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Affective temperaments show potential for aggressive behavior (AB) preventive strategies in bipolar disorder (BD). We aim to define intra-diagnostic subgroups of patients with BD based on homogeneous behaviors related to AB. Subsequently, to assess whether affective temperament dimensions may contribute to the presence and severity of AB.Patients with BD were recruited. AB was evaluated through the modified overt aggression scale (MOAS); affective temperaments were assessed with the TEMPS-A. A cluster analysis was conducted based on TEMPS-A and MOAS scores. Stepwise backward logistic regression models were used to identify the predictive factors of cluster membership.799 patients with BD were enrolled. Three clusters were determined: non-aggressive (55.5 %), self-aggressive (18 %), and hetero-aggressive (26.5 %). Depressive, irritable, and anxious temperament scores significantly increased from the non-aggressive (lower) to the self-aggressive (intermediate) and the hetero-aggressive group (highest). A positive history of a suicide attempt (B = 5.131; OR = 169.2, 95 % CI 75.9; 377) and rapid cycling (B = -0.97; OR = 0.40, 95 % CI 0.17; 0.95) predicted self-aggressive cluster membership. Atypical antipsychotics (B = 1.19; OR = 3.28, 95 % CI 2.13; 5.06) or SNRI treatment (B = 1.09; OR = 3, 95 % CI 1.57; 5.71), psychotic symptoms (B = 0.73; OR = 2.09, 95 % CI 1.34; 3.26), and history of a suicide attempt (B = -1.56; OR = 0.20, 95 % CI 0.11; 0.38) predicted hetero-aggressive cluster membership.Recall bias might have affected the recollection of AB.Clinical factors orientate the prevention of different ABs in BD. Affective temperaments might play a role in preventing AB since patients with more pronounced affective temperaments might have an increased risk of showing AB, in particular hetero-AB.

Several psychotropic drugs, including antidepressants (AD), mood stabilizers, and antipsychotics (AP) have been suggested to have favorable effects in the treatment of COVID-19. The aim of this systematic review and meta-analysis was to collect evidence from studies concerning the scientific evidence for the repurposing of psychotropic drugs in COVID-19 treatment. Two independent authors searched PubMed-MEDLINE, Scopus, PsycINFO, and ClinicalTrials.gov databases, and reviewed the reference lists of articles for eligible articles published up to 13th December 2021. All computational, preclinical and clinical (observational and/or RCTs) studies on the effect of any psychotropic drug on Sars-CoV-2 or patients with COVID-19 were considered for inclusion. We conducted random effect meta-analyses on clinical studies reporting the effect of AD or AP on COVID-19 outcomes. 29 studies were included in the synthesis: 15 clinical, 9 preclinical, and 5 computational studies. 9 clinical studies could be included in the quantitative analyses. AD did not increase the risk of severe COVID-19 (RR= 1.71; CI 0.65-4.51) or mortality (RR=0.94; CI 0.81-1.09). Fluvoxamine was associated with a reduced risk of mortality for COVID-19 (OR=0.15; CI 0.02-0.95). AP increased the risk of severe COVID-19 (RR=3.66; CI 2.76-4.85) and mortality (OR=1.53; CI 1.15-2.03). Fluvoxamine might be a possible candidate for psychotropic drug repurposing in COVID-19 due to its anti-inflammatory and antiviral potential, while evidence on other AD is still controversial. Although AP are associated with worse COVID-19 outcomes, their use should be evaluated case to case and ongoing treatment with antipsychotics should be not discontinued in psychiatric patients.

Suicide claims over 800,000 deaths worldwide, making it a serious public health problem. The etiopathophysiology of suicide remains unclear and is highly complex, and postmortem gene expression studies can offer insights into the molecular biological mechanism underlying suicide. In the current study, we conducted a meta-analysis of postmortem brain gene expression in relation to suicide. We identified five gene expression datasets for postmortem orbitofrontal, prefrontal, or dorsolateral prefrontal cortical brain regions from the Gene Expression Omnibus repository. After quality control, the total sample size was 380 (141 suicide deaths and 239 deaths from other causes). We performed the analyses using two meta-analytic approaches. We further performed pathway and cell-set enrichment analyses. We found reduced expression of the KCNJ2 (Potassium Inwardly Rectifying Channel Subfamily J Member 2), A2M (Alpha-2-Macroglobulin), AGT (Angiotensinogen), PMP2 (Peripheral Myelin Protein 2), and VEZF1 (Vascular Endothelial Zinc Finger 1) genes (FDR p0.05). Our findings support the involvement of astrocytes, stress response, immune system, and microglia in suicide. These findings will require further validation in additional large datasets.

