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Journal of Psychiatric Research Jun 2022Sleep disturbances are a key feature of bipolar disorder (BD), and poor sleep has been linked to mood symptoms. Recent use of ecological momentary assessment (EMA) has...
Sleep disturbances are a key feature of bipolar disorder (BD), and poor sleep has been linked to mood symptoms. Recent use of ecological momentary assessment (EMA) has allowed for nuanced exploration of the sleep-mood link; though, the scale and directionality of this relationship is still unclear. Using EMA, actigraphy, and self-reported sleep measures, this study examines the concurrent and predictive relationships between sleep and mood. Participants with BD (n = 56) wore actigraphy devices for up to 14 days and completed validated scales and daily EMA surveys about mood and sleep quality. Linear mixed models were used to examine overall and time-lagged relationships between sleep and mood variables. EMA mood ratings were correlated with validated rating scales for depression, mania, anxiety, and impulsivity. Poor self-reported sleep quality was associated with worse overall ratings of sadness and anger. Worse self-reported sleep quality was associated with greater sadness the following day. Higher daytime impulsivity was associated with worse sleep quality the following night. Exploratory analyses found relationships between worse and more variable mood (sadness, anger, and impulsivity) with worse and more variable sleep that evening (efficiency, WASO, and sleep onset time). The sample size was modest, fairly homogenous, and included mainly euthymic persons with BD. EMA-based assessments of mood and sleep are correlated with validated scale scores and provide novel insight into intra-individual variability. Further work on the complex two-way interactions between sleep and mood is needed to better understand how to improve outcomes in BD.
Topics: Actigraphy; Affect; Bipolar Disorder; Ecological Momentary Assessment; Humans; Sleep; Sleep Initiation and Maintenance Disorders
PubMed: 35405410
DOI: 10.1016/j.jpsychires.2022.03.055 -
Bipolar Disorders Dec 2021Bipolar disorder (BP) is commonly researched in digital settings. As a result, standardized digital tools are needed to measure mood. We sought to validate a new survey...
OBJECTIVES
Bipolar disorder (BP) is commonly researched in digital settings. As a result, standardized digital tools are needed to measure mood. We sought to validate a new survey that is brief, validated in digital form, and able to separately measure manic and depressive severity.
METHODS
We introduce a 6-item digital survey, called digiBP, for measuring mood in BP. It has three depressive items (depressed mood, fidgeting, fatigue), two manic items (increased energy, rapid speech), and one mixed item (irritability); and recovers two scores (m and d) to measure manic and depressive severity. In a secondary analysis of individuals with BP who monitored their symptoms over 6 weeks (n = 43), we perform a series of analyses to validate the digiBP survey internally, externally, and as a longitudinal measure.
RESULTS
We first verify a conceptual model for the survey in which items load onto two factors ("manic" and "depressive"). We then show weekly averages of m and d scores from digiBP can explain significant variation in weekly scores from the Young Mania Rating Scale (R = 0.47) and SIGH-D (R = 0.58). Lastly, we examine the utility of the survey as a longitudinal measure by predicting an individual's future m and d scores from their past m and d scores.
CONCLUSIONS
While further validation is warranted in larger, diverse populations, these validation analyses should encourage researchers to consider digiBP for their next digital study of BP.
