Mood Episodes In Bipolar Disorder Research Articles

Prescribed psychostimulants and other pro-cognitive medications in bipolar disorder: A systematic review and meta-analysis of recurrence of manic symptoms.

Clinicians are often hesitant to prescribe psychostimulants in bipolar disorder (BD) due to concerns of inducing (hypo)mania, despite limited published evidence on associations between prescribed psychostimulant use and recurrence of mood episodes in BD. The current systematic review and meta-analysis evaluated the emergence of (hypo)manic symptoms in patients with BD receiving prescribed psychostimulants or other pro-cognitive medications in euthymic or depressive states. A systematic search was performed of MEDLINE, Embase, and PsychINFO from inception to April 5, 2023 and search of Clinicaltrials.gov and Clinicaltrialsregister.eu for unpublished data. References of included studies were hand-searched. Randomized trials and prospective longitudinal studies that evaluated psychostimulants and non-stimulant medications recommended for the treatment of ADHD by the Canadian ADHD practice guidelines were included. The review was reported in line with PRISMA guidelines and was preregistered on PROSPERO (CRD42022358588). After screening 414 unique records, we included 27 studies, of which five reported data that was quantitatively synthesized (n = 1653). The use of psychostimulants in BD was not associated with increased scores on the Young Mania Rating Scale in patients who were in a euthymic or depressed state (SMD IV -0.17; 95% CI, -0.40 to 0.06) compared to placebo. There was a high degree of study-level heterogeneity (I2 = 80%). A qualitative synthesis of studies revealed a limited risk of medication-induced manic symptoms. Our review provides preliminary evidence to suggest psychostimulants and non-stimulant ADHD medications have a limited risk of precipitating (hypo)mania symptoms. More extensive studies evaluating the safety and efficacy of these medications are warranted.

Preventive effect of aripiprazole once-monthly on relapse into mood episodes in bipolar disorder: A multicenter, one-year, retrospective, mirror image study

BackgroundWe conducted a one-year, retrospective, mirror-image study to investigate the clinical effectiveness and safety of aripiprazole once monthly (AOM) in patients with bipolar disorder (BD). We compared pre-treatment conditions with outcomes after 12 months of AOM treatment. MethodsSeventy-five bipolar patients were recruited from 12 hospitals in Korea. We included 75 patients with BD who had received at least three AOM treatments from September 2019 to September 2022 and had accessible electronic medical record (EMRs) for the year before and after the baseline visit. ResultsThe overall number of mood episodes significantly decreased from a mean of 1.5 ± 1.2 episodes pre-AOM to 0.5 ± 1.2 episodes post-AOM. Manic episodes significantly decreased from 0.8 ± 0.8 episodes pre-AOM to 0.2 ± 0.5 episodes post-AOM, and depressive episodes significantly decreased from 0.5 ± 0.8 episodes pre-AOM to 0.2 ± 0.6 episodes post-AOM (p = 0.017). Moreover, the number of psychiatric medications and pills and the proportion of patients treated with complex polypharmacy were significantly decreased post-AOM. LimitationsThe small sample size was insufficient to fully represent the entire population of individuals with BD, and potential selection bias was introduced due to only including subjects who received AOM three or more times. ConclusionThe results of this study suggest that AOM can reduce mood episode relapse and may be clinically beneficial in the treatment of BD patients, potentially reducing issues associated with polypharmacy in some individuals.

Hormonal and inflammatory signatures of different mood episodes in bipolar disorder: a large-scale clinical study

