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Introduction: The manifestation of bipolar disorder (BD) is hypothesized to be determined by clinical characteristics such as familial loading, childhood abuse, age at onset, illness duration, comorbid psychiatric disorders, addiction, treatment resistance, and premorbid cognitive functioning. Which of these are associated with a more severe course and worse outcome is currently unknown. Our objective is to find a combination of clinical characteristics associated with advancement to subsequent stages in two clinical staging models for BD. Methods: Using cross‐sectional data from the Dutch Bipolar Cohort, staging was applied to determine the progression of bipolar‐I‐disorder (BD‐I; N = 1396). Model A is primarily defined by recurrence of mood episodes, ranging from prodromal to chronicity. Model B is defined by level of inter‐episodic functioning, ranging from prodromal to inability to function autonomously. For both models, ordinal logistic regression was conducted to test which clinical characteristics are associated with subsequent stages. Results: For model A, familial loading, childhood abuse, earlier onset, longer illness duration, psychiatric comorbidity, and treatment resistance were all predictors for a higher stage in contrast to addiction and cognitive functioning. For model B, childhood abuse, psychiatric comorbidity, cognitive functioning, and treatment resistance were predictors for a more severe stage, whereas age at onset, illness duration, and addiction were not. Discussion/conclusions: Differences in clinical characteristics across stages support the construct validity of both staging models. Characteristics associated with a higher stage largely overlapped across both models. This study is a first step toward determining different clinical profiles, with a corresponding course and outcome. [ABSTRACT FROM AUTHOR]

Objective: To assess the clinical utility of two staging models for bipolar disorder by examining distribution, correlation, and the relationship to external criteria. These are primarily defined by the recurrence of mood episodes (model A), or by intra‐episodic functioning (model B). Methods: In the Dutch Bipolar Cohort, stages according to models A and B were assigned to all patients with bipolar‐I‐disorder (BD‐I; N = 1396). The dispersion of subjects over the stages was assessed and the association between the two models calculated. For both models, change in several clinical markers were concordant with the stage was investigated. Results: Staging was possible in 87% of subjects for model A and 75% for model B. For model A, 1079 participants (93%) were assigned to stage 3c (recurrent episodes). Subdividing stage 3c with cut‐offs at 5 and 10 episodes resulted in subgroups containing 242, 510, and 327 subjects. For model B, most participants were assigned to stage II (intra‐episodic symptoms, N = 431 (41%)) or stage III (inability to work, N = 451 (43%)). A low association between models was found. For both models, the clinical markers "age at onset," "treatment resistance," and "episode acceleration" changed concordant with the stages. Conclusion: The majority of patients with BD‐I clustered in recurrent stage 3 of Model A. Model B showed a larger dispersion. The stepwise change in several clinical markers supports the construct validity of both models. Combining the two staging models and sub‐differentiating the recurrent stage into categories with cut‐offs at 5 and 10 lifetime episodes improves the clinical utility of staging for individual patients. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) has been related to both a dysfunctional γ-amino butyric acid (GABA) system and to hyperactivity of the hypothalamic-pituitary-adrenal axis (HPA). Although GABA has been suggested to inhibit HPA axis activity, their relationship has never been studied at the level of the central GABAA-benzodiazepine receptor in depressed patients or in relation to antidepressant treatment. Eleven depressed outpatients were compared, before and after treatment with citalopram, with nine age-matched healthy controls. The subjects were scanned using the positron emission tomography (PET) tracer [11C]flumazenil ([11C]FMZ). Parametric voxel-by-voxel Logan plots were compared with methods based on regions of interest (ROI), to provide volume of distribution (VT) and binding potential (BPND) values. Plasma GABA levels were determined and a dexamethasone-corticotropin releasing hormone (DEX-CRH) test was performed. In MDD, parametric voxel-by-voxel Logan plots showed bilateral reduced [11C]FMZ binding in the parahippocampal gyrus and right lateral superior temporal gyrus ( p uncorrected ≤0.001). In the temporal area, [11C]FMZ binding showed a strong inverse correlation with HPA axis activity. Plasma GABA did not discriminate MDD from controls, but correlated inversely with [11C]FMZ binding in the right insula. Following treatment with citalopram, voxel-based analysis revealed reduced binding in the right lateral temporal gyrus and dorsolateral prefrontal cortex. The bilateral reduction in limbic parahippocampal and right temporal [11C]FMZ binding found in MDD indicates decreased GABAA-benzodiazepine receptor complex affinity and/or number. The inverse relationship between GABAA binding in the temporal lobe and HPA axis activity, suggests that HPA axis hyperactivity is partly due to reduced GABA-ergic inhibition. [ABSTRACT FROM AUTHOR]

