Clinical distinctions in symptomatology and psychiatric comorbidities between misdiagnosed bipolar I and bipolar II disorder versus major depressive disorder.

BACKGROUND: To explore the demographic and clinical features of current depressive episode that discriminate patients diagnosed with major depressive disorder (MDD) from those with bipolar I (BP-I) and bipolar II (BP-II) disorder who were misdiagnosed as having MDD . METHODS: The Mini-International Neuropsychiatric Interview (MINI) assessment was performed to establish DSM-IV diagnoses of MDD, and BP-I and BP-II, previously being misdiagnosed as MDD. Demographics, depressive symptoms and psychiatric comorbidities were compared between 1463 patients with BP-I, BP-II and MDD from 8 psychiatric settings in mainland China. A multinomial logistic regression model was performed to assess clinical correlates of diagnoses. RESULTS: A total of 14.5% of the enrolled patients initially diagnosed with MDD were eventually diagnosed with BP. Broad illness characteristics including younger age, higher prevalence of recurrence, concurrent dysthymia, suicidal attempts, agitation, psychotic features and psychiatric comorbidities, as well as lower prevalence of insomnia, weight loss and somatic symptoms were featured by patients with BP-I and/or BP-I, compared to those with MDD. Comparisons between BP-I and BP-II versus MDD indicated distinct symptom profiles and comorbidity patterns with more differences being observed between BP-II and MDD, than between BP-I and MDD . CONCLUSION: The results provide evidence of clinically distinguishing characteristics between misdiagnosed BP-I and BP- II versus MDD. The findings have implications for guiding more accurate diagnoses of bipolar disorders.

Not missing at random: Missing data are associated with clinical status and trajectories in an electronic monitoring longitudinal study of bipolar disorder.

There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.

Perinatal photoperiod associations with bipolar disorder and depression: A systematic literature review and cross-sectional analysis of the UK Biobank database.

Season-of-birth associations with psychiatric disorders point to environmental (co-)aetiological factors such as natural photoperiod that, if clarified, may allow interventions toward prevention. We systematically reviewed the literature concerning season-of-birth and bipolar disorder and depression and explored associations between the perinatal natural photoperiod and these outcomes in a cross-sectional analysis of the UK Biobank database. We used mean daily photoperiod and relative photoperiod range (relative to the mean) in the 3rd trimester and, separately, in the first 3 months post birth as metrics. From review, increased risk of depression with late spring birth is compatible with increased odds of probable single episode-, probable recurrent-, and diagnosed depression (OR 2.85 95 %CI 1.6-5.08, OR 2.20 95 %CI 1.57-3.1, and OR 1.48 95 %CI 1.11-1.97, respectively) with increasing 3rd trimester relative photoperiod range for participants who experienced relatively non-extreme daily photoperiods. Risk of bipolar disorder with winter-spring birth contrasted with no consistent patterns of perinatal photoperiod metric associations with bipolar disorder in the UK Biobank. As natural photoperiod varies by both time-of-year and latitude, perinatal natural photoperiods (and a hypothesized mechanism of action via the circadian timing system and/or serotonergic circuitry associated with the dorsal raphe nucleus) may reconcile inconsistencies in season-of-birth associations. Further studies are warranted.

Why we need to pursue both universal and targeted prevention to reduce the incidence of affective and psychotic disorders: Systematic review and meta-analysis.

The effectiveness of universal preventive approaches in reducing the incidence of affective/psychotic disorders is unclear. We therefore aimed to synthesise the available evidence from randomised controlled trials. For studies reporting change in prevalence, we simulated all possible scenarios for the proportion of individuals with the disorder at baseline and at follow-up to exclude them. We then combined these data with studies directly measuring incidence and conducted random effects meta-analysis with relative risk (RR) to estimate the incidence in the intervention group compared to the control group. Eighteen studies (k=21 samples) were included investigating the universal prevention of depression in 66,625 individuals. No studies were available investigating universal prevention on the incidence of bipolar/psychotic disorders. 63 % of simulated scenarios showed a significant preventive effect on reducing the incidence of depression (k=9 - 19, RR=0.75-0.94, 95 %CIs=0.55-0.87,0.93-1.15, p=0.007-0.246) but did not survive sensitivity analyses. There is some limited evidence for the effectiveness of universal interventions for reducing the incidence of depression but not for bipolar/psychotic disorders.

The characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders.

BACKGROUND: Recent studies have indicated that clinical high risk for psychosis (CHR-P) is highly specific for psychotic disorders other than pluripotential to various serious mental illnesses. However, not all CHR-P develop psychotic disorder only, and psychosis can occur in non-psychotic disorders as well. Our prospective cohort study aims to investigate the characteristics and clinical outcomes of a pluripotent high-risk group with the potential to develop a diverse range of psychiatric disorders. METHODS: The SPRIM study is a prospective naturalistic cohort program that focuses on the early detection of those at risk of developing serious mental illness, including psychosis (CHR-P), bipolar (CHR-B), and depressive disorder (CHR-D), as well as undifferentiated risk participants (UCHR). Our study has a longitudinal design with a baseline assessment and eight follow-up evaluations at 6, 12, 18, 24, 30, 36, 42, and 48 months to determine whether participants have transitioned to psychosis or mood disorders. RESULTS: The SPRIM sample consisted of 90 CHR participants. The total cumulative incidence rate of transition was 53.3% (95% CI 32.5-77.2). CHR-P, CHR-B, CHR-D, and UCHR had cumulative incidence rates of 13.7% (95% CI 3.4-46.4), 52.4% (95% CI 28.1-81.1), 66.7% (95% CI 24.6-98.6) and 54.3% (95% CI 20.5-93.1), respectively. The cumulative incidence of psychosis, bipolar, and depressive disorder among all participants was 3.3% (95% CI 0.8-11.5), 45.7% (95% CI 24.4-73.6), and 11.2% (95% CI 3.1-36.2), respectively. CONCLUSIONS: Our study suggests that the concept of pluripotent high-risk for a diverse range of psychiatric disorders is an integrative approach to examining transdiagnostic interactions between illnesses with a high transition rate and minimizing stigma.

Comorbid physical health burden of serious mental health disorders in 32 European countries.

BACKGROUND: Mental health disorders (MHDs) are associated with physical health disparities, but underlying excess risk and health burden have not yet been comprehensively assessed. OBJECTIVE: To assess the burden of comorbid physical health conditions (PHCs) across serious MHDs in Europe. METHODS: We estimated the relative prevalence risk of PHCs associated with alcohol use disorders (AUD), bipolar disorder (BD), depressive disorders (DD) and schizophrenia (SZ) across working-age populations of 32 European countries in 2019 based on a targeted literature review. Excess physical health burden was modelled using population-attributable fractions and country-level prevalence data. FINDINGS: We screened 10 960 studies, of which 41 were deemed eligible, with a total sample size of over 18 million persons. Relative prevalence of PHCs was reported in 54%, 20%, 15%, 5% and 7% of studies, respectively, for SZ, DD, BD, AUD or mixed. Significant relative risk estimates ranged from 1.44 to 3.66 for BD, from 1.43 to 2.21 for DD, from 0.81 to 1.97 for SZ and 3.31 for AUD. Excess physical health burden ranged between 27% and 67% of the total, corresponding to 84 million (AUD), 67 million (BD), 66 million (DD) and 5 million (SZ) PHC diagnoses in Europe. A 1% reduction in excess risk assuming causal inference could result in two million fewer PHCs across investigated MHDs. CONCLUSIONS: This is the first comprehensive study of the physical health burden of serious MHDs in Europe. The methods allow for updates, refinement and extension to other MHDs or geographical areas. CLINICAL IMPLICATIONS: The results indicate potential population health benefits achievable through more integrated mental and physical healthcare and prevention approaches.

Cancer diagnosis after emergency presentations in people with mental health and substance use conditions: a national cohort study.

