Diagnosis Of Bipolar Disorder Research Articles

Toxoplasma gondii IgG serointensity and cognitive function in bipolar disorder

BackgroundAlongside affective episodes, cognitive dysfunction is a core symptom of bipolar disorder. The intracellular parasite T. gondii has been positively associated with both, the diagnosis of bipolar disorder and poorer cognitive performance, across diagnostic boundaries. This study aims to investigate the association between T. gondii seropositivity, serointensity, and cognitive function in an euthymic sample of bipolar disorder.MethodsA total of 76 participants with bipolar disorder in remission were tested for T. gondii-specific IgG and IgM antibodies and for cognitive performance using neuropsychological test battery. Cognitive parameters were categorized into three cognitive domains (attention and processing speed, verbal memory, and executive function). Statistical analysis of associations between continuous indicators of cognitive function as dependent variables in relationship to T. gondii, included multivariate analyses of co-variance for seropositivity, and partial correlations with IgG serointensity in IgG seropositives. All analyses were controlled for age and premorbid IQ.ResultsIn seropositives (n = 27), verbal memory showed significant inverse partial correlations with IgG antibody levels (short delay free recall (r=–0.539, p = 0.005), long delay free recall (r=–0.423, p = 0.035), and immediate recall sum trial 1–5 (r=–0.399, p = 0.048)). Cognitive function did not differ between IgG seropositive and seronegative individuals in any of the cognitive domains (F (3,70) = 0.327, p = 0.806, n = 76). IgM positives (n = 7) were too few to be analyzed.ConclusionsThis investigation is the first to show an association between T. gondii IgG serointensity and memory function in a well-diagnosed bipolar disorder sample. It adds to the existing literature on associations between latent T. gondii infection and cognition in bipolar disorder, while further research is needed to confirm and expand our findings, eliminate potential sources of bias, and establish cause-effect relationships.

Mood stabilizers for treatment of bipolar disorder in pregnancy and impact on neonatal outcomes.

Untreated bipolar disorder in pregnancy is associated with adverse maternal and neonatal outcomes. Despite advances in clinical management, there is concern among obstetric providers and patients about the safety of pharmacological agents for the treatment of bipolar disorder in pregnancy. Recent studies have shown atypical antipsychotics and lamotrigine to have a favorable safety profile; however, little information is published on lurasidone. The objective of this retrospective chart review was to evaluate pregnancy and neonatal outcomes in obstetric patients with bipolar disorder who are untreated, compared to those treated with lurasidone, other atypical antipsychotics, and lamotrigine at a tertiary teaching institution. This retrospective cohort study included neonates whose mothers had a diagnosis of bipolar disorder and were referred to the Maternal & Fetal Care Clinic with two documented visits after January 1, 2014, with delivery by October 31, 2017, within an SSM health-system hospital. In this study, women with untreated bipolar disorder (not on any mood stabilizer) in pregnancy had significantly higher rates of premature delivery and low birth weight compared to women on mood stabilizers of lamotrigine, lurasidone, and other atypical antipsychotics. No difference was observed for pregnancy or neonatal outcomes between patients taking any of the mood stabilizers. This study suggests that the use of lurasidone, other atypical antipsychotics, and lamotrigine have better neonatal outcomes than untreated bipolar disorder in pregnancy.

Oral health knowledge, attitudes, and practices of people living with mental illness: a mixed-methods systematic review

