Advancing treatment response prediction in first-episode psychosis: integrating clinical and electroencephalography features.

Aims: Prompt diagnosis and intervention are crucial for first-episode psychosis (FEP) outcomes, but predicting the response to antipsychotics remains challenging. We studied whether adding electroencephalography (EEG) characteristics improves clinical prediction models for treatment response and whether EEG-based predictors are influenced by initial treatment.

Methods: We included 115 antipsychotic-naïve patients with FEP.

DELirium treatment with Transcranial Electrical Stimulation (DELTES): study protocol for a multicentre, randomised, double-blind, sham-controlled trial.

Introduction: Delirium, a clinical manifestation of acute encephalopathy, is associated with extended hospitalisation, long-term cognitive dysfunction, increased mortality and high healthcare costs. Despite intensive research, there is still no targeted treatment. Delirium is characterised by electroencephalography (EEG) slowing, increased relative delta power and decreased functional connectivity.

A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC).

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures).

Forward head posture associated with reduced cardiorespiratory fitness in psychotic disorders compared to autism spectrum disorder and healthy controls.

Individuals with psychotic disorders often lead sedentary lives, heightening the risk of developing forward head posture. Forward head posture affects upper cervical vertebrae, raising the likelihood of daily discomforts like skeletal misalignment, neck pain, and reduced cardiorespiratory fitness. Improving cardiorespiratory fitness in psychotic disorders is relevant, given its proven benefits in enhancing physical and mental health.

Precision psychiatry: predicting predictability.

Precision psychiatry is an emerging field that aims to provide individualized approaches to mental health care. An important strategy to achieve this precision is to reduce uncertainty about prognosis and treatment response. Multivariate analysis and machine learning are used to create outcome prediction models based on clinical data such as demographics, symptom assessments, genetic information, and brain imaging.

Pre-treatment predictors of cognitive side-effects after treatment with electroconvulsive therapy in patients with depression: A multicenter study.

Background: Electroconvulsive therapy (ECT) is a highly effective treatment for major depressive episodes (MDE). However, ECT-induced cognitive side-effects remain a concern. Identification of pre-treatment predictors that contribute to these side-effects remain unclear.

Associations between psychotropic drugs and rsEEG connectivity and network characteristics: a cross-sectional study in hospital-admitted psychiatric patients.

Introduction: Resting-state EEG (rsEEG) characteristics, such as functional connectivity and network topology, are studied as potential biomarkers in psychiatric research. However, the presence of psychopharmacological treatment in study participants poses a potential confounding factor in biomarker research. To address this concern, our study aims to explore the impact of both single and multi-class psychotropic treatments on aforementioned rsEEG characteristics in a psychiatric population.

Mental, cognitive and physical outcomes after intensive care unit treatment during the COVID-19 pandemic: a comparison between COVID-19 and non-COVID-19 patients.

To compare mental, cognitive and physical outcomes between COVID-19 and non-COVID-19 patients, 3-6 months after Intensive Care Unit (ICU) treatment during the COVID-19 pandemic and to compare mental outcomes between relatives of these patients. This retrospective cohort study included 209 ICU survivors (141 COVID-19 patients and 68 non-COVID-19 patients) and 168 of their relatives (maximum one per patient) during the COVID-19 pandemic. Primary outcomes were self-reported occurrence of mental, cognitive and/or physical symptoms 3-6 months after ICU discharge.

Advancing specificity in delirium: The delirium subtyping initiative.

Background: Delirium, a common syndrome with heterogeneous etiologies and clinical presentations, is associated with poor long-term outcomes. Recording and analyzing all delirium equally could be hindering the field's understanding of pathophysiology and identification of targeted treatments. Current delirium subtyping methods reflect clinically evident features but likely do not account for underlying biology.

Outcome prediction of electroconvulsive therapy for depression.

Introduction: We developed and tested a Bayesian network(BN) model to predict ECT remission for depression, with non-response as a secondary outcome.

Methods: We performed a systematic literature search on clinically available predictors. We combined these predictors with variables from a dataset of clinical ECT trajectories (performed in the University Medical Center Utrecht) to create priors and train the BN.

Syntactic Network Analysis in Schizophrenia-Spectrum Disorders.

Background: Language anomalies are a hallmark feature of schizophrenia-spectrum disorders (SSD). Here, we used network analysis to examine possible differences in syntactic relations between patients with SSD and healthy controls. Moreover, we assessed their relationship with sociodemographic factors, psychotic symptoms, and cognitive functioning, and we evaluated whether the quantification of syntactic network measures has diagnostic value.

Clustering of antipsychotic-naïve patients with schizophrenia based on functional connectivity from resting-state electroencephalography.

Schizophrenia is associated with aberrations in the Default Mode Network (DMN), but the clinical implications remain unclear. We applied data-driven, unsupervised machine learning based on resting-state electroencephalography (rsEEG) functional connectivity within the DMN to cluster antipsychotic-naïve patients with first-episode schizophrenia. The identified clusters were investigated with respect to psychopathological profile and cognitive deficits.

Changes in perfusion, and structure of hippocampal subfields related to cognitive impairment after ECT: A pilot study using ultra high field MRI.

Background: Electroconvulsive therapy (ECT) in patients with major depression is associated with volume changes and markers of neuroplasticity in the hippocampus, in particular in the dentate gyrus. It is unclear if these changes are associated with cognitive side effects.

Objectives: We investigated whether changes in cognitive functioning after ECT were associated with hippocampal structural changes.

Muva physical activity intervention to improve social functioning in people with a severe mental illness: study protocol of a pragmatic stepped wedge cluster randomized trial.

Background: People with severe mental illness (SMI) often suffer from long-lasting symptoms that negatively influence their social functioning, their ability to live a meaningful life, and participation in society. Interventions aimed at increasing physical activity can improve social functioning, but people with SMI experience multiple barriers to becoming physically active. Besides, the implementation of physical activity interventions in day-to-day practice is difficult.

Functional brain network and trail making test changes following major surgery and postoperative delirium: a prospective, multicentre, observational cohort study.

Background: Delirium is a frequent complication after surgery in older adults and is associated with an increased risk of long-term cognitive impairment and dementia. Disturbances in functional brain networks were previously reported during delirium. We hypothesised that alterations in functional brain networks persist after remission of postoperative delirium and that functional brain network alterations are associated with long-term cognitive impairment.

Spontaneous brain activity, graph metrics, and head motion related to prospective post-traumatic stress disorder trauma-focused therapy response.

Introduction: Trauma-focused psychotherapy for post-traumatic stress disorder (PTSD) is effective in about half of all patients. Investigating biological systems related to prospective treatment response is important to gain insight in mechanisms predisposing patients for successful intervention. We studied if spontaneous brain activity, brain network characteristics and head motion during the resting state are associated with future treatment success.

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis.

Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear. This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP).

Interrogating Associations Between Polygenic Liabilities and Electroconvulsive Therapy Effectiveness.

Background: Electroconvulsive therapy (ECT) is the most effective treatment for severe major depressive episodes (MDEs). Nonetheless, firmly established associations between ECT outcomes and biological variables are currently lacking. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response in psychiatry are seldom reported.

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity.

Background And Purpose: The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.

Methods: We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders.

Childhood trauma is associated with reduced frontal gray matter volume: a large transdiagnostic structural MRI study.

Background: Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain regions may be impacted by trauma as well, and effects may be independent of diagnosis.