BackgroundBipolar disorder (BD) is characterized by intensive mood fluctuations. While hormones imbalance plays important role in the mood swings, it is unknown whether peripheral hormones profiles could differentiate the manic and depressive mood episodes in BD. In this study, we investigated the changes of various hormones and inflammatory markers across distinct mood episodes of BD in a large clinical study to provide mood episode-specific peripheral biomarkers for BD.MethodsA total of 8332 BD patients (n = 2679 depressive episode; n = 5653 manic episode) were included. All patients were in acute state of mood episodes and need hospitalization. A panel of blood tests were performed for levels of sex hormones (serum levels of testosterone, estradiol, and progesterone), stress hormones (adrenocorticotropic hormone and cortisol), and an inflammation marker (C-reactive protein, CRP). A receiver operating characteristic (ROC) curve was used to analyze the discriminatory potential of the biomarkers for mood episodes.ResultsIn overall comparison between mood episodes, the BD patients expressed higher levels of testosterone, estradiol, progesterone, and CRP (P < 0.001) and lower adrenocorticotropic hormone (ACTH) level (P < 0.001) during manic episode. The episode-specific changes of testosterone, ACTH, and CRP levels remained between the two groups (P < 0.001) after correction for the confounding factors including age, sex, BMI, occupation, marital status, tobacco use, alcohol consumption, psychotic symptoms, and age at onset. Furthermore, we found a sex- and age-specific impact of combined biomarkers in mood episodes in male BD patients aged ≥ 45 years (AUC = 0.70, 95% CI, 0.634–0.747), not in females.ConclusionsWhile both hormone and inflammatory change is independently associated with mood episodes, we found that the combination of sex hormones, stress hormones and CRP could be more effective to differentiate the manic and depressive episode. The biological signatures of mood episodes in BD patients may be sex- and age-specific. Our findings not only provide mood episode-related biological markers, but also better support for targeted intervention in BD treatments.

Digitally acquired recreational computer programming activity and its association with bipolar disorder mood episodes.

Digitally acquired recreational computer programming activity and its association with bipolar disorder mood episodes.

Circadian variability of objective sleep measures predicts the relapse of a mood episode in bipolar disorder: findings from the APPLE cohort.

Sleep disturbance, a core feature of bipolar disorder, is closely associated with mood symptoms. We examined the association between actigraphy sleep parameters and mood episode relapses in patients with bipolar disorder. This prospective cohort study analyzed 193 outpatients with bipolar disorder who participated in the Association between the Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study. The participants' sleep was objectively evaluated via actigraphy over seven consecutive days for the baseline assessment and then at the 2-year follow-up appointment for mood episode relapses. The actigraphy sleep parameters were presented using the mean and variability (standard deviation) of each sleep parameter for 7 days. Of the 193 participants, 110 (57%) experienced mood episodes during follow-up. The participants with higher variability in total sleep time had a significantly shorter mean estimated time to mood episode relapses than those with lower variability (12.5 vs. 16.8 months; P < 0.001). The Cox proportional hazards model, when adjusted for potential confounders, demonstrated that variability in total sleep time was significantly associated with an increase in the mood episode relapses (per hour; hazard ratio [HR], 1.407; 95% confidence interval (CI), 1.057-1.873), mainly in the depressive episodes (per hour; HR, 1.477; 95% CI, 1.088-2.006). Our findings suggest that consistency in sleep time might be useful, as an adjunct therapy, in preventing the recurrence or relapse of mood episodes in bipolar disorder.

A comparative meta-analysis of peripheral 8-hydroxy-2′-deoxyguanosine (8-OHdG) or 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxo-dG) levels across mood episodes in bipolar disorder

ObjectiveOxidative DNA damage has been associated with the pathophysiology of bipolar disorder (BD) as one of the common pathways between increased medical comorbidity and premature aging in BD. Previous evidence shows increased levels of oxidatively induced DNA damage markers, 8-hydroxy-2′-deoxyguanosine (8-OHdG) or its tautomer 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxo-dG), in patients with BD in comparison to healthy individuals. With the current research, we aim to analyze data on peripheral (blood or urine) 8-OHdG/8-oxo-dG levels across mood states of BD using a meta-analytical approach. MethodA literature search was conducted using the databases PubMed, Scopus, and Web of Science to identify eligible studies (January 1989 to July 2022). Relevant studies were systematically reviewed; a random-effects meta-analysis and a meta-regression analysis were conducted. ResultsThe current meta-analysis included 12 studies consisting of 808 BD patients (390 in euthymia, 156 in mania, 137 in depression, 16 in mixed episode, 109 not specified) and 563 healthy controls. BD patients that were currently depressed had significantly higher levels of 8-OHdG/8-oxo-dG than healthy controls, while euthymic or manic patients did not differ from healthy controls. A meta-regression analysis showed sex distribution (being female) and older age to be significantly related to increased 8-OHdG/8-oxo-dG levels. ConclusionOur findings suggest that 8-OHdG/8-oxo-dG may be a state-related marker of depression in BD and may be affected by older age and female gender.