People living with mental illness experience poorer oral health outcomes compared to the general population, yet little is known about their oral health knowledge, attitudes, and practices. The aim of this mixed-methods systematic review was to synthesise evidence regarding oral health knowledge, attitudes, and practices of people living with mental illness to inform preventative strategies and interventions. Database searches were conducted in PubMed, MEDLINE, PsycINFO, CINAHL, ProQuest, and Scopus with no limitations placed on the year of study. All studies available in the English language, that explored the oral health knowledge, attitudes, and/or practices of people with a mental illness were included. Articles were excluded if they primarily pertained to intellectual disability, behavioural and psychological symptoms of dementia, drug and alcohol or substance use, or eating disorders. A thematic synthesis was undertaken of 36 studies (26 high-moderate quality), resulting in 3 themes and 9 sub-themes. Study participants ranged from n = 7 to n = 1095 and aged between 15–83 years with most having a diagnosis of schizophrenia, schizoaffective, or bipolar affective disorder. People diagnosed with a mental illness were found to have limited oral health knowledge, particularly regarding the effects of psychotropic medication. Various barriers to oral health care were identified, including high dental costs, the negative impact of mental illness, dental fears, lack of priority, and poor communication with dental and health care providers. Study participants often displayed a reduced frequency of tooth brushing and dental visits. The findings highlight the potential for mental health care providers, oral health and dental professionals, mental health consumers, and carers to work together more closely to improve oral health outcomes for people with mental illness. The systematic review protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO), (registration ID CRD42022352122).

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder

BackgroundSchizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine learning-based studies have shown encouraging results using diagnostic biomarkers in predictive models, but few have focused on immune-based markers. Our main objective was to develop supervised machine learning models to predict diagnosis and illness state in schizophrenia and bipolar disorder using only a panel of peripheral kynurenine metabolites and cytokines. MethodsThe cross-sectional I-GIVE cohort included hospitalized acute bipolar patients (n = 205), stable bipolar outpatients (n = 116), hospitalized acute schizophrenia patients (n = 111), stable schizophrenia outpatients (n = 75) and healthy controls (n = 185). Serum kynurenine metabolites, namely tryptophan (TRP), kynurenine (KYN), kynurenic acid (KA), quinaldic acid (QUINA), xanthurenic acid (XA), quinolinic acid (QUINO) and picolinic acid (PICO) were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS), while V-plex Human Cytokine Assays were used to measure cytokines (interleukin-6 (IL-6), IL-8, IL-17, IL-12/IL23-P40, tumor necrosis factor-alpha (TNF-ɑ), interferon-gamma (IFN-γ)). Supervised machine learning models were performed using JMP Pro 17.0.0. We compared a primary analysis using nested cross-validation to a split set as sensitivity analysis. Post-hoc, we re-ran the models using only the significant features to obtain the key markers. ResultsThe models yielded a good Area Under the Curve (AUC) (0.804, Positive Prediction Value (PPV) = 86.95; Negative Prediction Value (NPV) = 54.61) for distinguishing all patients from controls. This implies that a positive test is highly accurate in identifying the patients, but a negative test is inconclusive. Both schizophrenia patients and bipolar patients could each be separated from controls with a good accuracy (SCZ AUC 0.824; BD AUC 0.802). Overall, increased levels of IL-6, TNF-ɑ and PICO and decreased levels of IFN-γ and QUINO were predictive for an individual being classified as a patient. Classification of acute versus stable patients reached a fair AUC of 0.713. The differentiation between schizophrenia and bipolar disorder yielded a poor AUC of 0.627. ConclusionsThis study highlights the potential of using immune-based measures to build predictive classification models in schizophrenia and bipolar disorder, with IL-6, TNF-ɑ, IFN-γ, QUINO and PICO as key candidates. While machine learning models successfully distinguished schizophrenia and bipolar disorder from controls, the challenges in differentiating schizophrenic from bipolar patients likely reflect shared immunological pathways by the both disorders and confounding by a larger state-specific effect. Larger multi-centric studies and multi-domain models are needed to enhance reliability and translation into clinic.

Hospital-treated bipolar disorder in adolescence in Finland 1980-2010: Rehospitalizations, diagnostic stability, and mortality.