A single-tissue compartment model with plasma input is the established method for analysing [11C]flumazenil ([11C]FMZ) studies. However, arterial cannulation and measurement of metabolites are time-consuming. Therefore, a reference tissue approach is appealing, but this approach has not been fully validated for [11C]FMZ. Dynamic [11C]FMZ positron emission tomography scans with arterial blood sampling were performed in nine drug-free depressive patients and eight healthy subjects. Regions of interest were defined on co-registered magnetic resonance imaging scans and projected onto dynamic [11C]FMZ images. Using a Hill-type metabolite function, single (1T) and reversible two-tissue (2T) compartmental models were compared. Simplified reference tissue model (SRTM) and full reference tissue model (FRTM) were investigated using both pons and (centrum semiovale) white matter as reference tissue. The 2T model provided the best fit in 59% of cases. Two-tissue VT values were on average 1.6% higher than 1T VT values. Owing to the higher rejection rate of 2T fits (7.3%), the 1T model was selected as plasma input method of choice. SRTM was superior to FRTM, irrespective whether pons or white matter was used as reference tissue. BPND values obtained with SRTM correlated strongly with 1T VT (r=0.998 and 0.995 for pons and white matter, respectively). Use of white matter as reference tissue resulted in 5.5% rejected fits, primarily in areas with intermediate receptor density. No fits were rejected using pons as reference tissue. Pons produced 23% higher BPND values than white matter. In conclusion, for most clinical studies, SRTM with pons as reference tissue can be used for quantifying [11C]FMZ binding.Journal of Cerebral Blood Flow & Metabolism (2008) 28, 579–587; doi:10.1038/sj.jcbfm.9600554; published online 10 October 2007 [ABSTRACT FROM AUTHOR]

Objective: Sex-specific research in adult bipolar disorder (BD) is sparse and even more so among those with older age bipolar disorder (OABD). Knowledge about sex differences across the bipolar lifespan is urgently needed to target and improve treatment. To address this gap, the current study examined sex differences in the domains of clinical presentation, general functioning, and mood symptoms among individuals with OABD., Methods: This Global Aging & Geriatric Experiments in Bipolar Disorder (GAGE-BD) study used data from 19 international studies including BD patients aged ≥50 years (N = 1,185: 645 women, 540 men).A comparison of mood symptoms between women and men was conducted initially using two-tailed t tests and then accounting for systematic differences between the contributing cohorts by performing generalized linear mixed models (GLMMs). Associations between sex and other clinical characteristics were examined using GLMM including: age, BD subtype, rapid cycling, psychiatric hospitalization, lifetime psychiatric comorbidity, and physical health comorbidity, with study cohort as a random intercept., Results: Regarding depressive mood symptoms, women had higher scores on anxiety and hypochondriasis items. Female sex was associated with more psychiatric hospitalizations and male sex with lifetime substance abuse disorders., Conclusion: Our findings show important clinical sex differences and provide support that older age women experience a more severe course of BD, with higher rates of psychiatric hospitalization. The reasons for this may be biological, psychological, or social. These differences as well as underlying mechanisms should be a focus for healthcare professionals and need to be studied further., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Perfectionism is common amongst medical doctors and, further, it is becoming more frequently seen in young people. Factors associated with this include the rise of social media and the increasing focus on social performance. Whilst perfectionism can be associated with positive characteristics such as accuracy and perseverance, it may also have a dark side: it is associated with significant mental and physical health problems. In this context, developing greater insight into one's perfectionism and means to address it would be of benefit to doctors. Perfectionism can be divided into three forms - perfectionistic concerns (PC), perfectionistic strivings (PS), perfectionism oriented at others (PO) - each of which has a different relationship to health problems and can reinforce each other. High PC are associated with many health complaints. The relationship between PS and health complaints is possibly U-shaped: both too little and too much PS are associated with many health complaints. Doctors could benefit from more balance in their perfectionism and this could be achieved by understanding their own perfectionism as well as daring to show vulnerability and leniency towards themselves and those around them.

Objective: To assess the clinical utility of two staging models for bipolar disorder by examining distribution, correlation, and the relationship to external criteria. These are primarily defined by the recurrence of mood episodes (model A), or by intra-episodic functioning (model B)., Methods: In the Dutch Bipolar Cohort, stages according to models A and B were assigned to all patients with bipolar-I-disorder (BD-I; N = 1396). The dispersion of subjects over the stages was assessed and the association between the two models calculated. For both models, change in several clinical markers were concordant with the stage was investigated., Results: Staging was possible in 87% of subjects for model A and 75% for model B. For model A, 1079 participants (93%) were assigned to stage 3c (recurrent episodes). Subdividing stage 3c with cut-offs at 5 and 10 episodes resulted in subgroups containing 242, 510, and 327 subjects. For model B, most participants were assigned to stage II (intra-episodic symptoms, N = 431 (41%)) or stage III (inability to work, N = 451 (43%)). A low association between models was found. For both models, the clinical markers "age at onset," "treatment resistance," and "episode acceleration" changed concordant with the stages., Conclusion: The majority of patients with BD-I clustered in recurrent stage 3 of Model A. Model B showed a larger dispersion. The stepwise change in several clinical markers supports the construct validity of both models. Combining the two staging models and sub-differentiating the recurrent stage into categories with cut-offs at 5 and 10 lifetime episodes improves the clinical utility of staging for individual patients., (© 2019 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd.)

