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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.

Objectives Clinical staging is widely used in medicine to map disease progression, inform prognosis and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well-defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking. Methods Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders. Results Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at-risk status and subthresholdhold stages, and to various clinical stages of BD as it is currently diagnosed. Conclusion The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light.

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.

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.

Background: Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are frequently comorbid. Aims: To assess the effectiveness of vortioxetine in patients with MDD and comorbid GAD. Methods: Open-label, 8-week study (NCT04220996) in 100 adult outpatients with severe MDD and severe comorbid GAD receiving vortioxetine as first treatment for the current depressive episode or switching to vortioxetine due to inadequate response to another drug for depression. Vortioxetine starting dosage was 10 mg/day, with forced up-titration to 20 mg/day after 1 week. Response was defined as ⩾50% decrease in Montgomery–Åsberg Depression Rating Scale (MADRS) and/or Hamilton Anxiety Rating Scale (HAM-A) total score from baseline; remission defined as MADRS and/or HAM-A total score ⩽10. Results: Clinically meaningful and statistically significant improvements from baseline in symptoms of depression and anxiety, and overall functioning and health-related quality of life, were observed after 8 weeks’ vortioxetine treatment (all changes p Conclusion: Vortioxetine demonstrates effectiveness in significantly reducing symptoms of both depression and anxiety in patients with severe MDD comorbid with severe GAD. Findings support increasing vortioxetine dosage to 20 mg/day early in the course of therapy, and show that this may be achieved without compromising tolerability.

Substance use disorder (SUD) is a common comorbidity in individuals with bipolar disorder (BD), and it is associated with a severe course of illness, making early identification of the risk factors for SUD in BD warranted. We aimed to identify, through machine-learning models, the factors associated with different types of SUD in BD. We recruited 508 individuals with BD from a specialized unit. Lifetime SUDs were defined according to the DSM criteria. Random forest (RF) models were trained to identify the presence of (i) any (SUD) in the total sample, (ii) alcohol use disorder (AUD) in the total sample, (iii) AUD co-occurrence with at least another SUD in the total sample (AUD+SUD), and (iv) any other SUD among BD patients with AUD. Relevant variables selected by the RFs were considered as independent variables in multiple logistic regressions to predict SUDs, adjusting for relevant covariates. AUD+SUD could be predicted in BD at an individual level with a sensitivity of 75% and a specificity of 75%. The presence of AUD+SUD was positively associated with having hypomania as the first affective episode (OR = 4.34 95% CI = 1.42–13.31), and the presence of hetero-aggressive behavior (OR = 3.15 95% CI = 1.48–6.74). Machine-learning models might be useful instruments to predict the risk of SUD in BD, but their efficacy is limited when considering socio-demographic or clinical factors alone.

This article reviews the most common non-psychiatric comorbidities associated with affective disorders, examining the implications of their possible bidirectional link. A narrative review was conducted on the association among the three most common non-psychiatric diseases in major depressive disorder and bipolar disorder (obesity, metabolic syndrome, and cardiovascular diseases) in articles published from January 1994 to April 2020. The evidence suggests that obesity, metabolic syndrome, and cardiovascular diseases are highly prevalent in patients diagnosed with affective disorders. The presence of non-psychiatric comorbidities significantly worsens the therapeutic management and prognosis of affective disorders and vice versa. In many cases, these comorbidities may precede the onset of affective disorders, although in most cases they appear after it. The presence of these concurrent non-psychiatric diseases in an individual diagnosed with an affective disorder is associated with a more complex disease presentation and management. For professionals, the evidence unequivocally supports routine surveillance of comorbidities from a multidisciplinary approach.