Estimates of the occurrence of bipolar disorder among adolescents vary from country to country and from time to time. Long delays from first symptoms to diagnosis of bipolar disorder have been suggested. Studies among adults suggest increased mortality, particularly due to suicide and cardiovascular diseases. We set out to study the prognosis of adolescent onset bipolar disorder in terms of rehospitalizations, diagnostic stability, and mortality. The study comprised a register-based follow-up of all adolescents admitted to psychiatric inpatient care for the first time in their lives at age 13-17 during the period 1980-2010. They were followed up in the National Care Register for Health Care and Causes of death registers until 31 December 2014. Incidence of bipolar disorder among 13- to 17-year-old adolescents over the whole study period was 2.8 per 100, 000 same aged adolescents, and across decades, the incidence increased six-fold. Patients with bipolar disorder during their first-ever inpatient treatment were rehospitalized more often than those treated for other reasons. Conversion from bipolar disorder to other diagnoses was far more common than the opposite. Mortality did not differ between those firstdiagnosed with bipolar disorder and those treated for other reasons. The incidence of adolescent onset bipolar disorder has increased across decades. The present study does not call for attention to delayed diagnosis of bipolar disorder. Adolescent onset bipolar disorders are severe disorders that often require rehospitalization, but diagnostic stability is modest. Mortality is comparable to that in other equally serious disorders.

Predictors of psychosocial impairment in a transdiagnostic sample: Unique effects of repetitive negative thinking

BackgroundRepetitive negative thinking (RNT) is a transdiagnostic process involving perseverative, unproductive, and uncontrollable thoughts. Although RNT may impede adaptive psychosocial functioning by prolonging negative mood states, strengthening cognitive biases, and preventing effective problem-solving, the extent to which RNT is associated with risk for poor psychosocial outcomes is unclear. Given that this has clear transdiagnostic treatment implications, the present study aimed to isolate the unique relationship of RNT with social functioning and life satisfaction in a mixed clinical and non-clinical sample. MethodsIn 201 mid-to-later life adult participants (27 with primary diagnoses of bipolar disorder, 84 with major depressive disorder, and 90 healthy volunteers), we measured RNT, social functioning, life satisfaction, trait rumination, DSM-5 diagnoses, depressive symptoms, manic symptoms, cognitive control performance, and global cognitive functioning. ResultsLinear regression models revealed that RNT, but not rumination, was significantly associated with poorer social functioning (β = 0.42 p < .001) and reduced life satisfaction (β = −0.42, p < .001) after controlling for clinical and cognitive covariates. LimitationsLimited demographic diversity, cross-sectional design, self-reporting of outcomes. ConclusionsResults suggest that RNT may confer risk for key psychosocial outcomes during middle to later adulthood, over and above the effects of clinical and cognitive variables and independent of diagnostic status. Findings lend support to the notion of RNT as a transdiagnostic process and suggest that RNT may be an important therapeutic target for adults with poor social functioning and/or reduced life satisfaction.

Clinical and sociodemographic characteristics associated with relapse following electroconvulsive therapy for bipolar disorder.

Electroconvulsive therapy (ECT) is an effective treatment for bipolar disorder, but relapse following a successful ECT series is common. We aimed to identify clinical and sociodemographic characteristics associated with the risk of relapse following ECT in bipolar disorder. Using data from nationwide Danish registers, we identified all patients receiving their first ECT series with an indication diagnosis of bipolar disorder between 2006 and 2018. We then followed these patients for relapse, defined as either psychiatric admission or a new ECT series, for 6 months following ECT. Associations between clinical and sociodemographic characteristics and relapse were examined via multivariable Cox proportional-hazards regression, yielding adjusted hazard rate ratios (aHRR). Of the 1473 patients receiving ECT for bipolar disorder (62% females, mean age = 53 years), 34% met the relapse criterion. The following characteristics were associated with an elevated risk of relapse; age <40 (aHRR = 1.54, 95% CI = 1.05-2.26); being a pensioner (aHRR = 1.73, 95% CI = 1.29-2.32), indication diagnosis for ECT being psychotic mania (aHRR = 1.63, 95% CI = 1.16-2.28), psychotic bipolar depression (aHRR = 1.37, 95% CI = 1.06-1.80), mixed episode (aHRR = 1.51, 95% CI = 1.13-2.02), or other bipolar episodes (aHRR = 1.68, 95% CI = 1.28-2.21); and treatment with antipsychotics prior to the course of ECT (aHRR = 1.32, 95% CI = 1.04-1.67). Patients with bipolar disorder face a particularly high risk of relapse following ECT if they present with the following characteristics when initiating ECT: age <40, being a pensioner, having received treatment with an antipsychotic before initiating ECT, or having psychotic bipolar depression, psychotic mania, mixed episodes, or other bipolar episodes as the indication for ECT. These findings may guide relapse monitoring following ECT in bipolar disorder.