Resilience Moderates the Associations between Bipolar Disorder Mood Episodes and Mental Health

Resilience could moderate the impact of bipolar disorder (BD) on patients’ quality of life (QoL) and psychosocial functioning. This study aimed to (1) explore the relationships between bipolar disorder mood episodes (depression, &lsqb;hypo&rsqb;mania, and euthymia) and mental health outcomes of QoL, personal recovery, impaired work, and psychosocial functioning in individuals with BD; and (2) determine whether resilience domains were moderators of these associations. A clinical adult sample of 97 individuals diagnosed with BD (63.90&percnt; female, mean age = 45.02 years) completed a battery of BD-specific measures of resilience and mental health-related variables. Multiple regression showed that self-management of BD resilience domain moderated the negative relationship between (hypo)manic episode and personal recovery. Furthermore, self-confidence moderated the positive relationships between (hypo)manic and depressive episodes and impaired functioning. We suggest that BD patients experiencing (hypo)manic or depressive episodes may improve their mental health and wellbeing through interventions that promote disorder-specific resilience factors.

Differences in the prophylactic effect of serum lithium levels on depression and mania in bipolar disorder: A dose-response meta-analysis

The optimal serum lithium levels for preventing the recurrence of mood episodes in bipolar disorder are controversial, especially when polarity is considered. The present study aimed to comprehensively examine the dose-response relationship between lithium concentration and risk of recurrence of mood episodes. We conducted a systematic search of major databases before January 2021 (PROSPERO: CRD42021235812). A one-stage, random-effects, restricted cubic splines model was used to estimate the dose-response relationship between lithium concentration and risk of recurrence of any or specific mood episodes (depression or mania). The effect size is shown as odds ratio (OR). Our meta-analysis included six randomised controlled trials with a total of 975 participants. The dose-response curve showed that increased serum concentrations were associated with a gradual decrease in the risk of any mood episodes (OR 0.50 at 0.60 mmol/l, OR 0.15 at 1.20 mmol/l). The risk of depression decreased slightly with a concentration of 0.60 mmol/l (OR 0.83) but dropped rapidly as the concentration increased to 1.20 mmol/l (OR 0.39). By contrast, the risk for mania initially decreased steadily (OR 0.44), but decreased only marginally (OR 0.30) as the concentration increased. To reduce the recurrence risk to 56%, prevention of depression required a higher concentration than that required for mania (1.13 mmol/l vs. 0.60 mmol/l). Our results suggest a negative dose-response relationship between serum lithium levels and risk of recurrence. In particular, the different preventive effects of serum concentration on depression and mania will be an important clinical reference.

Stochastic modelling of transition dynamic of mixed mood episodes in bipolar disorder

In the present state of health and wellness, mental illness is always deemed less importance compared to other forms of physical illness. In reality, mental illness causes serious multi-dimensional adverse effect to the subject with respect to personal life, social life, as well as financial stability. In the area of mental illness, bipolar disorder is one of the most prominent type which can be triggered by any external stimulation to the subject suffering from this illness. There diagnosis as well as treatment process of bipolar disorder is very much different from other form of illness where the first step of impediment is the correct diagnosis itself. According to the standard body, there are classification of discrete forms of bipolar disorder viz. type-I, type-II, and cyclothymic. Which is characterized by specific mood associated with depression and mania. However, there is no study associated with mixed-mood episode detection which is characterized by combination of various symptoms of bipolar disorder in random, unpredictable, and uncertain manner. Hence, the model contributes to obtain granular information with dynamics of mood transition. The simulated outcome of the proposed system in MATLAB shows that resulting model is capable enough for detection of mixed mood episode precisely

Complexity and variability analyses of motor activity distinguish mood states in bipolar disorder.