Background: We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD). Methods: 261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (

BACKGROUND Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. OBJECTIVE Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels’ individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales’ items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. RESULTS Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with “increased motor activity” (NMI>0.55), “insomnia” (NMI=0.6), and “motor inhibition” (NMI=0.75). EDA was associated with “aggressive behavior” (NMI=1.0) and “psychic anxiety” (NMI=0.52). CONCLUSIONS Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

BACKGROUND Many people attending primary care (PC) have anxiety-depressive symptoms and work-related burnout compounded by a lack of resources to meet their needs. The COVID-19 pandemic has exacerbated this problem, and digital tools have been proposed as a solution. OBJECTIVE We aimed to present the development, feasibility, and potential effectiveness of Vickybot, a chatbot aimed at screening, monitoring, and reducing anxiety-depressive symptoms and work-related burnout, and detecting suicide risk in patients from PC and health care workers. METHODS Healthy controls (HCs) tested Vickybot for reliability. For the simulation study, HCs used Vickybot for 2 weeks to simulate different clinical situations. For feasibility and effectiveness study, people consulting PC or health care workers with mental health problems used Vickybot for 1 month. Self-assessments for anxiety (Generalized Anxiety Disorder 7-item) and depression (Patient Health Questionnaire-9) symptoms and work-related burnout (based on the Maslach Burnout Inventory) were administered at baseline and every 2 weeks. Feasibility was determined from both subjective and objective user-engagement indicators (UEIs). Potential effectiveness was measured using paired 2-tailed t tests or Wilcoxon signed-rank test for changes in self-assessment scores. RESULTS Overall, 40 HCs tested Vickybot simultaneously, and the data were reliably transmitted and registered. For simulation, 17 HCs (n=13, 76% female; mean age 36.5, SD 9.7 years) received 98.8% of the expected modules. Suicidal alerts were received correctly. For the feasibility and potential effectiveness study, 34 patients (15 from PC and 19 health care workers; 76% [26/34] female; mean age 35.3, SD 10.1 years) completed the first self-assessments, with 100% (34/34) presenting anxiety symptoms, 94% (32/34) depressive symptoms, and 65% (22/34) work-related burnout. In addition, 27% (9/34) of patients completed the second self-assessment after 2 weeks of use. No significant differences were found between the first and second self-assessments for anxiety (t8=1.000; P=.34) or depressive (t8=0.40; P=.70) symptoms. However, work-related burnout scores were moderately reduced (z=−2.07, P=.04, r=0.32). There was a nonsignificant trend toward a greater reduction in anxiety-depressive symptoms and work-related burnout with greater use of the chatbot. Furthermore, 9% (3/34) of patients activated the suicide alert, and the research team promptly intervened with successful outcomes. Vickybot showed high subjective UEI (acceptability, usability, and satisfaction), but low objective UEI (completion, adherence, compliance, and engagement). Vickybot was moderately feasible. CONCLUSIONS The chatbot was useful in screening for the presence and severity of anxiety and depressive symptoms, and for detecting suicidal risk. Potential effectiveness was shown to reduce work-related burnout but not anxiety or depressive symptoms. Subjective perceptions of use contrasted with low objective-use metrics. Our results are promising but suggest the need to adapt and enhance the smartphone-based solution to improve engagement. A consensus on how to report UEIs and validate digital solutions, particularly for chatbots, is required.

Susac-syndrome is a rare autoimmune disease that manifests with mood alterations in up to 15% of cases and is usually treated with corticosteroids. We present the case of a 41-year-old woman with a first manic episode and history of Susac-syndrome, secondary Cushing's syndrome after receiving high doses of corticosteroids and a previous depressive episode. Differentiating between primary and secondary mania is difficult, as people with bipolar disorder are prone to multiple psychiatric and nonpsychiatric comorbidities, in this case, the differential diagnosis included secondary mania, corticoid-induced manic episode and primary bipolar disorder. Upon admission, corticosteroid treatment was suspended, and the patient was started on lithium and risperidone. Secondary causes of mania were discarded and, assessing temporal and dosage criteria, it was deemed unlikely that the present episode was corticosteroid-induced. One-year outpatient follow-up pointed towards a primary bipolar type I disorder, as a separate entity from her Susac-syndrome. Corticosteroid use or abrupt withdrawal pose an underestimated risk of inducing depressive or manic symptoms, which may unmask affective disorders in susceptible individuals. Many medical conditions share CNS involvement and/or high-dose/prolonged corticosteroid treatment. In such cases, psychiatric manifestations such as mania or depression should be regarded as secondary and studied to determine the existence of medical complications before considering primary psychiatric conditions.

We examined bipolar disorder (BD) as a risk factor for developing cancer and the role of lithium on cancer incidence. We conducted two systematic review and meta-analyses of population-based studies providing data on these associations. We screened articles indexed in MEDLINE, Scopus, Embase, and PsycINFO up to August 2020. The first random-effects meta-analysis, based on 4,910,661 individuals from nine studies estimated an increased risk of cancer of any kind [RR = 1.24 (1.05-1.46); p < 0.01], especially breast cancer [RR = 1.33 (1.15-1.55); p < 0.01] in BD. The second random-effects meta-analysis, based on 2,606,187 individuals from five studies did not show increased risk of cancer in people with BD using lithium, and even suggested a small protective effect both in overall [RR = 0.94 (0.72-1.22); p = 0.66] and urinary cancer [RR = 0.93 (0.75-1.14); p = 0.48] although these findings did not reach statistical significance. The current evidence highlights that cancer risk is increased in individuals with BD, particularly breast cancer in women. Lithium may have a potential protective effect on cancer, including urinary cancer. The role of lithium as a mainstay of treatment for BD is reinforced by this study.