Clinical and sociodemographic features of the Texas resilience against depression (T-RAD) study: Findings from the initial cohort

ObjectiveThe burden of major depressive disorder is compounded by a limited understanding of its risk factors, the limited efficacy of treatments, and the lack of precision approaches to guide treatment selection. The Texas Resilience Against Depression (T-RAD) study was designed to explore the etiology of depression by collecting comprehensive socio-demographic, clinical, behavioral, neurophysiological/neuroimaging, and biological data from depressed individuals (D2K) and youth at risk for depression (RAD). MethodsThis report details the baseline sociodemographic, clinical, and functional features from the initial cohort (D2K N = 1040, RAD N = 365). ResultsOf the total T-RAD sample, n = 1078 (76.73 %) attended ≥2 in-person visits, and n = 845 (60.14 %) attended ≥4 in-person visits. Most D2K (84.82 %) had a primary diagnosis of any depressive disorder, with a bipolar disorder diagnosis being prevalent (13.49 %). RAD participants (75.89 %) did not have a psychiatric diagnosis, but other non-depressive diagnoses were present. D2K participants had 9-item Patient Health Questionnaire scores at or near the moderate range (10.58 ± 6.42 > 24 yrs.; 9.73 ± 6.12 10–24 yrs). RAD participants were in the non-depressed range (2.19 ± 2.65). While the age ranges in D2K and RAD differ, the potential to conduct analyses that compare at-risk and depressed youth is a strength of the study. The opportunity to examine the trajectory of depressive symptoms in the D2K cohort over the lifespan is unique. LimitationsAs a longitudinal study, missing data were common. ConclusionT-RAD will allow data to be collected from multiple modalities on a clinically well-characterized sample. These data will drive important discoveries on diagnosis, treatment, and prevention of depression.

Association of psychiatric and substance use disorders with cannabis use and cannabis use disorder during early pregnancy in northern California.

To estimate the strength of association between psychiatric disorders and substance use disorders (SUD), and cannabis use and cannabis use disorder (CUD)during early pregnancy. Observational study. Kaiser Permanente Northern California, USA. 299 496 pregnancies from 227 555 individuals screened for cannabis use by self-report and a urine toxicology test at entrance to prenatal care in Kaiser Permanente Northern California during January 2011-December 2021 (excepting year 2020). The sample was 62.5% non-White, with a mean (standard deviation) age of 31.1 (5.5) years; 6.8% used cannabis; 0.2% had a CUD. Exposure variables included electronic health record-based psychiatric diagnoses of attention deficit hyperactivity, anxiety, bipolar, depressive, personality, posttraumatic stress and psychotic disorders; and alcohol, opioid, stimulant and tobacco use disorders, during the two years prior to pregnancy up to the day before the prenatal substance use screening date. Outcome variables were any cannabis use, frequency of self-reported cannabis use and CUD during early pregnancy. Psychiatric disorder prevalence ranged from 0.2% (psychotic) to 14.3% (anxiety), and SUD ranged from 0.3% (stimulant/opioid) to 3.8% (tobacco). Psychiatric disorders were associated with cannabis use and CUD, with the strongest association for any use found for bipolar disorder (adjusted odds ratio [aOR] = 2.83; 95% confidence interval [CI] = 2.53-3.17) and the strongest association for CUD found for psychotic disorders (aOR = 10.01, 95% CI = 6.52-15.37). SUDs were associated with cannabis use and CUD, with the strongest association for any use found for tobacco use disorder (aOR = 4.03, 95% CI = 3.82-4.24) and the strongest association for CUD found for stimulant use disorder (aOR = 21.99, 95% CI = 16.53-29.26). Anxiety, bipolar, depressive disorders and tobacco use disorder were associated with greater odds of daily than monthly or less cannabis use. Psychiatric disorders and substance use disorders appear to be associated with elevated odds of any and frequent cannabis use as well as cannabis use disorder during early pregnancy. In most cases, the associations with cannabis outcomes were stronger for substance use disorders than other psychiatric disorders.

