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Introduction: Childhood trauma and adversities (CTA) and aberrant salience (AS) have a pivotal role in schizophrenia development, but their interplay with psychotic symptoms remains vague. We explored the mediation performed by AS between CTA and psychotic symptomatology in schizophrenia., Methods: We approached 241 adults suffering from schizophrenia spectrum disorders (SSDs), who have been in the unit for at least 12 consecutive months, excluding the diagnosis of dementia, and recent substance abuse disorder, and cross-sectional evaluated through the Aberrant Salience Inventory (ASI), Childhood Trauma Questionnaire Short-Form (CTQ-SF), and Positive and Negative Symptom Scale (PANSS). We tested a path-diagram where AS mediated the relationship between CTA and psychosis, after verifying each measure one-dimensionality through confirmatory factor analysis., Results: The final sample comprised 222 patients (36.9% female), with a mean age of 42.4 (± 13.3) years and an average antipsychotic dose of 453.6 (± 184.2) mg/day (chlorpromazine equivalents). The mean duration of untreated psychosis was 1.8 (± 2.0) years while the mean onset age was 23.9 (± 8.2) years. Significant paths were found from emotional abuse to ASI total score (β = 0.39; p < .001) and from ASI total score to PANSS positive (β = 0.17; p = .019). Finally, a statistically significant indirect association was found from emotional abuse to PANSS positive mediated by ASI total score (β = 0.06; p = .041; CI 95% [0.01, 0.13])., Conclusion: Emotional abuse has an AS-mediated effect on positive psychotic symptomatology. AS evaluation could allow a better characterization of psychosis as well as explain the presence of positive symptoms in adults with SSDs who experienced CTA., Competing Interests: Declaration of competing interest No commercial organizations had any role in the writing of this paper for publication. In the last 3 years, RdF has received speaker fees from Janssen Pharmaceutica, Angelini, and Lundbeck, and travel support from Janssen Pharmaceutica, Otsuka, Lundbeck, and ROVI Pharma Industrial Services. In the last 3 years, the remaining authors report no conflicts of interest., (Copyright © 2023. Published by Elsevier Inc.)

Introduction: Cognitive models suggest the co-occurrence of cognitive biases and aberrant salience is unique to psychosis, but their interaction is not yet fully understood. Therefore, we aimed to elucidate the relationship between subjective cognitive biases and aberrant salience in individuals with schizophrenia spectrum disorders (SSDs) in this study., Methods: A sample of 92 subjects with SSDs underwent an assessment using Davos Assessment Cognitive Biases (DACOBS) and the Aberrant Salience Inventory (ASI) in a cross-sectional design. We evaluated psychopathological differences based on ASI scores and conducted a linear regression analysis to examine the variables associated with aberrant salience., Results: Subjects with an ASI score ≥14 demonstrated significantly higher scores across all subscales and total score of ASI and DACOBS (p<0.001). ASI subscales were significantly positive correlated with all DACOBS subscales, ranging from 0.250 for Increased Significance and Safety Behavior to 0.679 for Heightened Emotionality and Social cognition problems. The linear regression analysis revealed a positive association between aberrant salience and the DACOBS subscales jumping to conclusions (JTC) (β=0.220), social cognition problems (β=0.442), subjective cognitive problems (β=0.405), and a negative association with the subscale belief inflexibility (β=-0.350)., Conclusions: Our findings suggest that JTC, social cognition problems and subjective cognitive problems may play a central role in the experience of aberrant salience in individuals with SSDs. This work informs about the need of developing prevention and intervention strategies that specifically target cognitive biases and aberrant salience in the treatment of psychosis., (Copyright © 2023 The Author(s). Published by Elsevier España S.L.U. All rights reserved.)

Purpose: Recently two instruments were developed to address the study of the cognitive biases in schizophrenia spectrum disorders (SSD): the Cognitive Biases Questionnaire for Psychosis (CBQ-P) and the Davos Assessment of Cognitive Biases Scale (DACOBS). Aim of this study was to validate the Italian version of the DACOBS., Methods: We investigated factor structure, reliability, discriminative and convergent validity of the instrument by comparing to the CBQ-P in an Italian sample of 102 patients diagnosed with SSD and 330 healthy controls (HC), matched by age, education and gender., Results: The second-order seven-factor solution provided the best results among the four models tested. Reliability proved to be very satisfactory, with ω coefficient ranged from 0.75 for Jumping to conclusions to 0.89 for Safety Behavior. The Italian version of DACOBS could discriminate psychosis from HC (Wilks' Lambda=0.64, F=34.284, p<0.001; h2=0.364). All seven DACOBS subscales were significantly correlated with the CBQ-P subscales (total sample: r=0.331-0.707; SSD group: r=0.424-0.735; HC group: r=0.177-0.460)., Conclusions: The Italian version of DACOBS is a valid instrument for measuring cognitive biases for patients with psychosis, confirming previous results regarding the psychometric properties of the tool.

