Uso de cariprazina en el trastorno bipolar: una revisión sistemática y aspectos prácticos / Use of cariprazine in bipolar disorder: A systematic review and practical considerations

Cariprazina es un antipsicótico de nueva generación que actúa como agonista parcial de los receptores de la dopamina D2 y D3, y de los receptores de serotonina 5HT1A. Actualmente, la cariprazina está aprobada por la Asociación Española del Medicamento para el tratamiento de la esquizofrenia, y por la Food and Drug Administration para el tratamiento de las fases maníacas, depresivas y mixtas asociadas al trastorno bipolar. La evidencia científica disponible, así como varias guías clínicas internacionales, acreditan la eficacia, seguridad y tolerabilidad de este fármaco y avalan su uso en cualquier tipo de episodio agudo del TB, con o sin síntomas mixtos. Los efectos adversos más frecuentes son los síntomas extrapiramidales, especialmente la acatisia. En dichos estudios se propone individualizar la dosis de cariprazina en función del tipo y la gravedad del episodio, así como de la tolerabilidad del paciente. Los estudios más recientes parecen indicar también un potencial beneficio para la prevención de recaídas en la fase de eutimia, y actualmente se están llevando a cabo ensayos clínicos para evaluar tanto este aspecto como el impacto del fármaco en la esfera cognitiva y en la funcionalidad de los pacientes. En conclusión, el uso de cariprazina en el TB está plenamente justificado desde un punto de vista científico, con unos beneficios globales que sobrepasan ampliamente el perfil de efectos adversos. (AU)

Cariprazine is a new generation antipsychotic that acts as a partial agonist of dopamine D2 and D3 receptors and serotonin 5HT1A receptors.Cariprazine has now been approved by the Spanish Medicines Association (Asociación Española del Medicamento (AEM)) for the treatment of schizophrenia, and by the Food and Drug Administration (FDA) for the treatment of the manic, depressive, and mixed states associated with bipolar disorder (BD). The available scientific evidence, and several international guidelines attest to the efficacy, safety, and tolerability of this drug and endorse its use in any type of acute BD episode, with or without mixed symptoms.The most frequent adverse effects are extrapyramidal symptoms, especially akithisia. Studies propose individualising the dose of cariprazine to the type and severity of the episode, and the patient’s tolerability. The most recent studies also seem to indicate a potential benefit in the prevention of relapse in the euthymia phase, and clinical trials are currently underway to evaluate this and the impact of the drug on patients’ cognitive sphere and functionality. To conclude, the use of cariprazine in bipolar disorder is fully justified from a scientific perspective, with overall benefits that far outweigh the adverse effects profile. (AU)

Lithium therapy and weight change in people with bipolar disorder: A systematic review and meta-analysis.

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.

Biased accuracy in multisite machine-learning studies due to incomplete removal of the effects of the site.

Brain MRI researchers conducting multisite studies, such as within the ENIGMA Consortium, are very aware of the importance of controlling the effects of the site (EoS) in the statistical analysis. Conversely, authors of the novel machine-learning MRI studies may remove the EoS when training the machine-learning models but not control them when estimating the models' accuracy, potentially leading to severely biased estimates. We show examples from a toy simulation study and real MRI data in which we remove the EoS from both the "training set" and the "test set" during the training and application of the model. However, the accuracy is still inflated (or occasionally shrunk) unless we further control the EoS during the estimation of the accuracy. We also provide several methods for controlling the EoS during the estimation of the accuracy, and a simple R package ("multisite.accuracy") that smoothly does this task for several accuracy estimates (e.g., sensitivity/specificity, area under the curve, correlation, hazard ratio, etc.).

Psychiatric Clinical Profiles and Pharmacological Interactions in COVID-19 Inpatients Referred to a Consultation Liaison Psychiatry Unit: a Cross-Sectional Study.

The Coronavirus Disease 2019 (COVID-19) can affect mental health in different ways. There is little research about psychiatric complications in hospitalized patients with COVID-19. The aim of the study was to describe the psychiatric clinical profile and pharmacological interactions in COVID-19 inpatients referred to a Consultation-Liaison Psychiatry (CLP) unit. This is a cross-sectional study, carried out at a tertiary hospital in Spain, in inpatients admitted because of COVID-19 and referred to our CLP Unit from March 17,2020 to April 28,2020. Clinical data were extracted from electronic medical records. The patients were divided in three groups depending on psychiatric diagnosis: delirium, severe mental illness (SMI) and non-severe mental illness (NSMI). Of 71 patients included (median [ICR] age 64 [54-73] years; 70.4% male), 35.2% had a delirium, 18.3% had a SMI, and 46.5% had a NSMI. Compared to patients with delirium and NSMI, patients with SMI were younger, more likely to be institutionalized and were administered less anti-COVID19 drugs. Mortality was higher among patients with delirium (21.7%) than those with SMI (0%) or NSMI (9.45%). The rate of side effects due to interactions between anti-COVID19 and psychiatric drugs was low, mainly drowsiness (4.3%) and borderline QTc prolongation (1.5%). Patients affected by SMI were more often undertreated for COVID-19. However, the rate of interactions was very low, and avoidable with a proper evaluation and drug-dose adjustment. Half of the patients with SMI were institutionalized, suggesting that living conditions in residential facilities could make them more vulnerable to infection.

Mixed Features in Depression: The Unmet Needs of Diagnostic and Statistical Manual of Mental Disorders Fifth Edition.

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.

mHealth in affective disorders: hype or hope? A focused narrative review.

The constant growth and widespread availability of mobile technologies (i.e. smartphones and wearables) over the last decades have been a subject of intense interest and research in the affective disorders (AD) field. The potential of mHealth for collecting a new kind of passive and active information while providing cost-effective and tailored interventions have raised many hopes. However, until now, despite some encouraging results, research in the field has not been translated to reach real-world clinical settings or to develop additional evidence-based mHealth tools for people suffering from AD. Meanwhile, commercial untested apps and wearables are already being increasingly used and adopted by patients for the self-management of their illnesses. Hence, there is a latent need and demand from service users to integrate mHealth in their care, which the field cannot yet fulfil. In this article, through a focused narrative review, we discuss the evidence available for the use, validity and efficacy of mHealth tools in AD. Challenges in the academic field hampering the advancement of these technologies and its implementation into clinical practice are discussed. Lastly, we propose a framework to overcome these issues, which may facilitate mHealth solutions reaching service users.