Seasonality and sun exposure in incidence of major depression, bipolar disorder, and first-time use of antidepressant medication

Introduction Seasonality in depressive and bipolar disorders, are recognized in the ICD-10/11 and DSM-5 diagnostic systems. The existence of a seasonal pattern of hospital diagnosis of major depression, bipolar disorder and prescription of antidepressant medications has not been evaluated in the Danish population. Methods We retrieved date and year for all first-time hospital contacts with depression or bipolar disorder between 1999 and 2019, registered in the Danish National Patient Registry. Depression was defined using the ICD-10 F32-F33 codes, and for bipolar disorder the F30 or F31 codes. Date and year of all first-time purchases of antidepressant medications with ATC codes (N06A) between 1999 and 2021 were retrieved from the Danish National Prescription Registry, containing information on all prescribed drugs dispensed at pharmacies since 1995. Data on sunlight hours from 2012 to 2021 were retrieved from the Danish Metrological Institute. Results Incidences of hospital diagnoses as well as purchases of medication varied with month and season. The monthly variations were larger for antidepressant medication and smallest for bipolar disorder. The multiple linear regression analysis showed that number of first-time diagnoses of depression or bipolar disorder did not correlate with season. For antidepressant medication the number of first-time prescriptions was significantly lower in summer compared to the winter season. Conclusion This study found a seasonal variation of first-time prescriptions of antidepressant medication. We did not find a seasonal variation in first-time hospital diagnoses. Further research looking into depression severity, polarity of bipolar illness episodes, lag-time for sunlight exposure, and specific parts of the yearly photoperiods should be conducted.

The Prediction of Diagnostic Change From Bipolar Disorder to Schizophrenia and Schizophrenia to Bipolar Disorder in a Population-Based, Longitudinal, National Swedish Sample.

To clarify, in a large, representative, longitudinal sample, the rate and predictors of diagnostic conversion from Bipolar Disorder (BD) to Schizophrenia (SZ) and from SZ→BD. From individuals born in Sweden 1950-1995 and living there in 1970 or later, we identified at least one initial diagnoses of SZ (n = 8449) and BD (n = 8438) followed for a minimum of 10 and a mean of 24 years. Diagnostic conversion required, respectively, at least two final diagnoses of BD and SZ 30 days apart with no intervening diagnosis of SZ or BD. At follow-up, rates of BD→SZ and SZ→BD conversion were 10.1 and 4.5%, respectively. Conversions occurred slowly, with around 50% completed in the first decade. Using a diverse range of variables available at first onset including family genetic risk scores, BD→SZ conversion was predicted with greater accuracy (AUC = 0.78) than SZ→BD conversion (AUC = 0.65). The strongest predictors of BD→SZ conversion were earlier years of birth, younger age at BD onset, low BD genetic risk, and being unmarried at BD onset. SZ→BD conversion was most strongly predicted by high BD genetic risk, being married at SZ onset, female sex, early age at SZ onset, and an MD episode prior to SZ onset. Cases of BD and SZ in the highest decile for conversion risk had HRs for a diagnostic change of, respectively, 12.5 and 3.4. Diagnostic conversion of BD→SZ and SZ→BD are not rare, are moderately predictable, and should likely be accounted for in many research designs.

The Role of Selected Speech Signal Characteristics in Discriminating Unipolar and Bipolar Disorders.

The objective of this study is to explore and enhance the diagnostic process of unipolar and bipolar disorders. The primary focus is on leveraging automated processes to improve the accuracy and accessibility of diagnosis. The study aims to introduce an audio corpus collected from patients diagnosed with these disorders, annotated using the Clinical Global Impressions Scale (CGI) by psychiatrists. Traditional diagnostic methods rely on the clinician's expertise and consideration of co-existing mental disorders. However, this study proposes the implementation of automated processes in the diagnosis, providing quantitative measures and enabling prolonged observation of patients. The paper introduces a speech signal pipeline for CGI state classification, with a specific focus on selecting the most discriminative features. Acoustic features such as prosodies, MFCC, and LPC coefficients are examined in the study. The classification process utilizes common machine learning methods. The results of the study indicate promising outcomes for the automated diagnosis of bipolar and unipolar disorders using the proposed speech signal pipeline. The audio corpus annotated with CGI by psychiatrists achieved a classification accuracy of 95% for the two-class classification. For the four- and seven-class classifications, the results were 77.3% and 73%, respectively, demonstrating the potential of the developed method in distinguishing different states of the disorders.

