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BackgroundClinical staging, already widespread in medicine, represents a new frontier in psychiatry. Our goal was to convert the existing theoretical staging model for schizophrenia into a feasible tool to have a timely assessment of patients’ health status applicable in any psychiatric facility.MethodsWe assessed the empirical soundness of a staging model for schizophrenia spectrum disorders (SSDs), primarily centered on their current status. This model delineated six sequential stages (1, 2A, 2B, 3A, 3B, and 4) based on factors like symptom recurrence, persistence, and progression, including functional decline. Our analysis involved data from 137 individuals affected by SSDs. We examined 22 baseline variables, 23 construct-related variables, and 31 potentially modifiable clinical variables.ResultsThe latter stages demonstrated significantly poorer outcomes compared to the early stages across various measures, indicating medium to large effect sizes and a dose–response pattern. This pattern confirmed the validity of the model. Notably, stages 2 and 3A exhibited pronounced differences in comparison to other stages, although variables from each validation category also distinguished between consecutive stages, particularly 3A and beyond.ConclusionBaseline predictors, such as familial predisposition to schizophrenia, neurodevelopmental impairment, childhood adversities, treatment delay, negative symptoms, neurological impairment, and inadequate early response to treatment, independently largely explained the staging variance. The clinical staging model, grounded in the extended course of psychosis, exhibited sound validity and feasibility, even without the use of biological or neuroimaging markers, which could greatly improve the sensitivity of the model. These findings provide insights into stage indicators and predictors of clinical stages from the onset of psychosis.

IntroductionDissociative symptoms have been recently related to bipolar disorder (BD) symptomatology. Moreover, the disease burden carries on a share of perceived self-stigma that amplifies the BD impairment. Internalized stigma and dissociative symptoms often seem overlapping, leading toward common outcomes, with reduced treatment seeking and poor adherence. We hypothesize a potential relationship between dissociation and self-stigma in patients suffering from BD.Materials and methodsIn this cross-sectional study we enrolled a total of 120 adult clinically stable BD outpatients. All participants completed the Internalized Stigma of Mental Illness (ISMI), Dissociative Experiences Scale-II (DES-II), and Manchester Short Assessment of Quality of Life (MANSA).ResultsAverage age and age at BD (BD-I n = 66, 55%; BD-II n = 54, 45%) onset were 46.14 (±4.23), and 27.45 (±10.35) years, with mean disease duration of 18.56 (±13.08) years. Most participants were female (n = 71; 59.2%) and 40 (33%) of them experienced lifetime abuse, with an average of 1.05 (±0.78) suicide attempts. DES scores (mean 31.8, ±21.6) correlated with ISMI total-score, with significant association with spikes in Alienation (13.1, SD±3.1) (p < 0.001) and Stereotype (13.8, SD±3.9) (p < 0.001). Linear regression analysis has shown a significant association between DES total score and alienation (p < 0.001), stereotype (p < 0.001) and MANSA total-score (p < 0.001).DiscussionFor the first time, our data suggests that self-stigma is associated to dissociative symptoms, reducing overall quality of life in BD. The early identification of at-risk patients with previous lifetime abuse and high perceived stigma could lead the way for an ever more precise tailoring of treatment management.

Background: Dissociative symptoms are under recognized and scarcely studied by clinicians and researchers in patients with bipolar disorder (BD). We examined the relationship between dissociative symptoms and the psychotic features in patients with BD and assessed clinical and socio-demographic characteristics more frequently associated with dissociative symptoms and treatment response.Methods: Participants were 100 adult outpatients with BD. They were screened with semi-structured interview to collect socio-demographic and clinical characteristics; the Dissociative Experiences Scale-II (DES-II) and the ALDA scale were used to assess dissociative psychopathologies and response to treatment with mood stabilizers, respectively.Results: DES score (mean 31.7 ± 21.7) correlated with clinical variables, BD features, and course of illness. Psychotic symptoms, mixed features, and previous suicide attempts significantly predicted DES score [F(3, 47) = 39.880, p < 0.001, R2 corrected = 0.713]. Dissociative symptoms were inversely correlated with poor response to treatment (r = −0.593; p < 0.001).Limitations: Cross-sectional design with a small sample and backward clinical assessment of psychotic symptoms.Conclusions: Dissociative phenomena are closely related to the presence of psychotic symptoms, mixed features, and previous suicide attempts in BD, especially in BD-I. Given the close association between dissociative and psychotic symptoms, this association could represent a diagnostic indicator of BD-I that may guide the clinician to plan the most appropriate treatment.