Resumen: Introducción: La comorbilidad médica en pacientes con trastornos del estado de ánimo tiende a convertirse en un problema de salud pública clínica y global cada vez más importante. Varias patologías médicas específicas están asociadas con un mayor riesgo de padecer trastornos del estado de ánimo y, por otra parte, los trastornos del estado de ánimo están asociados con un aumento de la morbilidad y mortalidad debidas a condiciones médicas comórbidas. En este artículo se revisan las comorbilidades médicas que más comúnmente se asocian a los trastornos afectivos (enfermedades cardiovasculares, obesidad y síndrome metabólico) examinando sus posibles implicaciones bidireccionales. Métodos: Se ha realizado una revisión no sistemática y búsqueda de la literatura científica sobre la asociación entre las tres enfermedades médicas más frecuentes en trastorno depresivo mayor y trastorno bipolar (enfermedades cardiovasculares, obesidad, síndrome metabólico) entre enero de 1995 y noviembre de 2019. Resultados: La evidencia sugiere que la comorbilidad entre estas tres enfermedades médicas y los trastornos del estado de ánimo es muy frecuente; la presencia de las primeras empeora significativamente el pronóstico y el manejo terapéutico de las segundas y viceversa, comparten mecanismos fisiopatológicos e implican una etiología aparentemente bidireccional. Conclusiones: La presencia de estas enfermedades médicas concurrentes en un individuo con un trastorno del estado de ánimo se asocia con una presentación de enfermedad más compleja. En muchos casos, estas comorbilidades pueden preceder a la aparición de los trastornos del estado de ánimo, aunque en la mayoría de los casos parecen seguir a la aparición de los trastornos del estado de ánimo. Para los profesionales, la evidencia apoya inequívocamente las recomendaciones para la vigilancia rutinaria de las comorbilidades según un enfoque multidisciplinar. Summary: Introduction: Medical comorbidity in patients with mood disorders tends to become an increasingly important clinical and global public health problem. On one hand, several specific medical pathologies are associated with an increased risk of mood disorders and on the other hand, mood disorders are associated with increased morbidity and mortality due to comorbid medical conditions. This article reviews the medical comorbidities that are most commonly associated with affective disorders (cardiovascular diseases, obesity and metabolic syndrome) examining their possible bidirectional implications. Methods: A non-systematic review about the association between the three most common medical diseases in major depressive disorder and bipolar affective disorder (cardiovascular diseases, obesity, metabolic syndrome) has been carried out from January 1995 to November 2019. Results: The evidence suggests that comorbidity between these three medical diseases and mood disorders is very prevalent. The presence of medical disease significantly worsens the prognosis and therapeutic management of the mood disorders and vice versa. In many cases, these comorbidities may precede the onset of mood disorders, although in most cases they appear to follow the onset of mood disorders. Conclusions: The presence of these concurrent medical diseases in an individual with a mood disorder is associated with a more complex disease presentation. For professionals, the evidence unequivocally supports recommendations for routine surveillance of comorbidities according to a multidisciplinary approach. Palabras clave: Trastorno bipolar, Trastorno depresivo mayor, Comorbilidad médica, Enfermedad cardiovascular, Obesidad, Síndrome metabólico, Keywords: Bipolar disorder, Major depressive disorder, Comorbidities, cardiovascular disease, Obesity, Metabolic syndrome

Jessica Madera,1 Pedro Such,2 Peter Zhang,1 Ross A Baker,1 Iria Grande31Medical Affairs, Otsuka Pharmaceutical Development and Commercialization Inc, Princeton, NJ, USA; 2Medical Affairs, H. Lundbeck A/S, Valby, Denmark; 3Bipolar and Depression Disorders Unit, Hospital Clinic, Institute of Neurosciences, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, SpainPurpose: There is growing agreement that definitions of “recovery” in bipolar-I disorder (BP-I) should include functional outcomes beyond sustained symptomatic remission. In this post-hoc analysis, we assessed functional recovery rates according to the validated Functioning Assessment Short Test (FAST) in participants with BP-I after 52 weeks of maintenance treatment with aripiprazole once monthly (AOM).Patients and methods: Rates of functional recovery with AOM 400 were investigated in two 52-week studies. NCT01567527 was a placebo-controlled, double-blind, randomized-withdrawal study and NCT01710709 was an open-label study. Functional recovery, assessed at the end of the respective maintenance phases, was defined as a total FAST score of ≤11 for 8 consecutive weeks.Results: Post-hoc analyses included 229 patients from the randomized-withdrawal study (AOM 400 n=116; placebo n=113). The open-label study included 402 patients (including 321 de novo patients and 81 rollover patients who had completed the randomized-withdrawal study). In the randomized-withdrawal study, functional recovery was achieved by 30.2% (n=35) of the AOM 400 group compared with 24.8% (n=28) in the placebo group. The difference was not statistically significant (p=0.39). In the open-label study, 36% (n=116) of de novo patients and 43% (n=35) of rollover patients had functionally recovered after 52 weeks of AOM 400 treatment.Conclusion: These data highlight the utility of a sustained FAST total score of ≤11 as a definition of recovery and emphasize the possibility of achieving this ambitious treatment goal with effective long-term treatment.Keywords: bipolar disorder, aripiprazole, long-acting injectable, maintenance, functioning, recovery