Changes in motor activity are core symptoms of mood episodes in bipolar disorder. The manic state is characterized by increased variance, augmented complexity and irregular circadian rhythmicity when compared to healthy controls. No previous studies have compared mania to euthymia intra-individually in motor activity. The aim of this study was to characterize differences in motor activity when comparing manic patients to their euthymic selves. Motor activity was collected from 16 bipolar inpatients in mania and remission. 24-h recordings and 2-h time series in the morning and evening were analyzed for mean activity, variability and complexity. Lastly, the recordings were analyzed with the similarity graph algorithm and graph theory concepts such as edges, bridges, connected components and cliques. The similarity graph measures fluctuations in activity reasonably comparable to both variability and complexity measures. However, direct comparisons are difficult as most graph measures reveal variability in constricted time windows. Compared to sample entropy, the similarity graph is less sensitive to outliers. The little-understood estimate Bridges is possibly revealing underlying dynamics in the time series. When compared to euthymia, over the duration of approximately one circadian cycle, the manic state presented reduced variability, displayed by decreased standard deviation (p = 0.013) and augmented complexity shown by increased sample entropy (p = 0.025). During mania there were also fewer edges (p = 0.039) and more bridges (p = 0.026). Similar significant changes in variability and complexity were observed in the 2-h morning and evening sequences, mainly in the estimates of the similarity graph algorithm. Finally, augmented complexity was present in morning samples during mania, displayed by increased sample entropy (p = 0.015). In conclusion, the motor activity of mania is characterized by altered complexity and variability when compared within-subject to euthymia.

Prospective early warning signals to detect transitions to manic and depressive episodes in bipolar disorder

IntroductionFor patients with bipolar disorder, early recognition of impending mood episodes is crucial to enable timely intervention. Longitudinal digital mood monitoring using ecological momentary assessment (EMA) enable prospective study of early warning signals (EWS) in momentary affective estates prior to symptom transitions.ObjectivesThe present study examined in a unique longitudinal EMA data set whether EWS prospectively signal transitions to manic or depressive episodes.MethodsTwenty bipolar type I/II patients completed EMA questionnaires five times a day for four months (average 491 observations per person), as well as weekly symptom questionnaires concerning depressive (Quick Inventory for Depressive Symptomatology) and manic (Altman Self-Rating Mania Scale) symptoms. Weekly data was used to determine transitions (i.e., abrupt increase in symptoms). Prior to these transitions, EWS (autocorrelation at lag-1 and standard deviation) were calculated in moving windows over 17 affective EMA states. Kendall’s tau was calculated to detect significant rises in the EWS indicator prior to the transition.ResultsEleven patients reported one or two transitions to a mood episode. All transitions were preceded by at least one EWS. Average sensitivity for detecting EWS was slightly higher for manic episodes (36%) than for depressive episodes (25%). For manic episodes, EWS in thoughts racing, being full of ideas, and feeling agitated showed the highest sensitivity and specificity, whereas for depression, only feeling tired showed high sensitivity and specify.ConclusionsEWS show promise in anticipating transitions to mood episodes in bipolar disorder. Further investigation is warranted.DisclosureNo significant relationships.

Odour identification impairment is a trait but not a disease-specific marker for bipolar disorders: Comparisons of bipolar disorder with different episodes, major depressive disorder and schizophrenia.