Mood disorders are severe and chronic mental conditions exacting high costs from society. The lack of reliable biomarkers to aid clinicians in tailoring pharmacotherapy based on distinguishable patient-specific traits means that the current prescribing paradigm is largely one of trial and error. Previous studies showed that different biological signatures, such as patterns of heart rate variability or electro-dermal reactivity, are associated with clinically meaningful outcomes. Against this backdrop, the advances in machine learning and the spread of wearable devices capable of providing continuous and ecological monitoring of patients may unlock great opportunities in mental healthcare. We herewith present a pilot study on mania and depression where we moved beyond the simple disease state binary classification but pursued the more informative and clinically meaningful task of differentiating between levels of disease severity. While most previous similar endeavours used recording segments extracted from the same subjects for both training and testing, we explicitly carried out model development and evaluation on segments from different groups of patients, in order to have a fair assessment of the model out-of-sample generalisation. This illustrated how individuals heterogeneity and non-disease-related dimensions of variations (e.g. sex, age, physical fitness) may dominate the signal so that in low sample size regimes a model might learn and overfit subject-specific patterns rather than capturing disease-relevant traits generalisable across disorders. Lastly, we developed a viable baseline for pre-processing raw data from wristband recordings and compared three classical and two deep-learning models to identify levels of disease severity.

OBJECTIVE Seasonal pattern (SP) is a bipolar disorder (BD) specifier that indicates a tendency towards affective relapses during specific moments of the year. SP affects 15%-25% of BD patients. In the past, SP was applied only to depressive relapses while, in DSM-5, SP may be applied to both depressive and (hypo)manic episodes. We examined the association between different clinical correlates of BD and SP according to its current definition in a cohort of patients with BD type I (BDI) and II (BDII). METHODS Patients were recruited from a specialized unit and assessed according to the season of relapse and type of episode per season. SP and non-SP patients were compared looking into sociodemographic and clinical correlates. Significant variables at univariate comparisons were included in multivariate logistic regression with SP as the dependent variable. RESULTS 708 patients were enrolled (503 BDI, 205 BDII), and 117 (16.5%) fulfilled DSM-5 criteria for SP. The mean age was 45.3 years (SD = 14.18), and 389 were female (54.9%). The logistic regression model included a significant contribution of BDII (OR = 2.23, CI 1.4-3.55), family history of mood disorder (OR = 1.97, CI 1.29-3.01), undetermined predominant polarity (OR = 0.44, CI 0.28-0.70), and aggressive behavior (OR = 0.42, CI 0.23-0.75). CONCLUSION Our results outline a novel positive association of SP with undetermined predominant polarity, BDII, family history of mood disorder, and with fewer aggressiveness-related symptoms. Seasonality is associated with a biphasic pattern with similar dominance of (hypo)mania and depression and is more frequent in BDII as compared to BDI. Seasonal episodes may be easier to predict, but difficult to prevent.

Highlights • A retrospective analysis was performed of all patients admitted to the Psychiatric Emergency Service 90 days before and after March 14th, 2020, the first day of lockdown in Spain due to COVID-19. • During the lockdown the number of admissions decreased by 37.9% while a significant increase in the percentage of patients requiring acute psychiatric hospitalization was observed. • Anxiety spectrum disorders accumulated the greatest decrease in admission rates compared to the three months before lockdown. • A statistically significant increase in admissions rates was found in patients with dementia-like cognitive impairments, autism spectrum, and substance use disorders during the lockdown., Background During the COVID-19 pandemic, a structural reorganization was imposed on public health systems. Psychiatry services were also affected with the imposed reduction of non-urgent consultations. We aim to explore the effect of these changes on a Psychiatry Emergency Service during COVID-19 lockdown in Spain. Methods A retrospective analysis was performed on all patients admitted to our Psychiatric Emergency Service 90 days before and after March 14th, 2020, the first day of lockdown in Spain. Extracted data were compared between the two periods. Poisson regression analysis was performed to analyze changes in admission rates. Results 1,958 psychiatric emergency admissions were analyzed. Although the number of admissions decreased by 37.9%, we observed a significant increase in the percentage of acute psychiatric hospitalization during the lockdown. Anxiety spectrum disorders accumulated the greatest significant decrease in admission rates during the lockdown. On the other hand, a significant increase in admissions rates was found in patients with dementia, autism spectrum disorders, and substance use disorders during the lockdown. Limitations This study was conducted in a single psychiatric emergency service, preventing a generalization of our results. The comparison time period might have biased our results due to the influence of external factors. Conclusion Mental health consequences of COVID-19 are becoming apparent. A reduction of admission rates for anxiety disorders might be related telepsychiatry implementation during the lockdown. Other conditions particularly vulnerable to the routine changes and lack of social support have suffered the most, and efforts should be placed to treat these situations.

Emotion dysregulation (ED) is characterized by rigid and frequent use of maladaptive emotion regulation (ER) strategies. Conceptualized as a transdiagnostic feature, ED may occur in both clinical and non-clinical populations, including people diagnosed with bipolar disorder (BD) and their first-degree relatives (FDRs), though expected to manifest with differential clinical features. To this end, we conducted a systematic review and meta-analysis of the literature comparing people with BD to healthy controls (HCs) or FDRs, from inception up to November 25, 2021, across major databases. Random-effects meta-analyses considered twenty-eight studies assessing ER/ED with a validated scale. Patients with BD differed from HCs in adopting more maladaptive ER strategies, such as rumination, risk-taking behaviors, negative focus, and less adaptive ones. Unaffected FDRs differed from people with BD, yet to a lower extent, suggesting that ED may span a continuum. ED in BD should be widely explored to better understand its course and management, with specific interventions aimed at reducing its burden on both high-risk and full-threshold populations.