Resumen Introduccion La asistencia en salud mental (SM) presenta importantes retos, especialmente en el campo de la humanizacion. Los objetivos fueron identificar las medidas de humanizacion en los planes de SM de las comunidades autonomas (CC. AA.) espanolas y las prioridades a desarrollar en este ambito. Material y metodos Un grupo amplio y multidisciplinar de personas implicadas en la asistencia en SM participo en un consenso, segun un metodo Delphi modificado, basado en el «pensamiento de diseno», en 3 fases: 1) identificacion de medidas de humanizacion en los planes de SM de las CC. AA.; 2) analisis de la implantacion de estas medidas, y 3) identificacion de prioridades de humanizacion en SM. Resultados De las 17 CC. AA., 14 tienen planes de SM vigentes. Se identificaron 4 tipos de medidas de humanizacion: 1) mejora de la calidad de la atencion; 2) promocion de la participacion de usuarios; 3) lucha contra el estigma y la discriminacion, y 4) cuidado de personas especialmente vulnerables. El rango de implantacion de las medidas fue del 6,3% (p. ej., presupuesto especifico) al 100%, con promedio del 64,1%. Se identificaron aspectos prioritarios, operativizados en 5 propuestas: 1) campana de difusion; 2) foros multidisciplinares de encuentro; 3) plataforma de entidades de apoyo; 4) estrategia de educacion en SM, y 5) humanizacion en planes de estudios. Conclusiones Los planes de SM incluyen la humanizacion entre sus objetivos, pero de forma parcial. La implementacion de propuestas de humanizacion como las identificadas resulta imprescindible para lograr una atencion a la SM de calidad.

Objective The period immediately after the onset of first-episode psychosis (FEP) may present with high risk for suicidal ideation (SI) and attempts, although this risk may differ among patients. Thus, we aimed to identify trajectories of SI in a 2-years follow-up FEP cohort and to assess baseline predictors and clinical/functional evolution for each trajectory of SI. Methods We included 334 FEP participants with data on SI. Growth mixture modeling was used to identify trajectories of SI. Putative sociodemographic, clinical, and cognitive predictors of the distinct trajectories were examined using multinomial logistic regression. Results We identified three distinct trajectories: Non-SI trajectory (85.53% sample), Improving SI trajectory (9.58%), and Worsening SI trajectory (6.89%). Multinomial logistic regression model revealed that greater baseline pessimistic thoughts, anhedonia, and worse perceived family environment were associated with higher baseline SI followed by an Improving trajectory. Older age, longer duration of untreated psychosis, and reduced sleep predicted Worsening SI trajectory. Regarding clinical/functional evolution, individuals within the Improving SI trajectory displayed moderate depression at baseline which ameliorated during the study period, while the Worsening SI subgroup exhibited persistent mild depressive symptoms and greater functional impairment at follow-up assessments. Conclusion Our findings delineated three distinct trajectories of SI among participants with FEP, one experiencing no SI, another in which SI might depend on acute depressive symptomatology, and a last subset where SI might be associated with mild but persistent clinical and functional impairments. These data provide insights for the early identification and tailored treatment of suicide in this at-risk population.

In the last few years, researchers are going beyond the conventional theories behind neuropsychiatric diseases, and the role of neuroinflammation is being increasingly recognized. It is known that microbiota plays a key role on human health and that there is a reciprocal communication between brain and gut. Also, it has been proved that altered microbiota can lead to systemic and central inflammation by several ways. For all these reasons, it has been hypothesized that alterations in the gut microbiota and the subsequent malfunction of the microbiota-gut-brain axis (MGBA) may be involved in the pathogenesis of various neuropsychiatric diseases including bipolar disorder. In this chapter, we aim to (1) summarize the different mechanisms by which the gut microbiota may modulate brain functions, (2) expose the consequences of leaky gut and dysbiosis, (3) illustrate the impact of MGBA in bipolar disorder patients and their relatives, and (4) present future therapeutic approaches targeting this axis.