Olfactory deficits have been reported in bipolar disorder, but this finding is controversial. This study investigated whether olfactory deficit can serve as a specific marker for bipolar disorder by comparing olfactory function in different mood episodes of bipolar disorder. We also compared olfactory function in bipolar disorder and other mental disorders - namely, major depressive disorder and schizophrenia. The study consisted of two experiments. Experiment 1 enrolled 175 bipolar disorder patients (70 depressed subgroup, 70 manic subgroup and 35 euthymic subgroup) and 47 controls. Experiment 2 enrolled the participants from Experiment 1, along with 85 major depressive disorder and 90 schizophrenia patients. The Sniffin' Sticks test was used to evaluate odour identification ability and odour threshold (as a measure of odour sensitivity). The Hamilton Depression Rating Scale and Young Mania Rating Scale were used to assess depressive symptoms in all subjects and manic symptoms in bipolar disorder patients, respectively. We also used the Positive and Negative Syndrome Scale to assess clinical symptoms in schizophrenia patients. All three bipolar disorder patient subgroups (depressed, manic and euthymic subgroup) showed reduced odour identification ability compared to controls; however, only patients in the acute phase of a mood episode (depressed, and manic subgroup) showed impaired odour sensitivity. Clinical symptoms were negatively correlated with odour sensitivity but not odour identification ability. Bipolar disorder and major depressive disorder patients showed less odour identification and sensitivity impairment than schizophrenia patients. Odour sensitivity is a potential dopaminergic marker for distinguishing between bipolar disorder patients in acute phase vs remission, while odour identification is a trait but a nonspecific marker of bipolar disorder.

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder.

Background: Several inflammatory hypotheses have been suggested to explain the etiopathogenesis of bipolar disorder (BD) and its different phases. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and monocyte-to-lymphocyte (MLR) ratios have been proposed as potential peripheral biomarkers of mood episodes. Methods: We recruited 294 patients affected by BD, of which 143 were experiencing a (hypo)manic episode and 151 were in a depressive phase. A blood sample was drawn to perform a complete blood count. NLR, PLR, and MLR were subsequently calculated. A t-test was performed to evaluate differences in blood cell counts between depressed and (hypo)manic patients and a regression model was then computed. Results: Mean values of neutrophils, platelets, mean platelet volume, NLR, PLR, and MLR were significantly higher in (hypo)manic than depressed individuals. Logistic regression showed that PLR may represent an independent predictor of (hypo)mania. Conclusions: Altered inflammatory indexes, particularly PLR, may explain the onset and recurrence of (hypo)manic episodes in patients with BD. As inflammatory ratios represent economical and accessible markers of inflammation, further studies should be implemented to better elucidate their role as peripheral biomarkers of BD mood episodes.

Cariprazine for acute mood episodes in bipolar disorder.

Pinto et al. recently published a systematic review and meta-analysis of randomized controlled trials (RCTs) investigating efficacy and tolerability of cariprazine in the treatment of bipolar disorder. In their analysis, authors included 7 RCTs, out of 225 studies screened after duplicates removal, synthesizing effect sizes of RCTs for manic/mixed and depressive episodes.1 The study found that cariprazine (doses 3-12 mg/day) had a significant and moderate impact when treating manic episodes (SMD: -0.52; 95%CI: -0.82 to -0.21; P = .018). However, cariprazine was not found to be associated with improvements in psychotic or depressive symptoms during manic/mixed episodes. As for depressive episodes, the summarized effect sizes were significant but small for 1.5 mg (SMD: -0.26, 95%CI: -0.49 to -0.02; P = .040) and 3 mg (SMD: -0.21, 95%CI: -0.41 to -0.01; P = .045) daily doses. Cariprazine did not have a significant impact on bipolar depression at 0.75 mg daily doses. Authors also reported that cariprazine is well tolerated since there was no association of adverse effects due to the medication with dropouts from the RCTs in comparison with placebo.