Reasons for diagnostic delays in Bipolar Disorder: Systematic review and narrative synthesis

BACKGROUND: Bipolar disorder is common, affecting 1% of people. The diagnosis of bipolar disorder is often delayed, which limits access to effective treatment and increases the burden of disease on individuals, families, and society. AIM: This paper investigates the individual, social, and clinical factors that contribute to delays in diagnosis for people with bipolar disorder, including delays that occur before and after a person presents to a primary care clinician. DESIGN AND SETTING: Systematic review and narrative synthesis. METHOD: Four electronic databases - Embase, Medline, PsychInfo, and Global Health - were systematically searched. This search yielded 3078 studies, 21 of which met the inclusion criteria. The data retrieved were analysed using Braun and Clarke’s Thematic Analysis to report a summary of recent research on the delays in the diagnosis of bipolar disorder. RESULTS: Analysis of the data from the 21 studies identified five main themes as reasons for delays in diagnosis: (1) misdiagnosis, (2) healthcare challenges, (3) mental health stigma, (4) the complex nature of bipolar disorder, and (5) individual factors. CONCLUSIONS: The review demonstrates the importance of educating individuals, families, and clinicians on the symptomology of bipolar disorder to avoid misdiagnosis. Furthermore, changes in the accessibility and delivery of mental health services are essential to ensure that people with bipolar disorder are diagnosed and treated in a timely manner. In addition, mental health stigma among individuals, families, and clinicians must be addressed to reduce diagnostic delays.

Polygenic scores for psychiatric disorders associate with year of first bipolar disorder diagnosis: A register-based study between 1972 and 2016

The diagnostic criteria of bipolar disorder (BD) have changed over time. To test if these changes are reflected in the polygenic profile in BD, we studied the association between first BD diagnosis year (during 1972–2016) and polygenic scores (PGS) for psychiatric disorders in BD patients (N = 3,818). We found significant associations between diagnosis year and PGS for BD, depression, and attention deficit hyperactivity disorder (ADHD). The PGS remained largely stable over time in BD type 1, while changes were observed in BD type 2. These findings bear significance not only for genetic research but also for clinical practise, as shifts in patient characteristics can influence treatment response.

Media Use and Its Associations With Paranoia in Schizophrenia and Bipolar Disorder: Ecological Momentary Assessment.

Paranoia is a spectrum of fear-related experiences that spans diagnostic categories and is influenced by social and cognitive factors. The extent to which social media and other types of media use are associated with paranoia remains unclear. We aimed to examine associations between media use and paranoia at the within- and between-person levels. Participants were 409 individuals diagnosed with schizophrenia spectrum or bipolar disorder. Measures included sociodemographic and clinical characteristics at baseline, followed by ecological momentary assessments (EMAs) collected 3 times daily over 30 days. EMA evaluated paranoia and 5 types of media use: social media, television, music, reading or writing, and other internet or computer use. Generalized linear mixed models were used to examine paranoia as a function of each type of media use and vice versa at the within- and between-person levels. Of the 409 participants, the following subgroups reported at least 1 instance of media use: 261 (63.8%) for using social media, 385 (94.1%) for watching TV, 292 (71.4%) for listening to music, 191 (46.7%) for reading or writing, and 280 (68.5%) for other internet or computer use. Gender, ethnoracial groups, educational attainment, and diagnosis of schizophrenia versus bipolar disorder were differentially associated with the likelihood of media use. There was a within-person association between social media use and paranoia: using social media was associated with a subsequent decrease of 5.5% (fold-change 0.945, 95% CI 0.904-0.987) in paranoia. The reverse association, from paranoia to subsequent changes in social media use, was not statistically significant. Other types of media use were not significantly associated with paranoia. This study shows that social media use was associated with a modest decrease in paranoia, perhaps reflecting the clinical benefits of social connection. However, structural disadvantage and individual factors may hamper the accessibility of media activities, and the mental health correlates of media use may further vary as a function of contents and contexts of use.