BACKGROUND: Cancer survival and mortality outcomes for people with mental health and substance use conditions (MHSUC) are worse than for people without MHSUC, which may be partly explained by poorer access to timely and appropriate healthcare, from screening and diagnosis through to treatment and follow-up. Access and quality of healthcare can be evaluated by comparing the proportion of people who receive a cancer diagnosis following an acute or emergency hospital admission (emergency presentation) across different population groups: those diagnosed with cancer following an emergency presentation have lower survival. METHODS: National mental health service use datasets (2002-2018) were linked to national cancer registry and hospitalisation data (2006-2018), to create a study population of people aged 15 years and older with one of four cancer diagnoses: lung, prostate, breast and colorectal. The exposure group included people with a history of mental health/addiction service contact within the five years before cancer diagnosis, with a subgroup of people with a diagnosis of bipolar disorder, schizophrenia or psychotic disorders. Marginal standardised rates were used to compare emergency presentations (hospital admission within 30 days of cancer diagnosis) in the exposure and comparison groups, adjusted for age, gender (for lung and colorectal cancers), ethnicity, area deprivation and stage at diagnosis. RESULTS: For all four cancers, the rates of emergency presentation in the fully adjusted models were significantly higher in people with a history of mental health/addiction service use than people without (lung cancer, RR 1.19, 95% CI 1.13, 1.24; prostate cancer RR 1.69, 95% CI 1.44, 1.93; breast cancer RR 1.42, 95% CI 1.14, 1.69; colorectal cancer 1.31, 95% CI 1.22, 1.39). Rates were substantially higher in those with a diagnosis of schizophrenia, bipolar disorder or psychotic disorders. CONCLUSIONS: Implementing pathways for earlier detection and diagnosis of cancers in people with MHSUC could reduce the rates of emergency presentation, with improved cancer survival outcomes. All health services, including cancer screening programmes, primary and secondary care, have a responsibility to ensure equitable access to healthcare for people with MHSUC.

[Prevalence and factors associated with benzodiazepine use in children and adult inpatients]. / Prevalentie van en factoren geassocieerd met benzodiazepinegebruik tijdens opname.

BACKGROUND: Given the growing focus on deprescribing, it is crucial to thoroughly evaluate our benzodiazepine prescribing practices considering the potential risks. AIM: To investigate the prevalence and predictors of benzodiazepine prescriptions during psychiatric hospitalization and as discharge medication. METHOD: This retrospective electronic patient file study included psychiatric admissions at the UMC Utrecht between 12/01/01 and 21/04/01. Descriptive statistics were used to evaluate prevalence of benzodiazepine prescriptions in youth and adults. Multivariate regression analyses were performed to predict factors associated with benzodiazepine prescriptions and dosage. RESULTS: In total, we analyzed data from 856 admissions of youth and 4002 admissions of adults. 36.0% of the youth were prescribed benzodiazepines during admission and 14.8% at discharge. Associated factors were age (OR: 1.38) and bipolar disorder (OR: 3.98). In adults, 69.7% were prescribed benzodiazepines during admission and 37.6% at discharge. Associated factors were length of hospital stay (OR: 1.01) and anxiety disorders (OR: 2.53). Male sex, age (resp. higher and lower), and a longer length of stay predicted benzodiazepine dosages for both youth (B = 3.48; 95% CI: 0.83-0.07) and adults (B = 2.17; 95% CI: -0.04-0.05). CONCLUSION: Benzodiazepines are frequently prescribed during inpatient stays and at discharge in youth and adults, offering opportunities for deprescribing.

Genetic correlation and causal associations between psychiatric disorders and lung cancer risk.

BACKGROUND: Patients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges. METHODS: Available summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR). RESULTS: Significant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking. LIMITATIONS: Participants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased. CONCLUSION: Our findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.

Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis.

BACKGROUND: People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness. METHODS: We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables. FINDINGS: From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21). INTERPRETATION: This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care. FUNDING: None.

The anxiety response of patients with severe psychiatric disorders to the recent public health crisis.