Biological Targets Underlying the Antisuicidal Effects of Lithium

This article highlights the potential relationship of lithium’s cellular and molecular targets to its antisuicidal effects in bipolar disorder (BD). Lithium is the mood stabilizer that shows the most robust therapeutic evidence in relapse prevention and mood episodes in BD. Compelling evidence also elucidates lithium’s unique effects in reversing and preventing suicidal behavior (SB), mostly in individuals with BD. The following review is an up-to-date summary of studies related to the anti-suicidal effects of lithium in patients with BD. We focused on studies investigating the similarities in pathogenesis of BD and SB and the related treatment targets for lithium’s anti-suicidal actions. Lithium seems to have beneficial effects in reversing pathophysiological changes in SB and BD associated with its ability to reduce suicidal risk. Several neurobiological targets have been associated with the antisuicidal effects of lithium such as brain atrophy and demyelination, alterations in glutamatergic neurotransmission, and increased central and peripheral inflammation as well as HPA axis hyperactivation, cell signaling pathways, and neurotrophic system dysfunctions. Further studies are required to elucidate the presence of a specific neurobiological signature of SB as an independent clinical dimension and not solely in the context of mood episodes.

Clinical validation of the BDSx scale with bipolar disorder outpatients

PurposeThe BDSx (Bipolar Disorder Symptom Scale) is a brief self-report instrument designed for repeated measurement of bipolar disorder (BD) symptoms over time. Previous research indicates that the BDSx measures two depression (cognitive and somatic symptoms) and two hypo/mania factors (affrontive symptoms and elation/loss of insight). The purpose of this study was to validate BDSx responses relative to diagnoses of BD mood episodes. MethodsSixty BD outpatients attending routine clinic appointments completed the BDSx, the Hamilton Rating Scale for Depression, the Altman Self-Rating Mania Scale, and the Satisfaction with Life Scale. Blind to scale responses by patients, a clinic psychiatrist determined if patients were currently symptomatic. ResultsBDSx depression and hypo/mania subscales showed good construct validity vis-à-vis clinical diagnoses, and concurrent/discriminant validity with other self-report scales. And though not designed as a screening measure, sensitivity for the depression subscale is high at 88% (6+, 76% specificity), yet lower at 57% for the hypo/mania subscale (5+, 90% specificity). ConclusionsThe results of this study indicate that BDSx responses distinguish patients experiencing depressive and hypo/manic mood episodes. Findings support the psychometric properties of the Hebrew version of this scale. The BDSx enables those with bipolar disorder to monitor their symptoms, gauge symptom variability, and identify factors that proceed and sustain BD symptoms over time.

Reward-Related Striatal Responses Following Stress in Healthy Individuals and Patients With Bipolar Disorder

BackgroundStress has a major impact on the onset and recurrence of mood episodes in bipolar disorder (BD), but the underlying mechanisms remain unknown. Previous studies have shown distinct time-dependent effects of stress on reward processing in healthy individuals. Impaired reward processing is a core characteristic of BD, and altered reward processing during recovery from stress could influence the development and course of bipolar disorder. MethodsWe investigated brain responses during reward processing 50 minutes after stress using functional magnetic resonance imaging in 40 healthy control subjects and 40 patients with euthymic BD assigned to either an acute stress test (Trier Social Stress Test) or a no-stress condition. ResultsAcute stress increased cortisol levels in both healthy control subjects and patients with BD. Ventral striatal responses to reward outcome were increased in healthy control subjects during stress recovery but not in patients with BD. For anticipation, no differences were found between the groups following stress. ConclusionsFor the first time, we show altered reward processing in patients with BD during the recovery phase of stress. These data suggest reduced neural flexibility of hedonic signaling in response to environmental challenges. This may increase the susceptibility to stressful life events in the future and play a role in the development of further psychopathology in the longer term.

Neurophysiological effects of multiple mood episodes in bipolar disorder.