Background: Binge eating disorder (BED) is clinically relevant by virtue of the global impairment, poor quality of life, and increased overall medical morbidity. The high comorbidity with psychiatric disorders, particularly depression, has received attention as a possible mediator of the poor outcome. Further, BED and depression share cognitive dysfunctions. This naturalistic and uncontrolled pilot study aimed at evaluating the efficacy of vortioxetine (VTX) on depressive symptoms in patients with BED, secondly the efficacy in improving a broad array of executive functions, and third to explore the effect on eating behavior and body weight.Methods: This pilot study involved 30 patients with BED and comorbid MDD, treated with VTX for 24 weeks. Assessments were run at baseline (t0), 4 (t1), 8 (t2), 12 (t3), and 24 (t4) weeks. Changes in depressive symptoms (HDRS and BDI), executive functions, eating behaviors (binge frequency and severity, night eating, food addiction), and body weight were estimated after treatment with VTX through GLM.Results: Significant improvements emerged after treatment with VTX in: depression (HDRS p < 0.001; BDI p = 0.002) regardless the dose of VTX and first diagnosis (BED/MDD), working memory (RAVLT acquisition p = 0.01, delay recall p < 0.001, RCFT percentage of recall p = 0.01, and Attentional Matrices p = 0.05), binge days frequency (p < 0.001), binge eating severity (BES p < 0.001), night eating (p = 0.001), food addiction (YFAS 2.0 p = 0.039), and body weight (p = 0.039). The improvement in depressive symptoms was associated with the concurrent improvement in night eating as assessed by the I-NEQ.Conclusions: VTX can be a valid therapeutic choice for patients with BED with comorbid depression in controlling the depressive symptoms, working memory, and eating behavior. Indeed, by acting on affective symptoms, neurocognitive functioning, and eating behaviors, it confirms the results already obtained with VTX in other disorders, expanding them to BED.

Non-invasive measurements of brain function and structure as neuroimaging in patients with mental illnesses are useful and powerful tools for studying discriminatory biomarkers. To date, functional MRI (fMRI), structural MRI (sMRI) represent the most used techniques to provide multiple perspectives on brain function, structure, and their connectivity. Recently, there has been rising attention in using machine‐learning (ML) techniques, pattern recognition methods, applied to neuroimaging data to characterize disease-related alterations in brain structure and function and to identify phenotypes, for example, for translation into clinical and early diagnosis. Our aim was to provide a systematic review according to the PRISMA statement of Support Vector Machine (SVM) techniques in making diagnostic discrimination between SCZ patients from healthy controls using neuroimaging data from functional MRI as input. We included studies using SVM as ML techniques with patients diagnosed with Schizophrenia. From an initial sample of 660 papers, at the end of the screening process, 22 articles were selected, and included in our review. This technique can be a valid, inexpensive, and non-invasive support to recognize and detect patients at an early stage, compared to any currently available assessment or clinical diagnostic methods in order to save crucial time. The higher accuracy of SVM models and the new integrated methods of ML techniques could play a decisive role to detect patients with SCZ or other major psychiatric disorders in the early stages of the disease or to potentially determine their neuroimaging risk factors in the near future.

The worldwide prevalence of sleep disorders is approximately 50%, with an even higher occurrence in a psychiatric population. Bipolar disorder (BD) is a severe mental illness characterized by shifts in mood and activity. The BD syndrome also involves heterogeneous symptomatology, including cognitive dysfunctions and impairments of the autonomic nervous system. Sleep abnormalities are frequently associated with BD and are often a good predictor of a mood swing. Preservation of stable sleep–wake cycles is therefore a key to the maintenance of stability in BD, indicating the crucial role of circadian rhythms in this syndrome. The symptom most widespread in BD is insomnia, followed by excessive daytime sleepiness, nightmares, difficulty falling asleep or maintaining sleep, poor sleep quality, sleep talking, sleep walking, and obstructive sleep apnea. Alterations in the structure or duration of sleep are reported in all phases of BD. Understanding the role of neuroglia in BD and in various aspects of sleep is in nascent state. Contributions of the different types of glial cells to BD and sleep abnormalities are discussed in this paper.