BACKGROUND: The devastating health, economic, and social consequences of COVID-19 may harm the already vulnerable groups, particularly people with severe psychiatric disorders (SPDs). The present study was conducted to investigate the anxiety response of patients with SPDs during the COVID-19 pandemic. METHODS: A total of 351 patients with SPDs [Schizophrenia Spectrum (SSD), Bipolar (BD), Major Depressive (MDD), and Obsessive-Compulsive (OCD) Disorders] and healthy controls in Guilan province, Iran, throughout 2021-2022 were included in this cross-sectional analytical study. The anxiety response consisted of four concepts: COVID-19-related anxiety, general health anxiety, anxiety sensitivity, and safety behaviors. We conducted an unstructured interview and provided sociodemographic and clinical information. Also, the participants were asked to complete four self-report measures of the Corona Disease Anxiety Scale, the Anxiety Sensitivity Index-Revised, the Short Health Anxiety Inventory, and the Checklist of Safety Behaviors. RESULTS: Analysis of variance showed a significant difference between the groups of patients with SPDs and the control group in COVID-19-related anxiety (F = 6.92, p = 0.0001), health anxiety (F = 6.21, p = 0.0001), and safety behaviors (F = 2.52, p = 0.41). No significant difference was observed between them in anxiety sensitivity (F = 1.77, p = 0.134). The Games-Howell test showed that the control group obtained a higher mean than the groups of people with BD (p < 0.0001), SSD (p = 0.033), and OCD (p = 0.003) disorders in COVID-19-related anxiety. The patients with MDD (p = 0.014) and OCD (p = 0.01) had a higher mean score than the control group in health anxiety. Tukey's test showed that the mean of safety behaviors of the control group was significantly higher than the OCD group (p = 0.21). No significant difference was found between the groups of patients with MDD, BD, SSD, and OCD in terms of COVID-19-related anxiety, health anxiety, and safety behaviors. CONCLUSION: Anxiety response to health crisis is different in groups with SPDs and control group. The findings of this study suggest that although health anxiety is present in many of these patients during the pandemic, their anxiety response to the health crisis may be less than expected. There can be various explanations, such as pre-existing symptoms, low health literacy, and possible co-occurring cognitive impairment. The results of this study have many practical and policy implications in meeting the treatment needs of this group of patients during public health crises and indicate that their needs may not be compatible with the expectations and estimates that health professionals and policymakers already have.

Developing a prediction model to identify people with severe mental illness without regular contact to their GP - a study based on data from the Danish national registers.

INTRODUCTION: People with severe mental illness (SMI) face a higher risk of premature mortality due to physical morbidity compared to the general population. Establishing regular contact with a general practitioner (GP) can mitigate this risk, yet barriers to healthcare access persist. Population initiatives to overcome these barriers require efficient identification of those persons in need. OBJECTIVE: To develop a predictive model to identify persons with SMI not attending a GP regularly. METHOD: For individuals with psychotic disorder, bipolar disorder, or severe depression between 2011 and 2016 (n = 48,804), GP contacts from 2016 to 2018 were retrieved. Two logistic regression models using demographic and clinical data from Danish national registers predicted severe mental illness without GP contact. Model 1 retained significant main effect variables, while Model 2 included significant bivariate interactions. Goodness-of-fit and discriminating ability were evaluated using Hosmer-Lemeshow (HL) test and area under the receiver operating characteristic curve (AUC), respectively, via cross-validation. RESULTS: The simple model retained 11 main effects, while the expanded model included 13 main effects and 10 bivariate interactions after backward elimination. HL tests were non-significant for both models (p = 0.50 for the simple model and p = 0.68 for the extended model). Their respective AUC values were 0.789 and 0.790. CONCLUSION: Leveraging Danish national register data, we developed two predictive models to identify SMI individuals without GP contact. The extended model had slightly better model performance than the simple model. Our study may help to identify persons with SMI not engaging with primary care which could enhance health and treatment outcomes in this group.

Bipolar symptoms, somatic burden and functioning in older-age bipolar disorder: A replication study from the global aging & geriatric experiments in bipolar disorder database (GAGE-BD) project.

