes and 69 up-regulated genes for further scrutiny. Through WGCNA, we obtained 22 co-expression modules, with the sienna3 module displaying the strongest association with BD. By integrating differential analysis with genes linked to OS, we identified 44 common genes. Subsequent PPI Network and WGCNA analyses confirmed three hub genes as potential biomarkers for BD. Functional enrichment pathway analysis revealed their involvement in neuronal signal transduction, oxidative phosphorylation, and metabolic obstacle pathways. Using the Cytoscape plugin "ClueGo assay," we determined that a majority of these targets regulate neuronal synaptic plasticity. ROC curve analysis underscored the excellent diagnostic value of these three hub genes. Quantitative reverse transcription-PCR (RT-qPCR) results indicated significant changes in the expression of these hub genes in the PBMCs of BD patients compared to HCs. We identified three hub genes (TAC1, MAP2K1, and MAP2K4) in BD associated with OS, potentially influencing the diagnosis and treatment of BD. Based on the GEO database, our study provides novel insights into the relationship between BD and OS, offering promising therapeutic targets.

An Update on the Efficacy of Single and Serial Intravenous Ketamine Infusions and Esketamine for Bipolar Depression: A Systematic Review and Meta-Analysis.

Ketamine has shown rapid antidepressant and anti-suicidal effects in treatment-resistant depression (TRD) with single and serial intravenous (IV) infusions, but the effectiveness for depressive episodes of bipolar disorder is less clear. We conducted an updated systematic review and meta-analysis to appraise the current evidence on the efficacy and tolerability of ketamine/esketamine in bipolar depression. A search was conducted to identify randomized controlled trials (RCTs) and non-randomized studies examining single or multiple infusions of ketamine or esketamine treatments. A total of 2657 articles were screened; 11 studies were included in the systematic review of which 7 studies were included in the meta-analysis (five non-randomized, N = 159; two RCTs, N = 33) with a mean age of 42.58 ± 13.1 years and 54.5% females. Pooled analysis from two RCTs showed a significant improvement in depression symptoms measured with MADRS after receiving a single infusion of ketamine (1-day WMD = -11.07; and 2 days WMD = -12.03). Non-randomized studies showed significant response (53%, p < 0.001) and remission rates (38%, p < 0.001) at the study endpoint. The response (54% vs. 55%) and remission (30% vs. 40%) rates for single versus serial ketamine infusion studies were similar. The affective switch rate in the included studies approximated 2.4%. Esketamine data for bipolar depression are limited, based on non-randomized, small sample-sized studies. Further studies with larger sample sizes are required to strengthen the evidence.

Bipolar Disorder and Antidepressant Associated Hypomania

The impact of antidepressant associated hypomania on monomanic depression and its relationship to bipolar disorder. This review attempts to investigate and review current research on bipolar disorder diagnosis, the neurobiological mechanisms of antidepressant-associated hypomania, risk factors, and how to manage the occurrence of this condition. Bipolar disorder is a widespread, debilitating, recurrent, variable-severity mental health condition in which the patient exhibits two different states and unpredictable mood switching. Mania, hypomania, mixed states, depression, and depression interspersed with moments of relative health are the stages of the disorder. Early identification of bipolar disorder can improve prognosis. Patients with monophasic episodes are uncommon, as the clinical manifestation of bipolar illness is unpredictable. Throughout their lives, individuals with bipolar disorder alternate between episodes of mania or hypomania and depression. Depressive episodes in bipolar disorder are referred to as bipolar depression, and the underlying core symptom is depressed mood, which are essentially identical to the diagnostic criteria and clinical symptoms of uniphasic depression, so there is a high risk of misdiagnosis during the initial visit. Patients often choose to seek specialist help during depressive episodes, and this can lead to a tendency to overlook whether a patient has bipolar disorder. Antidepressant monotherapy is contraindicated for hypomanic episodes. Antidepressants tend to induce hypomanic and manic episodes, a phenomenon known as antidepressant-associated hypomania (AAH). All antidepressant drugs may cause mania. One is drug induced mania; The other is considered a potential bipolar disorder. There is a high co-occurrence of psychiatric disorders, but only bipolar disorder, monophasic depression, and antidepressant-induced hypomanic episodes are discussed here.

