Electroconvulsive therapy in a 12-year-old boy with a severe depression

Electroconvulsive therapy (ect) is an uncommon treatment in children and adolescents. This could partially be explained by the fact that a large proportion of the (child and adolescent) psychiatrists have little knowledge on ect in youths. We describe a case of a 12-year-old boy with a severe depression refractory to pharmacotherapy and psychotherapy, in which ect treatment was successful, including six years follow-up. Additionally, this report represents the state of the art concerning the efficacy and safety of ect in youths.</p

Increased prevalence of metabolic syndrome in patients with bipolar disorder compared to a selected control group-a Northern Netherlands LifeLines population cohort study

OBJECTIVES: Metabolic syndrome (MetS) is highly prevalent among patients with bipolar disorder (BD). The aims of this cross-sectional study were to determine the prevalence of MetS in Dutch BD subjects and compare it with a control group, to examine the association of demographic and clinical characteristics with MetS in BD, and to determine the extent to which metabolic dysregulation is treated in those patients. METHODS: 493 Dutch adult patients (≥ 18 years) with BD receiving psychotropic drugs and 493 matched control subjects were compared using data from the biobank Lifelines. We determined MetS according to the National Cholesterol Education Program Adult Treatment Panel III-Adapted (NCEP ATP III-A) criteria. The difference in the prevalence of MetS and the associations with characteristics were analyzed with logistic regression. RESULTS: BD subjects (30.6%) showed a significantly higher prevalence of MetS compared to the control group (14.2%) (p < .001, OR:2.67, 95% CI:1.94-3.66). Univariate analysis showed that smoking, body mass index (BMI) and antidepressant drug use were associated with MetS. Multivariate analysis showed that smoking (OR:2.01) was independently associated with MetS in BD. For hypertension, hyperglycemia and lipid disorder pharmacological treatment was provided to respectively 69.5%, 24% and 18.4% of the BD subjects in our sample. LIMITATIONS: Duration of illness of BD subjects was unknown. CONCLUSIONS: This study demonstrated a higher prevalence of MetS in Dutch BD subjects compared to persons without BD. In addition, a remarkable undertreatment of some of the components of MetS was found

Chronotype changes with age; seven-year follow-up from the Netherlands study of depression and anxiety cohort

Background: Chronotype reflects an individual's optimal daily timing of sleep, activity, and cognitive performance. Previous, cross-sectional, studies have suggested an age effect on chronotype with later chronotypes in adolescents and earlier chronotypes in children and elderly. Additionally, later chronotypes have been associated with more depressive symptoms. Few studies have been able to study longitudinal associations between chronotype and age, while adjusting for depressive symptoms. Methods: Chronotype was assessed twice with the Munich Chronotype Questionnaire 7 years apart in the Netherlands Study of Depression and Anxiety (T1: N = 1842, mean age (SD): 42.63 years (12.66)) and T2: N = 1829, mean age (SD) 50.67 (13.11)). The longitudinal association between change in age and change in chronotype was tested using a generalized estimated equation analysis adjusted for covariates (including level of depressive symptoms). Using age-bins of 5 years (age at T2), change in chronotype between T1 and T2 was analyzed with Linear Mixed Models. Results: We found a change towards an earlier chronotype with higher age (B (95% CI): -0.011 (-0.014-0.008), p < 0.001). For the age-bins, the difference in chronotype was significant for the 25-29 years age-bin. Limitations: The sample did not include individuals younger than 19 years or older than 68 years. Conclusions: In the whole sample chronotype changed towards becoming more morning-type over a period of 7 years, but this change was only significant for those aged 25-29 years. The study was performed in a large naturalistic cohort study with a wide age-range, including patients with a diagnosis of depressive and anxiety disorder and healthy controls.Stress and Psychopatholog

Towards precision medicine:What are the stratification hypotheses to identify homogeneous inflammatory subgroups

Diverse lines of research testify a link, presumably causal, between immune dysregulation and the development, course and clinical outcome of psychiatric disorders. However, there is a large heterogeneity among the patients? individual immune profile and this heterogeneity prevents the development of precise diagnostic tools and the identification of therapeutic targets. The aim of this review was to delineate possible subgroups of patients on the basis of clinical dimensions, investigating whether they could lead to particular immune signatures and tailored treatments. We discuss six clinical entry points; genetic liability to immune dysregula-tion, childhood maltreatment, metabolic syndrome, cognitive dysfunction, negative symptoms and treatment resistance. We describe the associated immune signature and outline the effects of anti-inflammatory drugs so far. Finally, we discuss advantages of this approach, challenges and future research directions. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/

Aspirin for recurrence prevention in bipolar disorder-Promising, yet clinically understudied?

Current available maintenance pharmacotherapy for bipolar disorder (BD) leaves ample room for improvement. Up to 50% of patients with BD do not respond adequately to available treatments and still suffer from manic and/or depressive episodes. In this perspective article, we will give an overview of the neuropharmacodynamics of (low-dose) aspirin, reflect on the published clinical studies and argue that aspirin is a promising, yet understudied option for recurrence prevention This article is protected by copyright. All rights reserved

Clinical efficacy and satisfaction of a digital wheeze detector in a multicentre randomised controlled trial: the WheezeScan study.

INTRODUCTION: Wheezing is common in preschool children and its clinical assessment often challenging for caretakers. This study aims to evaluate the impact of a novel digital wheeze detector (WheezeScan™) on disease control in a home care setting. METHODS: A multicentre randomised open-label controlled trial was conducted in Berlin, Istanbul and London. Participants aged 4-84 months with a doctor's diagnosis of recurrent wheezing in the past 12 months were included. While the control group followed usual care, the intervention group received the WheezeScan™ for at-home use for 120 days. Parents completed questionnaires regarding their child's respiratory symptoms, disease-related and parental quality of life, and caretaker self-efficacy at baseline (T0), 90 days (T1) and 4 months (T2). RESULTS: A total of 167 children, with a mean±sd age of 3.2±1.6 years, were enrolled in the study (intervention group n=87; control group n=80). There was no statistically significant difference in wheeze control assessed by TRACK (mean difference 3.8, 95% CI -2.3-9.9; p=0.2) at T1 between treatment groups (primary outcome). Children's and parental quality of life and parental self-efficacy were comparable between both groups at T1. The evaluation of device usability and perception showed that parents found it useful. CONCLUSION: In the current study population, the wheeze detector did not show significant impact on the home management of preschool wheezing. Hence, further research is needed to better understand how the perception and usage behaviour may influence the clinical impact of a digital support

Machine learning and big data analytics in bipolar disorder:A position paper from the International Society for Bipolar Disorders Big Data Task Force

Objectives The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD. Method A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD. Results The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding. Conclusion Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings.Peer reviewe