Introduction Suicide is one of the leading causes of avoidable death. Gathering national data on suicidal behaviour incidence is crucial to develop evidence-based public policies. The study has two primary objectives: (1) to determine the incidence of suicide attempts in Spain and related risk factors, and (2) to analyze the efficacy of secondary prevention programmes to prevent suicide re-attempting in comparison to treatment as usual (TAU). Materials and methods Multisite, coordinated, cohort study with three nested randomized controlled trials. A cohort of 2000 individuals (age >=12) with suicidal behaviour will be recruited at ten sites distributed across Spain. Assessments will be conducted within 10 days of the suicide attempt (V0-baseline visit) and after 12 months (V4-last visit) and will include clinician reported and participant reported outcomes (PROs). Between V0 and V4, PROs will be collected remotely every three months (V1, V2 and V3). Optatively, cohort participants will participate in three nested randomized-controlled-trials (RCTs) evaluating different secondary prevention interventions: Participants aged 18 years and older will be randomly allocated to: Telephone-based Management + TAU vs. TAU or iFightDepression-Survive + TAU vs. TAU. Participants aged between 12 and 18 years will be allocated to a specific intervention for youths: Self Awareness of Mental Health + TAU vs. TAU. Results This study will provide interesting data to estimate suicide attempt incidence in Spain. and will provide evidence on three. Conclusions Evidence on three potentially efficacious interventions for individuals at high risk of suicide will be obtained, and this could improve the treatment given to these individuals. Trial registration NCT04343703

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.

Bipolar disorder is a recurrent disorder that affects more than 1% of the world population and usually has its onset during youth. Its chronic course is associated with high rates of morbidity and mortality, making bipolar disorder one of the main causes of disability among young and working-age people. The implementation of early intervention strategies may help to change the outcome of the illness and avert potentially irreversible harm to patients with bipolar disorder, as early phases may be more responsive to treatment and may need less aggressive therapies. Early intervention in bipolar disorder is gaining momentum. Current evidence emerging from longitudinal studies indicates that parental early-onset bipolar disorder is the most consistent risk factor for bipolar disorder. Longitudinal studies also indicate that a full-blown manic episode is often preceded by a variety of prodromal symptoms, particularly subsyndromal manic symptoms, therefore supporting the existence of an at-risk state in bipolar disorder that could be targeted through early intervention. There are also identifiable risk factors that influence the course of bipolar disorder, some of them potentially modifiable. Valid biomarkers or diagnosis tools to help clinicians identify individuals at high risk of conversion to bipolar disorder are still lacking, although there are some promising early results. Pending more solid evidence on the best treatment strategy in early phases of bipolar disorder, physicians should carefully weigh the risks and benefits of each intervention. Further studies will provide the evidence needed to finish shaping the concept of early intervention. AJP AT 175 Remembering Our Past As We Envision Our Future April 1925: Interpretations of Manic-Depressive Phases Earl Bond and G.E. Partridge reviewed a number of patients with manic-depressive illness in search of a unifying endo-psychic conflict. They concluded that understanding either phase of illness was "elusive" and "tantalizing beyond reach." (Am J Psychiatry 1925: 81: 643-662 ).

Major Depressive Disorder (MDD) is a serious psychiatric condition. Its treatment remains a challenge nowadays. Vortioxetine is a novel antidepressant with a unique profile, as it acts as a multimodal serotoninergic agent. Its efficacy in MDD has been established in many short- and long-term studies, with 7 positive, 4 negative and 1 failed randomized controlled trials. Moreover, its ability to modulate a wide range of neurotransmitters (serotonin, dopamine, norepinephrine, histamine, glutamate or GABA) confers vortioxetine pro-cognitive effects. Side effects are also different from conventional antidepressants, according to its low incidence of sexual dysfunction, weight gain or cardiovascular alterations. The aim of this systematic review is to describe the pharmacology, clinical efficacy and safety profile of vortioxetine, as well as its potential effectiveness in improving cognitive symptoms.