Background: Cognitive impairment is considered a central feature of schizophrenia (SZ) and several rehabilitation treatments have been developed to try to improve cognitive deficits. Aims : The aim of the present study was to analyze the effectiveness of integrated psychological therapy (IPT) compared with a standard treatment (TAU) in two groups of patients with SZ, using a comprehensive testing battery of clinical, cognitive, social cognition and functional outcome domains. Methods: Forty-one patients with SZ were assigned to IPT or TAU groups in a randomized controlled trial (RCT). Psychopathological, neuropsychological, emotional and functional outcome variables were assessed at baseline and after 36 weeks of treatment. Results: The IPT group showed significant improvements than the TAU group regarding clinical and functional outcome variables. Moreover, the IPT group improved significantly in the cognitive domains and emotional functioning. Finally, linear regression has highlighted that the improvement of cognitive variables depends on having done the IPT treatment. Conclusions: IPT seems to be effective in improving clinical, neuropsychological, emotional and functional outcome in chronic SZ inpatients. Further studies would be desirable to deepen the effectiveness of IPT in the field of the psychiatric rehabilitation pointing to the possibility of recovery from mental illness.

Background: The main purpose of this study was to assess possible modifications of cognitive performance among schizophrenia patients treated with long-acting injectable antipsychotics (LAIs) of second generation anti-psychotics (SGAs). Our hypothesis is that the shift from the oral formulation to the LAI formulation of SGAs drugs improves the cognitive performance. The secondary objective was to carry out a head to head comparison of two different SGA-LAI treatments [i.e., 1-month Paliperidone Palmitate (PP1M), monthly Aripiprazole (Ari-LAI)] in our study with an independent and real-world setting. Methods: The sample comprised 32 participants who were consecutively recruited over 12 months. Seventeen patients treated with Ari-LAI and 10 treated with PP1M completed psychopathological, neuropsychological and functional assessments. Group differences were explored through chi-squared and t -tests, as appropriate. GLM Repeated Measures were used to study variations of cognitive performance along 12 months and to test differences between drugs. Results: We found an effect of time on the outcomes investigated but this did not depend on the type of LAI used. Conclusions: In comparison with the previous oral treatment with SGAs, patients showed a significant improvement in neurocognitive function after 12 months of treatment with SGA-LAI. Furthermore, there were no differences between the SGA-LAI regimens.Key pointsThe main purpose of this study was to assess possible modification of cognitive performance of patients with Schizophrenia treated with second generation long-acting injectable antipsychotics (SGA-LAIs).The secondary objective was to carry out a head to head comparison of two different SGA-LAIs: Paliperidone Palmitate 1-Month (PP1M) and Aripiprazole Monthly (Ari-LAI).Patients showed a significant improvement in neurocognitive function after 12 months of treatment with SGA-LAI.There were no differences between the SGA-LAI regimens.From a practical point of view, switching to LAI formulation seems to produce further social and cognitive improvements in patients who had already benefitted from oral SGA therapy.

Background: Adverse childhood experiences (ACEs) are risk factors for psychiatric disorders, but evidence about their relationship with clinical severity is limited. We aimed to classify patients according to ACEs and to compare these clusters with regards to the clinical severity., Methods: Seventy-four patients with Bipolar Disorder (BD) and 91 patients with a diagnosis within the Schizophrenia Spectrum Disorders (SSDs) were interviewed. The Childhood Experience of Care and Abuse scale (CECA) and the Positive and Negative Symptoms Scale (PANSS) were administered. A two-step cluster analysis was run to identify clusters according to ACEs. PANSS average scores were compared between clusters., Results: Three clusters emerged; significant differences in ACEs distribution were evident. Cluster 1 was characterized by very low frequency of ACEs. ACEs related to lack of support/isolation were more frequent within Cluster 2, instead ACEs related to abuse/neglect were over represented in Cluster 3. The comparison of PANSS through ANOVA demonstrated that Cluster 3 not only had significantly higher scores in all dimensions than Cluster 1 and 2 but also a higher average number of ACEs., Limitations: CECA is a self-report scale and is subject to recall bias., Conclusions: Specific ACEs are related to clinical severity among BD and SSD patients. Early life adversities related to abuse and neglect are associated to greater symptomatic severity than those related to lack of support/isolation. Our findings suggest that a history of ACEs could be used to identify patients at higher risk of unfavorable clinical features., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: Although clozapine (CLZ) is considered the best evidence-based therapeutic option for treatment of resistant schizophrenia patients, a significant proportion of CLZ-treated patients show a partial or inadequate response to treatment, leading to increased healthcare cost and poor quality of life for affected individuals., Areas Covered: This paper comprises a review of main research in CLZ augmentation strategies for treatment-refractory schizophrenia, with a focus on research conducted between 1990 and 2014. Databases that were searched include: PubMed, CINAHL, EMBASE PsychINFO, AgeLine and Cochrane Database of Systematic Reviews. Primary search terms were 'clozapine augmentation', 'clozapine and add-on' and 'treatment-resistant schizophrenia', with cross reference to specific agents covered in this article. We reviewed the available evidence on CLZ augmentation with antipsychotics, antidepressants, mood stabilizers and other agents., Expert Opinion: Many drugs have been evaluated as CLZ add-on therapies without demonstrating convincing efficacy in treating refractory schizophrenia symptoms. More research is needed to better define outcomes in schizophrenia, the topic of treatment-resistance and more well-designed trials are required to establish true efficacy and safety of CLZ augmentation strategies.