Explainable machine-learning algorithms to differentiate bipolar disorder from major depressive disorder using self-reported symptoms, vital signs, and blood-based markers

Background and objectiveCaused by shared genetic risk factors and similar neuropsychological symptoms, bipolar disorder (BD) and major depressive disorder (MDD) are at high risk of misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. We aimed to develop a machine learning (ML)-based diagnostic system, based on electronic medical records (EMR) data, to mimic the clinical reasoning of human physicians to differentiate MDD and BD (especially BD depressive episodes) patients about to be admitted to a hospital and, hence, reduce the misdiagnosis of BD as MDD on admission. In addition, we examined to what extent our ML model could be made interpretable by quantifying and visualizing the features that drive the predictions. MethodsBy identifying 16,311 patients admitted to a hospital located in western China between 2009 and 2018 with a recorded main diagnosis of MDD or BD, we established three sub-cohorts with different combinations of features for both the MDD-BD cohort and the MDD-BD depressive episodes cohort, respectively. Four different ML algorithms (logistic regression, extreme gradient boosting (XGBoost), random forest, and support vector machine) and four train-test splits were used to train and validate diagnostic models, and explainable methods (SHAP and Break Down) were utilized to analyze the contribution of each of the features at both population-level and individual-level, including feature importance, feature interaction, and feature effect on prediction decision for a specific subject. ResultsThe XGBoost algorithm provided the best test performance (AUC: 0.838 (0.810–0.867), PPV: 0.810 and NPV: 0.834) for separating patients with BD from those with MDD. Core predictors included symptoms (mood-up, exciting, bad sleep, loss of interest, talking, mood-down, provoke), along with age, job, myocardial enzyme markers (creatine kinase, hydroxybutyrate dehydrogenase), diabetes-associated marker (glucose), bone function marker (alkaline phosphatase), non-enzymatic antioxidant (uric acid), markers of immune/inflammation (white blood cell count, lymphocyte count, basophil percentage, monocyte count), cardiovascular function marker (low density lipoprotein), renal marker (total protein), liver biochemistry marker (indirect bilirubin), and vital signs like pulse. For separating patients with BD depressive episodes from those with MDD, the test AUC was 0.777 (0.732–0.822), with PPV 0.576 and NPV 0.899. Additional validation in models built with self-reported symptoms removed from the feature set, showed test AUC of 0.701 (0.666–0.736) for differentiating BD and MDD, and AUC of 0.564 (0.515–0.614) for detecting patients in BD depressive episodes from MDD patients. Validation in the datasets without removing the patients with comorbidity showed an AUC of 0.826 (0.806–0.846). ConclusionThe diagnostic system accurately identified patients with BD in various clinical scenarios, and differences in patterns of peripheral markers between BD and MDD could enrich our understanding of potential underlying pathophysiological mechanisms of them.

Ketamine infusions for treatment-resistant bipolar depression: Commentary.

Ketamine infusions for treatment-resistant bipolar depression: Commentary.

Focus on olanzapine

No AccessFocus on olanzapine S Davis S Davis1 Search for more papers by this author Affiliations 1Amayeza Info Services, South Africa Published Online:1 Mar 2023https://doi.org/10.36303/SAGP.0172https://hdl.handle.net/10520/ejc-mp_sagp_v4_n2_a8SectionsPDFView Full Text ToolsAdd to favouritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InRedditGMailOutlookCopy LinkMendeley AboutAbstractOlanzapine is indicated for the management of manifestations of psychotic disorders, acute episodes of moderate to severe mania, and prevention of recurrence of manic or depressive episodes of bipolar disorder.1,21. Rossiter DSouth African Medicines Formulary14thCape TownSouth African Medical Association2022 Google Scholar2. Zyprexa (olanzapine tablets, VELOTAB and Powder for IM injection)Package Insert Eli Lilly (S.A.) (Pty) LimitedBryanston1Dec2006 Google Scholar3. "Olanzapine" MerativeTM Micromedex® DRUGDEX® (electronic version)MerativeAnn Arbor, Michigan, USAAvailable from: https://www.micromedexsolutions.com/Accessed 10 Feb 2023 Google Scholar4. Thomas KSaadabadi A "Olanzapine. Updated 8 Sept 2022" StatPearls [Internet]Treasure Island (FL)StatPearls Publishing2022JanAvailable from: https://www.ncbi.nlm.nih.gov/books/NBK532903/Accessed 10 Feb 2023 Google Scholar5. Bobo WVShelton RC "Bipolar major depression in adults: Efficacy and adverse effects of second-generation antipsychotics. Updated 1 Aug 2022" UpToDateAvailable from: https://www.uptodate.com/contents/bipolar-major-depression-in-adults-efficacy-and-adverse-effects-of-second-generation-antipsychoticsAccessed 10 Feb 2023 Google Scholar6. Zhang JPGallego JARobinson DGet al. "Efficacy and safety of individual second-generation vs first-generation antipsychotics in first episode psychosis: A systematic review and meta-analysis" Int J Neuropsychopharmacol2013 166120518 DOI: https://doi.org/10.1017/S1461145712001277 Google Scholar Previous article Next article FiguresReferencesRelatedDetails None Volume 4, Issue 2 | Mar 2023 Downloaded 6 times LanguagesEnglish InformationCopyright © 2023, Medpharm Publications:All rights reservedPDF download Disclosure The authors confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. The authors confirm that they have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. Ethical conduct of research The authors state that they have obtained appropriate institutional review board outlined in the Declaration of Helsinki for all human or animal experimental investigations. A signed informed consent document has been obtained from all participants included in the study.