Resumen El trastorno depresivo mayor (TDM) es una enfermedad psiquiatrica grave cuyo tratamiento sigue siendo un reto en la actualidad. Vortioxetina es un nuevo farmaco antidepresivo con accion multimodal, lo que le confiere un perfil unico. Su efectividad antidepresiva ha sido demostrada en varios estudios a corto y largo plazo, con 7 estudios aleatorizados positivos, 4 negativos y uno nulo. Ademas, su capacidad para modular varios neurotransmisores (serotonina, dopamina, noradrenalina, histamina, glutamato y GABA) le permite actuar sobre dominios como la cognicion. Su perfil de efectos adversos es tambien distinto al de otros antidepresivos convencionales, dado que se relaciona con una baja incidencia de disfuncion sexual, aumento de peso o alteraciones cardiovasculares. En esta revision sistematica se describiran las caracteristicas farmacologicas de vortioxetina y se detallara la evidencia disponible respecto a su eficacia clinica, su tolerabilidad y su prometedor efecto sobre los sintomas cognitivos.

Background Cognitive symptoms in Major Depressive Disorder (MDD) are persistent and commonly entail neurocognitive impairment and a decline in quality of life. This systematic review gathers the current scientific evidence on therapeutic strategies for neuropsychological impairment in MDD. Method A systematic search on PubMed, PsycINFO and Clinicaltrials.gov was carried out on December 2016 according to PRISMA using Boolean terms to identify interventions for the treatment of cognitive dysfunction in MDD. Only English-written articles providing original data and focusing in adults with MDD were included with no time restrictions. Results A total of 95 studies reporting data on 40 pharmacological and non-pharmacological interventions were included. Interventions were grouped into the following categories: 1) Pharmacological Therapies (antidepressants, stimulants, compounds acting on NMDA receptors, compounds acting on the cholinergic system, compounds showing anti-inflammatory or antioxidant properties, other mechanisms of action), 2) Physical Therapies and 3) Psychological Therapies, 4) Exercise. There are some promising compounds showing a positive impact on cognitive symptoms including vortioxetine, lisdexamfetamine or erythropoietin. Limitations The studies included showed significant methodological differences in heterogeneous samples. The lack of a standardized neuropsychological battery makes comparisons between studies difficult. Conclusion Current evidence is not sufficient to widely recommend the use of procognitive treatments in MDD although promising results are coming to light.

Over the last decade, there has been a growing appreciation of the importance of identifying and treating cognitive impairment associated with bipolar disorder, since it persists in remission periods. Evidence indicates that neurocognitive dysfunction may significantly influence patients’ psychosocial outcomes. An ever-increasing body of research seeks to achieve a better understanding of potential moderators contributing to cognitive impairment in bipolar disorder in order to develop prevention strategies and effective treatments. This review provides an overview of the available data from studies examining treatments for cognitive dysfunction in bipolar disorder as well as potential novel treatments, from both pharmacological and psychological perspectives. All these data encourage the development of further studies to find effective strategies to prevent and treat cognitive impairment associated with bipolar disorder. These efforts may ultimately lead to an improvement of psychosocial functioning in these patients.

Introduction: Early recognition of bipolar disorder improves the prognosis and decreases the burden of the disease. However, there is a significant delay in diagnosis. Multiple risk factors for bipolar disorder have been identified and a population at high-risk for the disorder has been more precisely defined. These advances have allowed the development of risk calculators to predict individual risk of conversion to bipolar disorder. This review aims to identify the risk calculators for bipolar disorder and assess their clinical applicability. Methods: A systematic review of original studies on the development of risk calculators in bipolar disorder was performed. The studies' quality was evaluated with the Newcastle-Ottawa Quality Assessment Form for Cohort Studies and according to recommendations of the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis Initiative. Results: Three studies met the inclusion criteria; one developed a risk calculator of conversion from major depressive episode to bipolar disorder; one of conversion to new-onset bipolar spectrum disorders in offspring of parents with bipolar disorder; and the last one of conversion in youths with bipolar disorder not-otherwise-specified. Conclusions: The calculators reviewed in this article present good discrimination power for bipolar disorder, although future replication and validation of the models is needed. info:eu-repo/semantics/publishedVersion