OBJECTIVES: The Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD) project pools archival datasets on older age bipolar disorder (OABD). An initial Wave 1 (W1; n = 1369) analysis found both manic and depressive symptoms reduced among older patients. To replicate this finding, we gathered an independent Wave 2 (W2; n = 1232, mean ± standard deviation age 47.2 ± 13.5, 65% women, 49% aged over 50) dataset. DESIGN/METHODS: Using mixed models with random effects for cohort, we examined associations between BD symptoms, somatic burden and age and the contribution of these to functioning in W2 and the combined W1 + W2 sample (n = 2601). RESULTS: Compared to W1, the W2 sample was younger (p < 0.001), less educated (p < 0.001), more symptomatic (p < 0.001), lower functioning (p < 0.001) and had fewer somatic conditions (p < 0.001). In the full W2, older individuals had reduced manic symptom severity, but age was not associated with depression severity. Age was not associated with functioning in W2. More severe BD symptoms (mania p ≤ 0.001, depression p ≤ 0.001) were associated with worse functioning. Older age was significantly associated with higher somatic burden in the W2 and the W1 + W2 samples, but this burden was not associated with poorer functioning. CONCLUSIONS: In a large, independent sample, older age was associated with less severe mania and more somatic burden (consistent with previous findings), but there was no association of depression with age (different from previous findings). Similar to previous findings, worse BD symptom severity was associated with worse functioning, emphasizing the need for symptom relief in OABD to promote better functioning.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment.

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

Ketogenic Diet Intervention on Metabolic and Psychiatric Health in Bipolar and Schizophrenia: A Pilot Trial.

The ketogenic diet (KD, also known as metabolic therapy) has been successful in the treatment of obesity, type 2 diabetes, and epilepsy. More recently, this treatment has shown promise in the treatment of psychiatric illness. We conducted a 4-month pilot study to investigate the effects of a KD on individuals with schizophrenia or bipolar disorder with existing metabolic abnormalities. Twenty-three participants were enrolled in a single-arm trial. Results showcased improvements in metabolic health, with no participants meeting metabolic syndrome criteria by study conclusion. Adherent individuals experienced significant reduction in weight (12 %), BMI (12 %), waist circumference (13 %), and visceral adipose tissue (36 %). Observed biomarker enhancements in this population include a 27 % decrease in HOMA-IR, and a 25 % drop in triglyceride levels. In psychiatric measurements, participants with schizophrenia showed a 32 % reduction in Brief Psychiatric Rating Scale scores. Overall Clinical Global Impression (CGI) severity improved by an average of 31 %, and the proportion of participants that started with elevated symptomatology improved at least 1-point on CGI (79 %). Psychiatric outcomes across the cohort encompassed increased life satisfaction (17 %) and enhanced sleep quality (19 %). This pilot trial underscores the potential advantages of adjunctive ketogenic dietary treatment in individuals grappling with serious mental illness.

Suspected geriatric onset of attention-deficit/hyperactivity disorder in a patient with comorbid bipolar disorder.

BACKGROUND: An increasing number of adults over 60 years old are presenting with requests for treatment of attention-deficit/hyperactivity disorder (ADHD). However, the prevalence of ADHD in older adults in geriatrics is unknown. Further, comorbid bipolar disorder and adult ADHD are likely underrecognized with many patients only receiving treatment for one of these conditions. The occurrence of bipolar disorder with geriatric onset ADHD is unknown. CASE PRESENTATION: A 64-year-old Hispanic woman with a psychiatric history of bipolar I disorder (diagnosed in early adulthood) was diagnosed with ADHD suspected of geriatric onset, and able to be successfully managed on concurrent mood stabilizers and psychostimulant medication. CONCLUSIONS: The findings of this case report emphasize the importance of appropriately recognizing and treating comorbid ADHD and bipolar disorder in any age group, including the geriatric population for which this occurrence appears to be very rare. Additionally, this case report demonstrates the safe utilization of psychostimulant medications in a geriatric patient with bipolar disorder without inducing a manic episode or other significant adverse reactions.

Managing the Dual Diagnosis Dilemma of Bipolar Disorder and Substance Abuse in Clinical Settings.

OBJECTIVE: Drug addiction is a chronic mental disorder that significantly impacts all aspects of an individual's life, and substance use disorder in patients with bipolar disorder. The objective of this study is to assess the frequency of substance abuse among patients with bipolar spectrum disorder. METHOD: This cross-sectional study evaluated the frequency of bipolar spectrum disorder in patients taking methadone through various screening measures, including Mini Mental State Examination (MMSE), DSM IV criteria, Mood Disorders Questionnaire (MDQ), Goodwin and Ghaemi's criteria, and Akiskal classification for bipolar disorders. RESULTS: Out of the total 197 participants in the study, 77 were identified as individuals engaging in poly-substance abuse. The investigation assessed the frequency of bipolar spectrum disorder based on various diagnostic criteria: 24% according to DSM-IV criteria, 29.9% using MDQ, 29.9% based on Ghaemi and Goodwin's criteria, and the highest rate at 48.2% when applying Akiskal's classification. CONCLUSIONS: This study highlights the high frequency of bipolar disorder among individuals with substance use disorder, especially those with concomitant depression. Therefore, it is crucial to pay special attention to individuals with substance use disorder with co-existing bipolar disorder.

