Introduction Mental disorders affect nearly one billion people worldwide, posing major challenges to public health. While conventional treatments like psychotherapy and pharmacotherapy are effective for many patients, they are often associated with adverse effects and high non-response rates, underscoring the need for alternative approaches. Non-invasive brain stimulation techniques such as transcranial magnetic stimulation, transcranial electric stimulation and transcranial focused ultrasound stimulation are increasingly used to treat psychiatric conditions. Although these methods show promising efficacy, data on their adverse effects remain fragmented and inconsistently reported. This meta-analysis aims to systematically compare the type and frequency of adverse effects, tolerability, and acceptability across different brain stimulation techniques and mental disorders. The findings will help improve safety monitoring and support more personalised, well-tolerated treatment strategies. - Methods and analysis A systematic literature search of the Embase, MEDLINE(R), AMED (Allied and Complementary Medicine) and APA PsycINFO via OVID will be performed. Eligible studies include randomised controlled trials (RCTs) that compare active treatments or an active treatment with sham control, including both parallel group and cross-over studies, as well as prospective non-randomised studies such as case-control studies and pre-post studies investigating adverse effects of non-invasive brain stimulation in psychiatric populations. Included studies report on the frequency of adverse effects in a standardised manner. Primary outcomes comprise the incidence of specific adverse effects, dropout rates due to adverse effects (tolerability) and overall dropout rates (acceptability). Risk of bias will be assessed using the Cochrane RoB 2.0 tool for RCTs and the NHLBI quality assessment tool for pre-post studies. The quality of case-control studies will be assessed using the Newcastle-Ottawa scale. Provided that sufficient data are available and the network of comparisons is adequately connected, a network meta-analysis will be conducted to compare adverse effects and tolerability across interventions. - Ethics and dissemination No ethical approval is needed to conduct this work. The findings will be submitted for publication in peer-reviewed journals and presented at scientific meetings. - PROSPERO registration number CRD420251164554
BMJ open London : BMJ Publishing Group, 2011 16(2026), Artikel-ID e107577, Seite 1-7 Online-Ressource
von Eivind Haga Ronold ; Daniel Jensen ; Anders Lillevik L Thorsen ; Rune Raudeberg ; Leif Oltedal ; Åsa Hammar ; Marco Hirnstein ; Katie Douglas ; Richard Porter ; Maximilian Kiebs
Online verfügbar: 18. September 2024, Artikelversion: 22. September 2024 ; Gesehen am 20.05.2025
The Global ECT MRI Research Collaboration (GEMRIC) has collected clinical and neuroimaging data of patients treated with electroconvulsive therapy (ECT) from around the world. Results to date have focused on neuroimaging correlates of antidepressant response. GEMRIC sites have also collected longitudinal cognitive data. Here, we summarize the existing GEMRIC cognitive data and provide recommendations for prospective data collection for future ECT-imaging investigations. We describe the criteria for selection of cognitive measures for mega-analyses: Trail Making Test Parts A (TMT-A) and B (TMT-B), verbal fluency category (VFC), verbal fluency letter (VFL), and percent retention from verbal learning and memory tests. We performed longitudinal data analysis focused on the pre-/post-ECT assessments with healthy comparison (HC) subjects at similar timepoints and assessed associations between demographic and ECT parameters with cognitive changes. The study found an interaction between electrode placement and treatment number for VFC (F(1,107) = 4.14, p = 0.04). Higher treatment was associated with decreased VFC performance with right unilateral electrode placement. Percent retention showed a main effect for group, with post-hoc analysis indicating decreased cognitive performance among the HC group. However, there were no significant effects of group or group interactions observed for TMT-A, TMT-B, or VFL. We assessed the current GEMRIC cognitive data and acknowledge the limitations associated with this data set including the limited number of neuropsychological domains assessed. Aside from the VFC and treatment number relationship, we did not observe ECT-mediated neurocognitive effects in this investigation. We provide prospective cognitive recommendations for future ECT-imaging investigations focused on strong psychometrics and minimal burden to subjects.
Journal of psychiatric research Amsterdam [u.a.] : Elsevier Science, 1961 179(2024) vom: Nov., Seite 199-208 Online-Ressource
Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = −2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.