Topics: Affect; Bipolar Disorder; Humans; Irritable Mood; Psychiatric Status Rating Scales; Self Report; Surveys and Questionnaires
PubMed: 33587813
DOI: 10.1111/bdi.13058 -
Translational Psychiatry Apr 2022Manic episodes are a defining, frequent and dramatically disabling occurrence in the course of Bipolar Disorder type I. Current pharmacotherapy of mania lists a good... (Review)
Review
Manic episodes are a defining, frequent and dramatically disabling occurrence in the course of Bipolar Disorder type I. Current pharmacotherapy of mania lists a good number of agents, but differences in efficacy and safety profiles among these agents must be considered in order to tailor personalized therapies, especially when the long-term course of the illness is considered. There is wide room and need to ameliorate current pharmacological approaches to mania, but ongoing pharmacological research on the topic is scant. In this work we try to critically assess clinical factors and patients' characteristics that may influence the treatment choice for manic episodes. In addition, we conduct a narrative review on experimental pharmacology of bipolar mania and psychotic disorders, presenting a critical overview on agents which could represent treatment alternatives for a manic episode in the next future. Results show limited novel or ongoing research on agents acting as mood stabilizers (Ebselen, Valnoctamide and Eslicarbazepine did not reach statistical significance in demonstrating antimanic efficacy). As for the emerging experimental antipsychotic, some of them (including KarXT, SEP-363856, RO6889450, ALKS3831) have demonstrated good antipsychotic efficacy and a favorable safety profile, but little is known about their use in patients with bipolar disorder and specifically designed trials are needed. Lastly, some benefits for the treatment of mania could be expected to come in the next future from non-mood stabilizers/non-antipsychotic agents (especially PKC inhibitors like Endoxifen): long-term trials are needed to confirm positive results in terms of long-term efficacy and safety.
Topics: Anticonvulsants; Antimanic Agents; Antipsychotic Agents; Bipolar Disorder; Humans; Mania; Psychotic Disorders
PubMed: 35461339
DOI: 10.1038/s41398-022-01928-8 -
Translational Psychiatry Feb 2018The hallmark of bipolar disorder is a clinical course of recurrent manic and depressive symptoms of varying severity and duration. Mathematical modeling of bipolar...
The hallmark of bipolar disorder is a clinical course of recurrent manic and depressive symptoms of varying severity and duration. Mathematical modeling of bipolar disorder holds the promise of an ability to personalize diagnoses, to predict future mood episodes, to directly compare diverse datasets, and to link basic mechanisms to behavioral data. Several modeling frameworks have been proposed for bipolar disorder, which represent competing hypothesis about the basic framework of the disorder. Here, we test these hypotheses with self-report assessments of mania and depression symptoms from 178 bipolar patients followed prospectively for 4 or more years. Statistical analysis of the data did not support the hypotheses that mood arises from a rhythmic process or multiple stable states (e.g., mania or depression) or that manic and depressive symptoms are highly anti-correlated. Alternatively, it is shown that bipolar disorder could arise from an inability for mood to quickly return to normal when perturbed. This latter concept is embodied by an affective instability model that can be personalized to the clinical course of any individual with chronic disorders that have an affective component.
Topics: Adult; Affect; Affective Symptoms; Bipolar Disorder; Female; Humans; Longitudinal Studies; Male; Models, Statistical; Young Adult
PubMed: 29391394
DOI: 10.1038/s41398-017-0084-4 -
Psychotherapy and Psychosomatics 2015Affective disturbances involving alterations of mood, anxiety and irritability may be early symptoms of medical illnesses. The aim of this paper was to provide a... (Review)
Review
BACKGROUND
Affective disturbances involving alterations of mood, anxiety and irritability may be early symptoms of medical illnesses. The aim of this paper was to provide a systematic review of the literature with qualitative data synthesis.
METHODS
MEDLINE, PsycINFO, EMBASE, Cochrane, and ISI Web of Science were systematically searched from inception to February 2014. Search terms were 'prodrome/early symptom', combined using the Boolean 'AND' operator with 'anxiety/depression/mania/hypomania/irritability/irritable mood/hostility', combined with the Boolean 'AND' operator with 'medical illness/medical disorder'. PRISMA guidelines were followed.
RESULTS
A total of 21 studies met the inclusion criteria and were analyzed. Depression was found to be the most common affective prodrome of medical disorders and was consistently reported in Cushing's syndrome, hypothyroidism, hyperparathyroidism, pancreatic and lung cancer, myocardial infarction, Wilson's disease, and AIDS. Mania, anxiety and irritability were less frequent.
CONCLUSIONS
Physicians may not pursue medical workup of cases that appear to be psychiatric in nature. They should be alerted that disturbances in mood, anxiety and irritability may antedate the appearance of a medical disorder.