Objective: In patients with bipolar disorder, olanzapine is commonly used to prevent episodes of acute mania. The drug pramipexole can, in theory, undermine the protective effect of olanzapine. Olanzapine is a dopamine D2 receptor antagonist and pramipexole is a mixed dopamine D2 /D3 receptor agonist. These drugs may therefore theoretically counteract their pharmacological effects. To date, there are no known cases in the literature where this interaction has been described., Methods: We report on a case where a patient with bipolar disorder developed mania after taking pramipexole in combination with olanzapine, and describe the pharmacological background of this interaction., Results: A patient with bipolar I disorder was hospitalized with a manic episode characterized by agitation and insomnia after taking pramipexole for restless leg syndrome (RLS) in combination with olanzapine. Co-medication, i.e., lithium and mirtazapine, and other circumstances are not likely to have contributed to this effect., Conclusion: There is a probable interaction between pramipexole and olanzapine, where pramipexole undermines the protective effect of olanzapine, provoking an episode of acute mania and hospitalization. This interaction is of clinical importance since pramipexole is the treatment of choice for RLS, a condition often seen in end-stage renal disease, and has also been investigated as an antidepressant therapy in patients with bipolar disorder., (© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: This [11C]flumazenil (FMZ) study evaluates the performance of various parametric analysis methods and their ability to detect statistically significant group differences., Methods: Dynamic 60-min FMZ scans were performed in eight healthy and nine individuals with major depressive disorder. Parametric volume of distribution (VT) images were generated using a basis function method (BFM) implementation of the single tissue compartment model (1T) and Logan plot analysis, both with a metabolite-corrected arterial plasma input function. Parametric binding potential (BP ND) images were generated using multilinear reference tissue methods (MRTM0-4), reference Logan and receptor parametric mapping (RPM1-2), with pons as a reference region. Standardized uptake value (SUV) and SUV ratio-to-pons (SUVr) images were calculated over the time interval 30-40 and 20-60 min postinjection. The resulting VT, BP ND, SUV and SUVr values were compared with nonlinear regression values, using both the 1T model and the simplified reference tissue model. Statistical parametric mapping (SPM5) was used to detect group differences, with an emphasis on the bilateral parahippocampal gyri., Results: BFM was more accurate than Logan, but showed more variability. Both RPM methods and MRTM2 showed the best average correlation with the simplified reference tissue model. In using SPM, SUV and SUVr images provided the best contrast between groups in the parahippocampal gyri, but provided large underestimation and overestimation in quantitative comparisons. BFM and RPM methods allowed for the determination of perfusion effects., Conclusion: Parametric Logan VT, MRTM2 and RPM1-2 BP ND methods allow the best quantitative comparison of FMZ binding between groups and show good discriminating performance in SPM analysis.

Extraction of arterial input functions from dynamic brain scans may obviate the need for arterial sampling and would increase the clinical applicability of quantitative PET studies. The aim of the present study was to evaluate applicability and accuracy of image derived input functions (IDIFs) following reconstruction based partial volume correction (PVC). Settings for the PVC ordered subset expectation maximization (PVC-OSEM) reconstruction algorithm were varied. In addition, different methods for defining arterial regions of interest (ROI) in order to extract IDIFs were evaluated. [(11)C]flumazenil data of 10 subjects were used in the present study. Results obtained with IDIFs were compared with those using standard on-line measured arterial input functions. These included areas under the curve (AUC) for peak (1-2 min) and tail (2-60 min), volume of distribution (V(T)) obtained using Logan analysis, and V(T) and K(1) obtained with a basis function implementation of a single tissue compartment model. Best results were obtained with PVC-OSEM using 4 iterations and 16 subsets. Based on (11)C point source measurements, a 4.5 mm FWHM (full width at half maximum) resolution kernel was used to correct for partial volume effects. A ROI consisting of the four hottest pixels per plane (over the carotid arteries) was the best method to extract IDIFs. Excellent peak AUC ratios (0.99+/-0.09) between IDIF and blood sampler input function (BSIF) were found. Furthermore, extracted IDIFs provided V(T) and K(1) values that were very similar to those obtained using BSIFs. The proposed method appears to be suitable for analysing [(11)C]flumazenil data without the need for online arterial sampling.