Healthcare workers (HCW) are at high risk for suicide, yet little is known about the onset of suicidal thoughts and behaviors (STB) in this important segment of the population in conjunction with the COVID-19 pandemic. We conducted a multicenter, prospective cohort study of Spanish HCW active during the COVID-9 pandemic. A total of n = 4809 HCW participated at baseline (May-September 2020; i.e., just after the first wave of the pandemic) and at a four-month follow-up assessment (October-December 2020) using web-based surveys. Logistic regression assessed the individual- and population-level associations of separate proximal (pandemic) risk factors with four-month STB incidence (i.e., 30-day STB among HCW negative for 30-day STB at baseline), each time adjusting for distal (pre-pandemic) factors. STB incidence was estimated at 4.2% (SE = 0.5; n = 1 suicide attempt). Adjusted for distal factors, proximal risk factors most strongly associated with STB incidence were various sources of interpersonal stress (scaled 0-4; odds ratio [OR] range = 1.23-1.57) followed by personal health-related stress and stress related to the health of loved ones (scaled 0-4; OR range 1.30-1.32), and the perceived lack of healthcare center preparedness (scaled 0-4; OR = 1.34). Population-attributable risk proportions for these proximal risk factors were in the range 45.3-57.6%. Other significant risk factors were financial stressors (OR range 1.26-1.81), isolation/quarantine due to COVID-19 (OR = 1.53) and having changed to a specific COVID-19 related work location (OR = 1.72). Among other interventions, our findings call for healthcare systems to implement adequate conflict communication and resolution strategies and to improve family-work balance embedded in organizational justice strategies. This work was supported by grants from the Instituto de Salud Carlos III (ISCIII)/Ministerio de Ciencia e Innovación/FEDER, Spain (Jordi Alonso, grant number COV20/00711); ISCIII-FEDER, Spain (Jordi Alonso, grant number PI17/00521); ISCIII-FSE, Spain: Sara Borrell and Miguel Servet grants (Philippe Mortier, grant number CD18/00049 and CP21/00078); Generalitat de Catalunya, Spain (2017SGR452); and PERIS, Departament de Salut, Spain (Itxaso Alayo; SLT017/20/000009). Additional partial funding was received from the Gerencia Regional de Salud de Castilla y León (SACYL), Spain (José María Pelayo Terán, grant number GRS COVID 32/A/20). Sí

Lamotrigine (LTG) is an anticonvulsant drug used for the prevention of depressive episodes in bipolar disorder (BD) that might induce manic episodes in some cases. A 38-year-old man, stabilized with asenapine due to a brief psychotic episode, presented depressive symptoms and LTG was titrated up to 200 mg/day in 6 weeks. One week later he was diagnosed with a first manic episode with psychotic symptoms [Young Mania Rating Scale (YMRS = 31)] and type I BD (BD-I). LTG was withdrawn and he was treated with lithium and lurasidone. The episode remitted in 1 week. A 45-year-old woman with BD presented persistent depressive symptoms and received LTG 25 mg/day. After 3 weeks she was diagnosed with a manic episode with psychotic symptoms (YMRS = 35). LTG was suspended and aripiprazole increased. The episode remitted within 10 days. Both patients remained euthymic with no further episodes after 1-year follow-up. The propensity of LTG to induce manic episodes may be related to its lack of antimanic effects, along with its antidepressant properties, probably related to decreased glutamate release. Secondary analyses from LTG randomized clinical trials have excluded subjects with higher vulnerability to manic switches so that the risk of LTG-induced mania might have been underestimated. LTG-induced mania may be more likely to happen in patients with BD-I, manic predominant polarity, an index manic episode, or those with a history of the antidepressant manic switch. Therefore, in BD patients with the aforementioned risk factors, LTG use should be carefully managed: starting with low doses, extending tapering lengths, using adjunctive treatments and close monitoring manic symptoms.

Suicide contributes to 1–4 % of deaths worldwide every year. We conducted a systematic review aimed at summarizing evidence on the use of lithium for the prevention of suicide risk both in mood disorders and in the general population. We followed the PRISMA methodology (keywords: “lithium”, “suicide” AND “suicidal” on Pubmed, Cochrane CENTRAL, Clinicaltrial.gov, other databases). Inclusion criteria: lithium therapy in mood disorder or found in drinking water or scalp in the general population. Exclusion criteria: no lithium administration. From 918 screened references, 18 prospective (number of participants: 153786), 10 retrospective (number of participants: 61088) and 16 ecological studies (total sample: 2062) were included. Most of the observational studies reported a reduction in suicide in patients with mood disorders. All studies about lithium treatment’s duration reported that long-term lithium give more benefits than short-term lithium in suicide risk The evidence seems to attribute an intrinsic anti-suicidal property of lithium, independent of its proven efficacy as a mood stabilizer.