Topics: Affect; Anxiety; Bipolar Disorder; Depression; Disease; Humans; Irritable Mood
PubMed: 25547421
DOI: 10.1159/000367913 -
Journal of Psychiatric Research Sep 2021Many of the existing models of mood in bipolar disorder can largely be divided into two camps, tracking mood as either a discrete or continuous variable. Both groups...
Many of the existing models of mood in bipolar disorder can largely be divided into two camps, tracking mood as either a discrete or continuous variable. Both groups rely upon certain assumptions, with most considering only aggregate scores on clinical instruments. In this study, we propose a novel framework that combines elements from both discrete and continuous mood models, using a machine learning pipeline to detect subtle patterns across individuals. Latent factors are constructed from assessments at the item level, then clustered into groups referred to as microstates. Transitions between microstates are captured via a discrete-time Markov chain, allowing for characterization of mood's dynamic nature. Key findings include a factor mapping heavily onto irritability and aggression, as well as a hierarchical pattern of microstates within depression and mania. Validity of these results is confirmed by reproduction in an unseen data set from a separate subject cohort.
Topics: Affect; Aggression; Bipolar Disorder; Humans; Irritable Mood
PubMed: 34304043
DOI: 10.1016/j.jpsychires.2021.07.021 -
Frontiers in Psychiatry 2020It remains unknown whether volumetric alterations of ventricles are similar or not in pediatric bipolar disorder (PBD) among different mood states. The present study...
It remains unknown whether volumetric alterations of ventricles are similar or not in pediatric bipolar disorder (PBD) among different mood states. The present study aims to estimate ventricular volumetric alteration of PBD patients in manic and euthymic status, as well as the relationship between this alteration and cognitive changes. T1 magnetic resonance images were obtained from 20 manic PBD patients, 21 euthymic PBD patients, and 19 healthy controls (HCs). Ventricular volumes were automatically obtained via FreeSurfer 6.0 software. Ventricular volumes and cognitive indices were compared among the three groups, and the relationship between ventricular volumes and cognitive/clinical indices was analyzed. In contrast to HCs, manic and euthymic PBD patients exhibited decreased cognitive scores of the Stroop color-word test and the digit span subtest. Manic PBD subjects presented enlarged volumes in the bilateral ventricles, third ventricle, and whole ventricles, and euthymic PBD participants displayed increased volumes in the third ventricle, fourth ventricle, and whole ventricles. No significant differences in cognitive performance and ventricular volumes were found between PBD groups. No significant correlation was discovered between ventricular volumes and cognitive/clinical indices in both manic and euthymic PBD patients. No significant differences in cognitive performance and ventricle volume were observed between euthymic and manic PBD groups, which may imply that the alterations are not specific to mood state. It may indicate structural and functional damage of corresponding brain circuits in euthymic PBD patients similar with that of manic PBD, which may provide clues to the diagnosis and treatment of euthymic PBD.
PubMed: 33381058
DOI: 10.3389/fpsyt.2020.593629 -
Trends in Psychiatry and Psychotherapy 2020Irritability has both mood and behavioral manifestations. These frequently co-occur, and it is unclear to what extent they are dissociable domains. We used confirmatory...
INTRODUCTION
Irritability has both mood and behavioral manifestations. These frequently co-occur, and it is unclear to what extent they are dissociable domains. We used confirmatory factor analysis and external validators to investigate the independence of mood and behavioral components of irritability.
METHODS
The sample comprised 246 patients (mean age 45 years; 63% female) from four outpatient programs (depression, anxiety, bipolar, and schizophrenia) at a tertiary hospital. A clinical instrument rated by trained clinicians was specifically designed to capture irritable mood and disruptive behavior dimensionally, as well as current categorical diagnoses i.e., intermittent explosive disorder (IED); oppositional defiant disorder (ODD); and an adaptation to diagnose disruptive mood dysregulation disorder (DMDD) in adults. Confirmatory factor analysis (CFA) was used to test the best fitting irritability models and regression analyses were used to investigate associations with external validators.
