No abstract

Repetitive transcranial magnetic stimulation (rTMS) may have the potential to prevent depressive relapse. This assessor-blinded, randomized controlled study was designed to evaluate the efficacy and safety of rTMS as a mono- and combination therapy in the prevention of depressive relapse/recurrence. A total of 281 depressed patients who had achieved stable full or partial remission on a 6-month antidepressant (ADP) run-in treatment were randomly assigned to an rTMS (n = 91), ADP (n = 108), or combined (rTMS + ADP, n = 82) treatment group for 12 months. Monthly clustered rTMS was conducted in 5–10 sessions over a 3–5-day period. Maintenance outcomes were assessed using time to relapse/recurrence and relapse/recurrence rate. Overall, 71.2% (200/281) of the participants completed the treatment per the protocol. rTMS + ADP and rTMS significantly reduced the risk of relapse/recurrence compared with ADP (P = 0.000), with hazard ratios of 0.297 and 0.466, respectively. Both rTMS-containing regimens produced significantly lower relapse/recurrence rates than ADP (15.9% and 24.2% vs. 44.4%, P < 0.001). In the relapsed/recurrent subgroup, first-episode depressed, rTMS-treated patients had a markedly lower relapse/recurrence rate than ADP-treated patients. Five patients on the ADP-containing regimens, but none on rTMS alone, developed acute mania. The rTMS-containing regimens had considerably more certain side effects than did the ADP group. We concluded that TMS, whether as a mono- or additional therapy, is superior to antidepressants in preventing depressive relapse/recurrence, particularly in first-episode depressed patients. The treatment does not increase the risk of manic switch, but may increase the risk of certain side effects.

BackgroundEmerging evidence suggests structural and functional disruptions of the thalamus in schizophrenia, but whether thalamus abnormalities are able to be used for disease identification and prediction of early treatment response in schizophrenia remains to be determined. This study aims at developing and validating a method of disease identification and prediction of treatment response by multi-dimensional thalamic features derived from magnetic resonance imaging in schizophrenia patients using radiomics approaches.MethodsA total of 390 subjects, including patients with schizophrenia and healthy controls, participated in this study, among which 109 out of 191 patients had clinical characteristics of early outcome (61 responders and 48 non-responders). Thalamus-based radiomics features were extracted and selected. The diagnostic and predictive capacity of multi-dimensional thalamic features was evaluated using radiomics approach.ResultsUsing radiomics features, the classifier accurately discriminated patients from healthy controls, with an accuracy of 68%. The features were further confirmed in prediction and random forest of treatment response, with an accuracy of 75%.ConclusionOur study demonstrates a radiomics approach by multiple thalamic features to identify schizophrenia and predict early treatment response. Thalamus-based classification could be promising to apply in schizophrenia definition and treatment selection.