Highlights • COVID-19 patients with psychiatric disorders should be managed on a personalized basis. • Risks of pharmacological interaction are not absolute and should be contextualized. • Essential psychopharmacological ongoing treatments should be maintained. • Most psychotropic drugs should be reduced 25–50% if given with lopinavir/ritonavir. • Dose titration should be progressive and with ECG monitoring if cardiotoxic risk., Background : The management of coronavirus disease 2019 (COVID-19) in patients with comorbid psychiatric disorders poses several challenges, especially regarding drug interactions. Methods : We report three representative case-scenarios on patients with psychiatric disorders and COVID-19 to provide a practical approach based on the existing literature and the clinical experience of an expert team in consultation-liaison psychiatry. Case-centered recommendations : Psychopharmacological ongoing treatments should be prioritized and most doses should be reduced 25–50% of original dose if the patient receives lopinavir/ritonavir, with some exceptions including quetiapine, asenapine, olanzapine, sertraline, lamotrigine, bupropion, and methadone. If the psychopharmacological usual doses are in the low-to-median range levels, a dose change during COVID-19 drugs co-administration is not recommended, but only ECG and clinical monitoring of adverse effects and drug levels if required. Furthermore, when introducing a psychopharmacological drug, dose titration should be progressive, with ECG monitoring if cardiotoxic interactions are present. (A) In agitated delirium, olanzapine is recommended as first-line antipsychotic and quetiapine should be avoided. (B) In severe mental illness (SMI), essential treatments should be maintained. (C) In non-SMI with depressive/anxiety symptoms, psychological support should be provided and symptoms identified and treated. Limitations : Most recommendations on pharmacological interactions provide only a limited qualitative approach and quantitative recommendations are lacking. Conclusions : Patients with psychiatric disorders and COVID-19 should be managed on a personalized basis considering several clinical criteria and, should not be excluded from receiving COVID-19 treatments. Risks of pharmacological interaction are not absolute and should be contextualized, and most psychopharmacological treatments should include an ECG with special attention to QTc interval.

The Diagnostic and Statistical Manual of Mental Disorders Fifth Edition introduced the specifier "with mixed features" including 3 or more nonoverlapping typical manic symptoms during a major depressive episode in bipolar disorder type I or II or unipolar major depressive disorder. Excluding overlapping excitatory symptoms, which are frequently observed in mixed depression, leaves many patients with mixed depression undiagnosed. As a consequence, alternative diagnostic criteria have been proposed, claiming for the inclusion in the rubric of mixed features the following symptoms: psychomotor agitation, mood lability, and aggressiveness. A deeper diagnostic reconsideration of mixed features in depression should be provided by the new nosologic classification systems.

Parenthood age may affect the risk for the development of different psychiatric disorders in the offspring, including bipolar disorder (BD). The present systematic review and meta-analysis aimed to appraise the relationship between paternal age and risk for BD and to explore the eventual relationship between paternal age and age at onset of BD. We searched the MEDLINE, Scopus, Embase, PsycINFO online databases for original studies from inception, up to December 2021. Random-effects meta-analyses were conducted. Sixteen studies participated in the qualitative synthesis, of which k = 14 fetched quantitative data encompassing a total of 13,424,760 participants and 217,089 individuals with BD. Both fathers [adjusted for the age of other parent and socioeconomic status odd ratio - OR = 1.29(95%C.I. = 1.13-1.48)] and mothers aged ≤ 20 years [(OR = 1.23(95%C.I. = 1.14-1.33)] had consistently increased odds of BD diagnosis in their offspring compared to parents aged 25-29 years. Fathers aged ≥ 45 years [adjusted OR = 1.29 (95%C.I. = 1.15-1.46)] and mothers aged 35-39 years [OR = 1.10(95%C.I. = 1.01-1.19)] and 40 years or older [OR = 1.2(95% C.I. = 1.02-1.40)] likewise had inflated odds of BD diagnosis in their offspring compared to parents aged 25-29 years. Early and delayed parenthood are associated with an increased risk of BD in the offspring. Mechanisms underlying this association are largely unknown and may involve a complex interplay between psychosocial, genetic and biological factors, and with different impacts according to sex and age range. Evidence on the association between parental age and illness onset is still tentative but it points towards a possible specific effect of advanced paternal age on early BD-onset.

Predominant polarity (PP) is a concept used to define patients with bipolar disorder (BD) as presenting a tendency to manifest depressive (DPP) or manic (MPP) episodes. Still, the high percentage of patients with an undetermined PP (UPP), has been overlooked in most studies. Thus, we aimed to study UPP and outline its socio-demographic, clinical, and treatment-related features.Patients were recruited from a BD specialized unit. The sample was divided into three groups according to PP and socio-demographic and clinical variables were compared. Significant variables at univariate comparisons were included in multivariate logistic regression with UPP as the dependent variable.A total of 708 BD patients were included, of which 437 with UPP (61.7%). UPP was associated with a higher number of affective relapses, when compared with DPP or MPP (χ2= 28.704, p0.001). Mixed episodes (OR=1.398; CI=1.118-1.749), aggressive behaviour (OR=1.861; CI=1.190-2.913), seasonality (OR=2.025; CI= 1.289-3.501) and treatment with lamotrigine (OR= 2.101; CI=1.244-3.550) were significantly associated with UPP at the logistic regression.Recall bias may have occurred due to mixed episode diagnostic criteria change over the years. No data on the patients' follow-up has been reported on predominant polarity changes.UPP is associated with a higher number of relapses, and different clinical variables related to a severe course of illness. Considering PP in patients with BD may guide the choice for differential treatment approaches having an impact on BD course of illness and patients' prognosis and recovery.