Treatment of bipolar depression: clinical practice vs. adherence to guidelines-data from a Bavarian drug surveillance project.

Pharmacotherapy of bipolar depression (BPD) is confronted with major clinical challenges, like limited evidence-based treatment options, regular cases of treatment resistance, and risk of treatment-emergent affective switches. Medical guidelines can support practitioners to make decisions based on current scientific evidence. The objective of this study is to evaluate to what extent recommendations of the 2019 German S3 guidelines "Diagnosis and Treatment of Bipolar Disorders" are reflected in clinical practice in inpatient treatment. We conducted a descriptive analysis of prescription numbers in 2,627 patients with BPD in a naturalistic inpatient setting analyzing data from the ongoing Bavarian multicenter drug safety project Pharmaco-Epidemiology and Vigilance (Pharmako-EpiVig) from the years 2014-2022. Of the patients, 38% were not administered any drug explicitly recommended for treatment of BPD, that is, quetiapine, lamotrigine, carbamazepine, or olanzapine. Only 6% of the patients received monotherapy with one of those drugs. Of the patients, 34% were administered ≥4 psychotropic drugs simultaneously. Patients received 912 different therapy regimens of mono or combination therapy with mood stabilizers (MS), atypical antipsychotics (AAP), and antidepressants. Of the patients, 72% received an antidepressant and 6% without concomitant prescription of an AAP or MS. Prescription rates of venlafaxine (21% to 14%) and tricyclic antidepressants (9% to 6%) decreased significantly from the first (2014-2016) to the last (2020-2022) observed time period. Of the patients, 60% received an MS. Prescription rate of valproate (22% to 14%) decreased significantly, while lithium prescription increased significantly (29% to 35%). Of the patients, 71% were administered an AAP. Quetiapine was the most prescribed drug overall (43%). Only two patients were administered a combination of olanzapine and fluoxetine. Our results demonstrate a substantial gap between guideline recommendations and current clinical practice. The remarkable heterogeneity in treatment regimens, with no discernible dominant treatment approach, is in part a reflection of the complexity of bipolar disorder but also substantiates the need of comprehensive recommendations regarding combination therapies. Increase in lithium prescription is an encouraging development due to its unique efficacy in maintenance treatment. To improve the quality of clinical practice guideline implementation, more randomized controlled trials shouldbeconducted in the future to prospectively investigate different implementation strategies.

Enhancing Early Diagnosis of Bipolar Disorder in Adolescents Through Multimodal Neuroimaging

BackgroundBipolar disorder (BD), a severe neuropsychiatric condition, often appears during adolescence. Traditional diagnostic methods, which primarily rely on clinical interviews and single-modal magnetic resonance imaging (MRI) techniques, may have limitations in accuracy. This study aimed to improve adolescent BD diagnosis by integrating behavioral assessments with multimodal MRI. We hypothesized that this combination would enhance diagnostic accuracy for at-risk adolescents. MethodsA retrospective cohort of 309 participants, including patients with BD, offspring of patients with BD (with and without subthreshold symptoms), non-BD offspring with subthreshold symptoms, and healthy control participants, was analyzed. Behavioral attributes were integrated with MRI features from T1-weighted, resting-state functional MRI, and diffusion tensor imaging. Three diagnostic models were developed using GLMNET multinomial regression: a clinical diagnosis model based on behavioral attributes, an MRI-based model, and a comprehensive model integrating both datasets. ResultsThe comprehensive model achieved a prediction accuracy of 0.83 (95% CI, 0.72–0.92), significantly higher than the clinical (0.75) and MRI-based (0.65) models. Validation with an external cohort showed high accuracy (0.89, area under the curve = 0.95). Structural equation modeling revealed that clinical diagnosis (β = 0.487, p < .0001), parental BD history (β = −0.380, p < .0001), and global function (β = 0.578, p < .0001) significantly affected brain health, while psychiatric symptoms showed only a marginal influence (β = −0.112, p = .056). ConclusionsThis study highlights the value of integrating multimodal MRI with behavioral assessments for early diagnosis in at-risk adolescents. Combining neuroimaging enables more accurate patient subgroup distinctions, facilitating timely interventions and improving health outcomes. Our findings suggest a paradigm shift in BD diagnostics, advocating for incorporating advanced imaging techniques in routine evaluations.