RESULTS
Irritable mood and disruptive behavior were both frequent, but diagnoses of disruptive syndromes were rare (IED, 8%; ODD, 2%; DMDD, 2%). A correlated model with two dimensions, and a bifactor model with one general dimension and two specific dimensions (mood and behavior) both had good fit indices. The correlated model had root mean square error of approximation (RMSEA) = 0.077, with 90% confidence interval (90%CI) = 0.071-0.083; comparative fit index (CFI) = 0.99; and Tucker-Lewis index (TLI) = 0.99, while the bifactor model had RMSEA = 0.041; CFI = 0.99; and TLI = 0.99 respectively). In the bifactor model, external validity for differentiation of the mood and behavioral components of irritability was also supported by associations between irritable mood and impairment and clinical measures of depression and mania, which were not associated with disruptive behavior.
CONCLUSIONS
Psychometric and external validity data suggest both overlapping and specific features of the mood vs. disruptive behavior dimensions of irritability.
Topics: Adult; Attention Deficit and Disruptive Behavior Disorders; Diagnosis, Differential; Disruptive, Impulse Control, and Conduct Disorders; Factor Analysis, Statistical; Female; Humans; Irritable Mood; Male; Middle Aged; Mood Disorders; Outpatient Clinics, Hospital; Problem Behavior; Reproducibility of Results; Tertiary Care Centers
PubMed: 33295573
DOI: 10.1590/2237-6089-2019-0078 -
Brain Imaging and Behavior Jun 2018Bipolar disorder is characterized by recurring episodes of depression and mania. Defining differences in brain function during these states is an important goal of...
Bipolar disorder is characterized by recurring episodes of depression and mania. Defining differences in brain function during these states is an important goal of bipolar disorder research. However, few imaging studies have directly compared brain activity between bipolar mood states. Herein, we compare functional magnetic resonance imaging (fMRI) responses during a flashing checkerboard stimulus between bipolar participants across mood states (euthymia, depression, and mania) in order to identify functional differences between these states. 40 participants with bipolar I disorder and 33 healthy controls underwent fMRI during the presentation of the stimulus. A total of 23 euthymic-state, 16 manic-state, 15 depressed-state, and 32 healthy control imaging sessions were analyzed in order to compare functional activation during the stimulus between mood states and with healthy controls. A reduced response was identified in the visual cortex in both the depressed and manic groups compared to euthymic and healthy participants. Functional differences between bipolar mood states were also observed in the cerebellum, thalamus, striatum, and hippocampus. Functional differences between mood states occurred in several brain regions involved in visual and other sensory processing. These differences suggest that altered visual processing may be a feature of mood states in bipolar disorder. The key limitations of this study are modest mood-state group size and the limited temporal resolution of fMRI which prevents the segregation of primary visual activity from regulatory feedback mechanisms.
Topics: Adult; Affect; Bipolar Disorder; Brain; Brain Mapping; Female; Humans; Magnetic Resonance Imaging; Male; Middle Aged; Photic Stimulation; Visual Perception
PubMed: 28674759
DOI: 10.1007/s11682-017-9741-8 -
Australasian Psychiatry : Bulletin of... Feb 2024While a DSM-5 criterion for both hypomania and mania is impaired functioning, the majority of those with a bipolar condition report improved functioning. When offered a...
OBJECTIVE
While a DSM-5 criterion for both hypomania and mania is impaired functioning, the majority of those with a bipolar condition report improved functioning. When offered a mood stabilizer, many express concerns about any impact on their creativity. This piece seeks to address the question and attendant issues.
METHOD
Reference is made to the impact of differing mood stabilizers on cognitive performance and the limited data on any specific impact on creativity, while some personal observations are offered.
RESULTS
There appears to be a distinctive gradient in the cognitive impacts of differing mood stabilizers, with lithium offering the highest risk, carbamazepine and valproate providing a slight risk, and lamotrigine seemingly without cognitive side-effects.
CONCLUSIONS
The question not only invites a nuanced response from the clinician but argues for close observation of any cognitive side-effects when lithium is introduced.
Topics: Humans; Lithium; Antimanic Agents; Bipolar Disorder; Anticonvulsants; Antipsychotic Agents; Mania
PubMed: 37903448
DOI: 10.1177/10398562231211127