Background: Cognitive profiles of BD patients show a demonstrated heterogeneity among young and middle-aged patients, but this issue has not yet deeply explored in Older Adults with bipolar disorder (OABD). The aim of the present study was to analyze cognitive variability in a sample of OABD. Methods: A total of 138 OABD patients and 73 healthy controls were included in this study. A comprehensive neuropsychological assessment was administered. We performed a k-means cluster analysis method based on the neurocognitive performance to detect heterogeneous subgroups. Demographic, clinical, cognitive and functional variables were compared. Finally, univariate logistic regressions were conducted to detect variables associated with the severity of the cognitive impairment. Results: We identified three distinct clusters based on the severity of cognitive impairment: (1) a preserved group (n = 58; 42%) with similar cognitive performance to HC, (2) a group showing mild cognitive deficits in all cognitive domains (n = 64; 46%) and, finally, (3) a group exhibiting severe cognitive impairment (n = 16; 12%). Older age, late onset, higher number of psychiatric admissions and lower psychosocial functioning were associated with the greatest cognitive impairment. Lower age, more years of education and higher estimated IQ were associated with a preserve cognitive functioning. Limitations: The small sample size of the severely impaired group. Conclusions: Cognitive heterogeneity remains at late-life bipolar disorder. Demographic and specific illness factors are related to cognitive dysfunction. Detecting distinct cognitive subgroups may have significant clinical implications for tailoring specific intervention strategies adapted to the level of the impairment and also to prevent cognitive decline.

Several pharmacogenetic-based decision support tools for psychoactive medication selection are available. However, the scientific evidence of the gene-drug pairs analyzed is mainly based on pharmacogenetic studies in patients with major depression or schizophrenia, and their clinical utility is mostly assessed in major depression. This study aimed at evaluating the impact of individual genes, with pharmacogenetic relevance in other psychiatric conditions, in the response to treatment in bipolar depression. Seventy-six patients diagnosed with bipolar disorder and an index major depressive episode were included in an observational retrospective study. Sociodemographic and clinical data were collected, and all patients were genotyped using a commercial multigene pharmacogenomic-based tool (Neuropharmagen®, AB-Biotics S.A., Barcelona, Spain). Multiple linear regression was used to identify pharmacogenetic and clinical predictors of efficacy and tolerability of medications. The pharmacogenetic variables response to serotonin-norepinephrine reuptake inhibitors (SNRIs) (ABCB1) and reduced metabolism of quetiapine (CYP3A4) predicted patient response to these medications, respectively. ABCB1 was also linked to the tolerability of SNRIs. An mTOR-related multigenic predictor was also associated with a lower number of adverse effects when including switch and autolytical ideation. Our results suggest that the predictors identified could be useful to guide the pharmacological treatment in bipolar disorder. Additional clinical studies are necessary to confirm these findings.

BACKGORUND Maintenance electroconvulsive therapy (mECT) is underused in the treatment of bipolar disorder (BD). We aimed to study the real-life effectiveness of mECT in BD. METHODS Naturalistic 3-year mirror-image study in individuals diagnosed with BD who underwent mECT at a tertiary hospital. Intra-subject comparisons of psychiatric hospitalization were performed using McNemar test. Days and number of psychiatric hospitalizations before and during mECT were compared through wilcoxon signed-rank test. Mean annual days and mean annual number of psychiatric hospitalizations per patient were compared by means of the rate ratio (RR) estimation through a generalized estimating equation (GEE) model. RESULTS A total of 43 patients were included and 37 required psychiatric hospitalization during the study. The use of mECT showed an effectiveness of 62.2% for preventing psychiatric hospitalizations (p

Background Despite an increasing number of available mental health apps in the bipolar disorder field, these tools remain scarcely implemented in everyday practice and are quickly discontinued by patients after downloading. The aim of this study is to explore adherence characteristics of bipolar disorder patients to dedicated smartphone interventions in research studies. Methods A systematic review following PRISMA guidelines was conducted. Three databases (EMBASE, PsychInfo and MEDLINE) were searched using the following keywords: "bipolar disorder" or "mood disorder" or “bipolar” combined with “digital” or “mobile” or “phone” or “smartphone” or “mHealth” or “ehealth” or "mobile health" or “app” or “mobile-health”. Results Thirteen articles remained in the review after exclusion criteria were applied. Of the 118 eligible studies, 39 did not provide adherence characteristics. Among the selected papers, study length, sample size and definition of measures of adherence were strongly heterogeneous. Activity rates ranged from 58 to 91.6%. Conclusion The adherence of bipolar patients to apps is understudied. Standardised measures of adherence should be defined and systematically evaluated in future studies dedicated to these tools.

Lithium remains the gold standard maintenance treatment for Bipolar Disorder (BD). However, weight gain is a side effect of increasing relevance due to its metabolic implications. We conducted a systematic review and meta-analysis aimed at summarizing evidence on the use of lithium and weight change in BD. We followed the PRISMA methodology, searching Pubmed, Scopus and Web of Science. From 1003 screened references, 20 studies were included in the systematic review and 9 included in the meta-analysis. In line with the studies included in the systematic review, the meta-analysis revealed that weight gain with lithium was not significant, noting a weight increase of 0.462 Kg (p = 0158). A shorter duration of treatment was significantly associated with more weight gain. Compared to placebo, there were no significant differences in weight gain. Weight gain was significantly lower with lithium than with active comparators. This work reveals a low impact of lithium on weight change, especially compared to some of the most widely used active comparators. Our results could impact clinical decisions.