Characteristics and Correlates of Metabolic Syndrome in Adolescents with Unipolar and Bipolar Depression: Results from a Cross-National Inpatient Case-Control Study.

<b>Abstract</b> <b><i>Objectives:</i></b> To assess characteristics and correlates of metabolic syndrome (MetS) in adolescents with major depressive disorder (MDD) or bipolar disorder-depressive episode (BP-d). <b><i>Methods:</i></b> Case-control study, using national inpatient sample data, including adolescents (age, 12-18 years) with a primary diagnosis of MDD or BP-d. Using propensity score matching (based on age, sex, and race/ethnicity), we extracted cases with MetS (≥3 of the following conditions: obesity, diabetes, hypercholesterolemia, and hypertension) and controls without MetS. We used a multivariable logistic regression model calculating adjusted odds ratios (aORs) for potential correlates of MetS, focusing on primary mood disorders and psychiatric comorbidities. <b><i>Results:</i></b> In 607 age-/sex-/race/ethnicity-matched adolescents (MDD = 83.5%, BP-d = 16.5%), comparing those with (<i>N</i> = 332) versus without MetS (<i>N</i> = 275), MetS was most prevalent in later-age adolescents (mean age 16.3 years), females (58.1%), Whites (40.3%), and Blacks (31.5%). MetS was characterized by obesity (84.9% vs. 3.6%), hypertension (81% vs. 1.8%), diabetes (72.8% vs. 9.1%), and hypercholesterolemia (67.2% vs. 3.6%) (all <i>p</i> &lt; 0.001). MetS was associated with a primary diagnosis of BP-d versus MDD (aOR 2.42, 95% confidence interval [CI] 1.47-3.97) and comorbid disruptive behavior disorders (DBD) (aOR 4.45, 95% CI 1.55-12.78), while comorbid substance use disorder reduced MetS risk (aOR 0.31, 95% CI 0.19-0.50). <b><i>Conclusion:</i></b> In adolescents with MDD or BP-d, MetS was associated with a primary BP-d diagnosis, and comorbid DBD. MetS-related parameters should be screened for early in adolescents with depression-spectrum disorders aiming to prevent the development or effects of MetS.

STEVEN JOHNSONS SYNDROM ON LAMOTRIGINE

Introduction: Lamotrigine is an anti-epileptic drug indicated for the treatment of bipolar disorder and recurrent depressive disorders. Its efficacy has been demonstrated. However, its use may be limited by the risk of severe, life-threatening allergic reactions. Objectives And Methods: We report hereafter the clinical case of a patient suffering from bipolar depression treated with lamotrigine which induced skin allergies in her. Our objective will be to detail the rules of prescribing the treatment, to describe Steven Johnson syndrome, a serious adverse effect to lamotrigine, to discuss the urgent course of action in the event of severe allergic reactions to lamotrigine as well as the therapeutic options after a hypersensitivity reaction to lamotrigine. Clinical Vignette:This is a patient followed in psychiatry for bipolar disorder, put on esitalopram clomipramine, aripiprazole and Lamotrigine, who was admitted to dermatology for minimal erythematous maculo-papular rash on the face and limbs with involvement of the oral and genital mucosa appeared 4 weeks after introduction of lamotrigine. Conclusion: Despite the efficacy of lamotrigine as an effective mood regulator in the treatment of recurrent depressive episodes and depressive episodes in bipolar disorder, this antiepileptic drug must be used with caution to avoid serious life-threatening reactions.