Prevalence and risk factors for metabolic syndrome in schizophrenia, schizoaffective, and bipolar disorder.

BACKGROUND: Metabolic Syndrome (MetS) is a risk for developing cardiovascular diseases and its prevalence is especially high in psychiatric patients. To date, there is limited data from the United Arab Emirates (UAE) on the prevalence of MetS. Therefore, we aimed to investigate its prevalence and possible risk factors in a large sample of psychiatric patients in the UAE. METHODS: A cross-sectional study was conducted at Al-Ain Hospital, in Al-Ain City, UAE. We collected demographic and clinical data on patients diagnosed with schizophrenia, schizoaffective, and bipolar affective disorder in the period between January 2017 and December 2020. This included their secondary diagnosis (psychiatric or medical), vital signs (heart rate, systolic and diastolic blood pressure, Body Mass Index [BMI]), metabolic parameters (fasting blood glucose, cholesterol, triglycerides, low-density lipoprotein, high-density lipoproteins), and prescribed medications. We used the American Association of Clinical Endocrinology (AACE) criteria to diagnose MetS. RESULTS: We included 889 subjects and of these, 79.8% (N = 709) had a BMI ≥25 kg/m2 and 9.8% (N = 87) had no abnormal metabolic parameters. Overall, 28.1% (N = 250) had MetS with no statistical difference between the three groups. Fasting blood glucose levels and abnormally elevated triglycerides were significant predictors for MetS. CONCLUSION: Our study found that around one in three patients had MetS irrespective of the three diagnoses. Some variables were significant predictors for MetS. Our findings were consistent with other studies and warrant the need for regular screening and management of abnormal metabolic parameters.

There is no statistical difference between schizophrenia, schizoaffective disorder, and bipolar disorder with regards to the prevalence of metabolic syndrome.Fasting blood glucose levels and abnormally elevated triglycerides were significant predictors of metabolic syndrome.Screening of metabolic parameters is important as well as the careful tailoring of the choice of antipsychotics.

The prevalence and clinical correlates of suicide attempts in patients with bipolar disorder misdiagnosed with major depressive disorder: Results from a national survey in China.

BACKGROUND AND AIM: Suicide is nearly always associated with underlying mental disorders. Risk factors for suicide attempts (SAs) in patients with bipolar disorder (BD) misdiagnosed with major depressive disorder (MDD) remain unelucidated. This study was to evaluate the prevalence and clinical risk factors of SAs in Chinese patients with BD misdiagnosed with MDD. METHODS: A total of 1487 patients with MDD from 13 mental health institutions in China were enrolled. Mini International Neuropsychiatric Interview (MINI) was used to identify patients with BD who are misdiagnosed as MDD. The general sociodemographic and clinical data of the patients were collected and MINI suicide module was used to identify patients with SAs in these misdiagnosed patients. RESULTS: In China, 20.6% of patients with BD were incorrectly diagnosed as having MDD. Among these misdiagnosed patients, 26.5% had attempted suicide. These patients tended to be older, had a higher number of hospitalizations, and were more likely to experience frequent and seasonal depressive episodes with atypical features, psychotic symptoms, and suicidal thoughts. Frequent depressive episodes and suicidal thoughts during depression were identified as independent risk factors for SAs. Additionally, significant sociodemographic and clinical differences were found between individuals misdiagnosed with MDD in BD and patients with MDD who have attempted suicide. CONCLUSIONS: This study highlights the importance of accurate diagnosis in individuals with BD and provide valuable insights for the targeted identification and intervention of individuals with BD misdiagnosed as having MDD and those with genuine MDD, particularly in relation to suicidal behavior.