Cel pracyLeki przeciwpadaczkowe (LPP), które są powszechnie stosowane w zapobieganiu nawrotom i leczeniu ostrych faz choroby afektywnej dwubiegunowej (ChAD) oraz zaburzeń schizoafektywnych (schizoaffective disorder, SAD), często wiążą się z działaniami niepożądanymi w czasie ciąży oraz z poważnymi wadami wrodzonymi (major congenital malformations, MCM). Celem niniejszej pracy było podsumowanie dostępnych badań oceniających skutki stosowania leków przeciwpadaczkowych u ciężarnych kobiet z ChAD i /lub SAD.MetodaPrzeszukano cztery bazy danych od początku do 18 stycznia 2019 roku. Do przeglądu włączono recenzowane badania obserwacyjne dotyczące stosowania LPP u ciężarnych kobiet z ChAD lub SAD. Wykluczono badania nieprzedstawiające danych dotyczących ChAD lub SAD, nie określające stosowanych LPP lub nie oceniające wyników ciąży lub poważnych wad wrodzonychWynikiŁączna ilość znalezionych badań wyniosła 2861. Po usunięciu zdublowanych badań i zastosowaniu kryteriów włączenia/wykluczenia do przeglądu włączono 9 badań obserwacyjnych oceniających pacjentki z ChAD i SAD. Badano następujące LPP: lamotrygina (LTG), kwas walproinowy (VPA), karbamazepina (CBZ), okskarbazepina (OXC), topiramat (TPR) i gabapentyna (GBP). Kwas walproinowy i karbamazepina były lekami przeciwpadaczkowymi, których stosowanie najczęściej wiązało się z poważnymi wadami wrodzonymi. Lamotrygina wykazywała najlepszy profil bezpieczeństwa. U leczonych i nieleczonych kobiet z ChAD obserwowano wyższe wskaźniki powikłań w czasie ciąży w porównaniu ze zdrowymi ciężarnymi.WnioskiStosowanie leków przeciwpadaczkowych w ciąży może mieć niekorzystne skutki oraz prowadzić do poważnych wad wrodzonych u dzieci kobiet z ChAD lub SAD, przy czym wyższe ryzyko występuje przy stosowaniu wyższych dawek. U tego typu pacjentek można rozważyć podawanie lamotryginy, biorąc pod uwagę niski poziom działań niepożądanych. W czasie ciąży należy unikać stosowania kwasu walproinowego i karbamazepiny.

Clinical and epidemiological research suggests that behavioral addictions (BA) are associated with a wide range of psychiatric disorders. However, the relationship between BA and bipolar disorders (BD) has not been thoroughly explored. The aim of this systematic review was to critically summarize and evaluate the current available evidence regarding a possible association between BA and BD. A systematic review of major electronic databases according to PRISMA guidelines was conducted from inception to 31st December 2017. We sought quantitative studies data concerning prevalence of comorbidity, features and treatment related to BA-BD comorbidity. Data were narratively synthesized. Of the 1250 studies returned from the search, a total of 28 articles were included in this review. BA may be overrepresented in BD samples, and the other way around. Pathological gambling and kleptomania were the most prevalent conditions followed by compulsive buying, compulsive sexual behavior and internet addiction. BA was also associated with other mood disorders, anxiety disorders and substance use disorder. BD-BA comorbidity was related with more severe course of illness. Studies on treatment strategies for BD–BA comorbidity are rather limited; only one randomized controlled trial that fulfilled inclusion criteria was identified. Methodological heterogeneity in terms of design and results among studies was found. BD-BA commonly co-occurs although there is a need for rigorous studies. Routine screening and adequate assessment may be helpful in BD patients to identify individuals at risk for BA and to effectively manage the complex consequences associated with BA-BD comorbidity.

Background The present systematic review was aimed at critically summarizing the evidence about interventions focused on circadian rhythms and mood symptoms in seasonal affective disorder (SAD). Methods A systematic search of the electronic databases PUBMED, PsycINFO and Web of Science was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Original papers reporting data about the effects of treatments on both mood and circadian rhythms disturbances in SAD patients were considered for inclusion. The quality of the evidence provided by the eligible studies was assessed using the Revised Cochrane Risk of Bias Tool (RoB 2.0) and the Cochrane Risk of Bias in Non-Randomized Studies of Interventions Tool (ROBINS-I). Results Forty papers were deemed eligible for the systematic review. The evidence of treatment outcomes referring to circadian disturbances was not robust. Despite this, bright light therapy (BLT) demonstrates to phase-advance delayed rhythms and to improve sleep-wake disorders. As for mood symptoms, both BLT and selective serotonin reuptake inhibitors (SSRIs) show evidence of efficacy. The possible connection between improvements of mood symptoms and changes in circadian outcomes seems controversial. Limitations The included studies presented considerable methodological heterogeneity, small sample sizes and non-optimal sample selection. Conclusions The effectiveness of BLT in depressive symptoms and circadian disturbances of SAD was outlined by the present systematic review. The evidence about other biological and pharmacological treatments, although promising, should be replicated. A multifactorial etiopathogenesis could explain the heterogeneous clinical presentations of SAD and the complex link between mood and circadian symptoms.