Effects of Treatment of Acute Major Depressive Episodes in Bipolar I Versus Bipolar II Disorders With Quetiapine.

Several second-generation antipsychotic drugs (SGAs) have evidence of benefit for acute major depressive episodes in bipolar disorder (BD) patients. However, their comparative efficacy in types I vs II BD (BD1 vs BD2) remains uncertain. We carried out a systematic literature search for randomized, double-blinded, controlled treatment trials for acute major depressive episodes involving head-to-head comparisons of BD1 versus BD2 subjects, followed by meta-analyses and meta-regression modeling. Seven reports met out inclusion criteria, yielding 22 comparisons of SGA versus placebo averaging 8.3 weeks in duration. All trials involved quetiapine, which was much more effective than placebo (pooled standardized mean difference [SMD] = 1.76 [95% confidence interval, 1.40-2.12], P < 0.0001). Estimated % improvement averaged 53.5% [46.5-60.5] with quetiapine vs 39.8% [34.2-45.4] with placebo ( P < 0.0001); their ratio was somewhat larger with BD1 (1.56 [1.26-1.86]) versus BD2 subjects (1.22 [1.07-1.37], P = 0.04; as was SMD (BD1: 2.35 [1.83-2.86]; BD2: SMD = 1.44 [1.05-1.82]). Meta-regression found diagnosis (BD1 > BD2) to be the only factor significantly associated with the meta-analytic outcome. Although data are limited, depressed BD1 patients may respond somewhat better to quetiapine than BD2. Additional head-to-head diagnostic comparisons are needed with other SGAs, as well as evaluation of monotherapy versus various combinations that include SGAs in both short- and long-term use.

Investigation of systemic immune-inflammation index, neutrophil/high-density lipoprotein ratio, lymphocyte/high-density lipoprotein ratio, and monocyte/high-density lipoprotein ratio as indicators of inflammation in patients with schizophrenia and bipolar disorder.

BackgroundThe systemic immune-inflammation index (SII), system inflammation response index (SIRI), neutrophil/high-density lipoprotein (HDL) ratio (NHR), lymphocyte/HDL ratio (LHR), monocyte/HDL ratio (MHR), and platelet/HDL ratio (PHR) have been recently investigated as new markers for inflammation. The purpose of this research is to use large-scale clinical data to discuss and compare the predictive ability of the SII, SIRI, NHR, LHR, MHR, and PHR in patients with schizophrenia (SCZ) and bipolar disorder (BD), to investigate potential biomarkers.Materials and methodsIn this retrospective, naturalistic, cross-sectional study, we collected the hematological parameter data of 13,329 patients with SCZ, 4,061 patients with BD manic episodes (BD-M), and 1,944 patients with BD depressive episodes (BD-D), and 5,810 healthy subjects served as the healthy control (HC) group. The differences in the SII, SIRI, NHR, LHR, MHR, and PHR were analyzed, and a receiver operating characteristic (ROC) curve was used to analyze the diagnostic potential of these parameters.ResultsCompared with the HC group, the values of the SII, SIRI, NHR, LHR, MHR, and PHR and the levels of neutrophils, monocytes, and triglycerides (TG) were higher in SCZ and BD groups, and levels of platelets, cholesterol (CHO), HDL, low-density lipoprotein (LDL), and apoprotein B (Apo B) were lower in SCZ and BD groups. Compared to the BD group, the values of the SIRI, lymphocytes, monocytes, and HDL were lower and the values of the SII, NHR, PHR, and platelet were higher in the SCZ group. In contrast to the BD-D group, the values of the SII; SIRI; NHR; and MHR; and levels of neutrophils, monocytes, and platelets were higher in the BD-M group, and the levels of CHO, TG, LDL, and Apo B were lower in the BD-M group. The MHR and NHR were predictors for differentiating the SCZ group from the HC group; the SIRI, NHR, and MHR were predictors for differentiating the BD-M group from the HC group; and the MHR was a predictor for differentiating the BD-D group from the HC group. The combination model of the indicators improved diagnostic effectiveness.ConclusionOur study highlights the role of systemic inflammation in the pathophysiology of SCZ, BD-M, and BD-D, the association between inflammation and lipid metabolism, and these inflammation and lipid metabolism indicators showed different variation patterns in SCZ, BD-D, and BD-M.