Analysis of the impact of legal circumstances on schizophrenia and bipolar disorder hospitalizations in Portugal: a nationwide study

ABSTRACT The main goal of this project was to evaluate the clinical and sociodemographic characteristics of patients hospitalized with schizophrenia or bipolar disorder and the register of legal circumstances. A descriptive study was conducted using a nationwide hospitalization administrative database that contains all admissions registered in public hospitals across mainland Portugal. All discharges between 2008 and 2015 with a primary diagnosis of schizophrenia or bipolar disorder were selected. Legal problems (LP) at the moment of hospitalization were identified based on the presence of a secondary diagnosis of the ICD-9-CM code V62.5 ‘Legal circumstances: Imprisonment; Legal investigation; Litigation; or Prosecution’. A total of 25,835 and 20,807 hospitalizations with a primary diagnosis of schizophrenia and bipolar disorder were analysed, respectively. Approximately 11.8% (n = 3,005) of schizophrenia hospitalizations and 6.0% (n = 1250) of bipolar disorder hospitalizations were associated with registered legal circumstances. Legal circumstances were associated with younger patients, male sex, and a longer length of stay. One in four episodes linked to LP was associated with drug abuse and/or dependence.

Factors Associated with High Parent- and Youth-Rated Irritability Score in Early-Onset Mood Disorders: A Cross-Sectional Study with the Affective Reactivity Index (ARI).

Correct classification of irritability is extremely important to assess prognosis and treatment indications of juvenile mood disorders. We assessed factors associated with low versus high parent- and self-rated irritability using the affective reactivity index (ARI) in a sample of 289 adolescents diagnosed with a bipolar or a major depressive disorder. Bivariate analyses were followed by multilinear logistic regression model. Factors significantly and independently associated with high versus low parent-rated ARI score were: more severe emotional dysregulation and bipolar disorders diagnosis. Factors significantly and independently associated with high versus low self-rated ARI score were: lower children depression rating scale (CDRS-R) difficulty of having fun item score, greater children depression inventory (CDI-2) self-report score, more severe emotional dysregulation, and greater CDRS-R appetite disturbance item score. High parent-rated irritability was strictly related with a bipolar disorder diagnosis, whereas high youth-rated irritability was related to depressive phenotype characterized by appetite/food-intake dysregulation, mood lability, and less anhedonia and apathy.

An e-Health Psychoeducation Program for Managing the Mental Health of People with Bipolar Disorder during the COVID-19 Pandemic: A Randomized Controlled Study.

Background: Social rhythm dysregulation has been identified as a determining factor in bipolar disorder (BD) relapses. It directly impacts individuals' quality of life (QoL). This study aims to present preliminary data on the efficacy of an e-health psychoeducational intervention for BD for improving clinical outcomes. Methods: This study used an open-label, crossover, randomized controlled trial design. The inclusion criteria consisted of a BD diagnosis, affiliation with the Consultation Psychiatry and Psychosomatic Center at the University Hospital in Cagliari, Italy, age over 18, and the obtaining of informed consent. Anxiety and depressive symptoms, QoL, and social and biological rhythms were measured using standardized instruments validated in Italian. Results: A total of 36 individuals were included in the experimental group (EG) and 18 in the control group (CG). The final sample consisted of 25 in the EG and 14 in the CG. A statistically significant improvement in QoL was found in the EG post-treatment (p = 0.011). Significant correlations were found between QoL and the dysregulation of biorhythms in the EG at T0 (p = 0.0048) and T1 (p = 0.0014). Conclusions: This study shows that, during extreme distress, an e-health group psychoeducation intervention for people with BD could significantly improve the perception of QoL. The results must be confirmed by studies conducted with larger-sized samples.