Background About 30–50% of Primary Care (PC) users in Spain suffer mental health problems, mostly mild to moderate anxious and depressive symptoms, which account for 2% of Spain's total Gross domestic product and 50% of the costs associated to all mental disorders. Mobile health tools have demonstrated to cost-effectively reduce anxious and depressive symptoms while machine learning (ML) techniques have shown to accurately detect severe cases. The main aim of this project is to develop a comprehensive ML digital support platform (PRESTO) to cost-effectively screen, assess, triage, and provide personalized treatments for anxious and depressive symptoms in PC. Methods The project will be carried out in 3 complementary phases: First, a ML predictive severity model will be built based on all the cases referred to the PC mental health support programme during the last 5 years in Catalonia. Simultaneously, a smartphone app to monitor and deliver psychological interventions for anxiety and depressive symptoms will be developed and tested in a clinical trial. Finally, the ML models and the app will be integrated in a comprehensive decision-support platform (PRESTO) which will triage and assign to each patient a specific intervention based on individual personal and clinical characteristics. The effectiveness of PRESTO to reduce waiting times in receiving mental healthcare will be tested in a stepped-wedge cluster randomized controlled trial in 5 PC centres. Discussion PRESTO will offer timely and personalized cost-effective mental health treatment to people with mild to moderate anxious and depressive symptoms. This will result in a reduction of the burden of mental health problems in PC and on society as a whole. Trial registration The project and their clinical trials were registered in Clinical Trials.gov: NCT04559360 (September 2020).

Background Despite an increasing number of smartphone apps, such therapeutic tools have not yet consistently demonstrated their efficacy and many suffer from low retention rates. To ensure the development of efficient apps associated with high adherence, we aimed to identify, through a user-centred design approach, patient and physician expectations of a hypothetical app dedicated to depression. Methods We conducted semi-structured interviews with physicians (psychiatrists and general practitioners) and patients who had experienced a major depressive episode during the last 12 months using the focus group method. The interviews were audio recorded, transcribed and analysed using qualitative content analysis to define codes, categories and emergent themes. Results A total of 26 physicians and 24 patients were included in the study. The focus groups showed balanced sex and age distributions. Most participants owned a smartphone (83.3% of patients, 96.1% of physicians) and were app users (79.2% of patients and 96.1% of physicians). The qualitative content analysis revealed 3 main themes: content, operating characteristics and barriers to the use of the app. Expected content included the data collected by the app, aiming to provide information about the patient, data provided by the app, gathering psychoeducation elements, therapeutic tools and functionalities to help with the management of daily life and features expected for this tool. The “operating characteristics” theme gathered aims considered for the app, its potential target users, considered modalities of use and considerations around its accessibility and security of use. Finally, barriers to the use of the app included concerns about potential app users, its accessibility, safety, side-effects, utility and functioning. All themes and categories were the same for patients and physicians. Conclusions Physician and patient expectations of a hypothetical smartphone app dedicated to depression are high and confirmed the important role it could play in depression care. The key points expected by the users for such a tool are an easy and intuitive use and a personalised content. They are also waiting for an app that gives information about depression, offers a self-monitoring functionality and helps them in case of emergency.

Bipolar disorders (BD) show highly prevalent rates of metabolic disturbances and obesity, with a two- to threefold increased risk for cardiovascular disease (CVD) and mortality compared with the general population. Metabolic syndrome (MetS) occurs in approximately 37.3% of BD patients and allows the risk assessment for metabolic complications. MetS worsens the course of BD, contributing to both poor treatment response and overall disability. BD and metabolic disturbances intertwine through common genetic susceptibility, shared neurobiological abnormalities, lifestyle-related psychopathological-behavioral features, and drug adverse effects. A comprehensive assessment of MetS in BD patients should be performed, with baseline and regular monitoring aimed at preventing long-term metabolic complications. When possible, treatment selection should consider the risk for MetS. The implementation of behavioral strategies is a first-line option for the management of MetS and should anticipate pharmacologic therapies. Adequate management of MetS may improve the clinical outcomes in patients with BD and prevent CVD.

Aggressive behavior (AB) represents a public health concern often associated with severe psychiatric disorders. Although most psychiatric patients are not aggressive, untreated psychiatric illness, including bipolar disorder (BD), may associate with an increased risk of AB. Accurate predictive models of AB are still lacking and it is crucial to delineate AB biomarkers state of the art in BD. We performed a systematic review according to PRISMA guidelines to identify biological correlates of AB in BD. Final results included 20 studies: 10 involving genetic and 10 other biological AB biomarkers (total sample size N = 5,181). Our results pointed to a serotoninergic hypoactivation in violent suicidal BD patients. Similarly, BD violent suicide attempters had a blunted hypothalamic-pituitary-adrenal (HPA) activity. Violent behavior in BD was associated with a chronic inflammatory state. While the role of lipids as biomarkers for AB remains equivocal, uric acid appears as a potential biomarker for hetero-AB in BD. Available data can be useful in the fulfill of specific biomarkers of AB in BD, ultimately leading to the development of accurate predictive models.