Bipolar disorder is marked by progressive symptomatic changes, which have been linked with episode-related structural findings-particularly in the prefrontal cortex. However, few studies have examined neurofunctional and neurochemical effects of disease burden. In this study, we compared first- and multi-episode bipolar individuals. We hypothesized that the latter would demonstrate evidence of neurophysiological differences consistent with a model of progressive functional degradation of these networks. First- and multi-episode manic bipolar subjects participated in functional magnetic resonance imaging (fMRI) including a continuous performance task with emotional distractors, and in single-voxel (1 H) magnetic resonance spectroscopy (MRS). A priori fMRI regions-of-interest (ROI) included structures comprising prefrontal-striatal-amygdala networks; (1 H)MRS voxels were placed within bilateral ventrolateral prefrontal (VLPFC) and anterior cingulate cortex (ACC). Both ROI and voxel-based brain activation in response to emotional stimuli, and neurochemical concentrations derived from (1 H)MRS were compared across bipolar groups. Multi-episode bipolar subjects showed relatively lower regional activation across prefrontal-striatal-amygdala networks, including bilateral VLPFC, orbitofrontal cortex, ACC, putamen, caudate, and amygdala. Exploratory whole-brain, voxel-based analysis suggested additional areas of lower activation extending into Brodmann area 22, posterior parietal regions, and right thalamus. Glutamate and N-acetylaspartate (NAA) concentrations were also relatively lower in the ACC of multi-episode subjects. Disease burden, exemplified by multiple affective episodes is associated with evidence of widespread decrements in affective network activity. Lower ACC NAA concentration is similarly consistent with a model of progressive functional deficits. These findings support the functional significance of previously observed progressive structural changes throughout these regions.

Racing thoughts revisited: A key dimension of activation in bipolar disorder

BackgroundRacing and crowded thoughts are frequently reported respectively in manic and mixed episodes of bipolar disorder (BD). However, questionnaires assessing this symptom are lacking. Here we aimed to investigate racing thoughts across different mood episodes of BD through a self-report questionnaire that we developed, the 34-item Racing and Crowded Thoughts Questionnaire (RCTQ). In addition to assessing its factor structure and validity, we were interested in the RCTQ's ability to discriminate mixed and non-mixed depression. Methods221 BD patients and 120 controls were clinically assessed via the YMRS (mania) and the QIDS-C16 (depression), then fulfilled the RCTQ, rumination, worry, and anxiety measures. Three depression groups were operationalized according to YMRS scores: YMRS scores 2 > 6 and YMRS scores = 1 or 2, for respectively mixed and non-pure depression, and YMRS = 0 for pure-depression. ResultsConfirmatory factor analysis showed that the three-factor model of the RCTQ yielded the best fit indices, which improved after the removal of redundant items, resulting in a 13-item questionnaire. Hypomanic and anxiety symptoms were the main predictors of scores; rumination was not a significant predictor. RCTQ results were similar between mixed groups and non-pure depression, and both were higher than in pure-depression. LimitationsPatients’ pharmacological treatment might have influenced the results. ConclusionsThe 13-item RCTQ captures different facets of racing thoughts heightened in hypomanic and mixed states, but also in depression with subclinical hypomanic/activation symptoms (e.g. non-pure depression characterized by enhanced subjective irritability), suggesting that it is particularly sensitive to activation symptoms in BD, and could become a valuable tool in the follow-up of patients.

Episode forecasting in bipolar disorder: Is energy better than mood?

Bipolar disorder is a severe mood disorder characterized by alternating episodes of mania and depression. Several interventions have been developed to decrease high admission rates and high suicides rates associated with the illness, including psychoeducation and early episode detection, with mixed results. More recently, machine learning approaches have been used to aid clinical diagnosis or to detect a particular clinical state; however, contradictory results arise from confusion around which of the several automatically generated data are the most contributory and useful to detect a particular clinical state. Our aim for this study was to apply machine learning techniques and nonlinear analyses to a physiological time series dataset in order to find the best predictor for forecasting episodes in mood disorders. We employed three different techniques: entropy calculations and two different machine learning approaches (genetic programming and Markov Brains as classifiers) to determine whether mood, energy or sleep was the best predictor to forecast a mood episode in a physiological time series. Evening energy was the best predictor for both manic and depressive episodes in each of the three aforementioned techniques. This suggests that energy might be a better predictor than mood for forecasting mood episodes in bipolar disorder and that these particular machine learning approaches are valuable tools to be used clinically. Energy should be considered as an important factor for episode prediction. Machine learning approaches provide better tools to forecast episodes and to increase our understanding of the processes that underlie mood regulation.