Background: Antipsychotic drugs appear to be related to reduced bone mineral density (BMD). We conducted a narrative review to collect the available literature investigating the relationship between antipsychotic use and bone fragility. Methods: A review of the published literature was conducted and reported through PubMed/Scopus/Cochrane libraries. We included studies using any antipsychotic treatment where the bone metabolism, osteoporosis, and/or risk of fractures has been assessed. Results: After screening 1707 items, we finally included 15 papers. A total of 3245 initial patients were identified, of whom 1357 patients with a mean age of 43.8 years underwent antipsychotic treatment and were analyzed. The mean antipsychotic treatment duration of the treated group was 15.8 ± 13.9 years. Among the included studies, two reported a statistically significant difference in lumbar BMD reduction between the antipsychotic exposed group and the control group. Femoral neck BMD levels had been reported in four of the case–control studies; two reported a statistically significant difference in femoral neck BMD reduction between the antipsychotic exposed group and the control group. Conclusions: Prolonged use of antipsychotic treatment seems to be associated with an increased risk of reduced BMD, and, consequentially, with an augmented risk of bone fragility and fractures. This effect is not limited to vulnerable groups, such as those with significant medical comorbidities, the elderly, and postmenopausal women, but may also apply to anyone using antipsychotics in the long-term. Clinicians' awareness of antipsychotic prescriptions should optimize their potential while reducing this risk. [ABSTRACT FROM AUTHOR]

Background: Clinical 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. Methods: We 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. Results: The 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. Conclusion: Baseline 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. [ABSTRACT FROM AUTHOR]

We hypothesized that shifting from oral second-generation antipsychotics (SGA) to their long-acting injectable (LAI) counterpart would be beneficial for the psychopathological, cognitive, social, and general health domains in outpatients suffering from schizophrenia. We aimed to evaluate the prospective usefulness of SGA-LAI treatment by carrying out a head-to-head comparison of two different medications (i.e., aripiprazole monohydrate (Ari-LAI) and paliperidone palmitate 1 and 3 month (PP1M, PP3M)) in a real-world setting, assessing the effectiveness and tolerability of Ari-LAI and PP1M/PP3M over a 15 month follow-up. A total of 69 consecutive individuals affected by schizophrenia were screened for eligibility. Finally, 46 outpatients (29 treated with Ari-LAI, 13 with PP1M, and four with PP3M) were evaluated through clinical, functional, and neuropsychological assessment administrated at baseline and after 3-, 12-, and 15-month follow-up periods. Moreover, periodic general medical evaluations were carried out. We estimated an overall improvement over time on the explored outcomes, without differences with respect to the type of LAI investigated, and with a global 16.4% dropout rate. Our findings suggest that switching from oral SGA to SGA-LAIs represents a valid and effective treatment strategy, with significant improvements on psychopathological, cognitive, social, and clinical variables for patients suffering from schizophrenia, regardless of the type of molecule chosen. [ABSTRACT FROM AUTHOR]

Background: Clozapine is well known for its efficacy and clinical superiority compared to other antipsychotics in treatment-resistant schizophrenia (TRS). However, it is frequently underutilized worldwide because of its acute adverse events, as well as for its long-term cardiometabolic and hematological consequences. Objective: The aim of the study was to evaluate 5-year safety in chronic TRS inpatients with continuous clozapine use. Methods: Patients with TRS and clozapine treatment were evaluated for 5 years. All participants were assessed using the Brief Psychiatric Rating Scale (BPRS), Glasgow Antipsychotic Side-effect Scale for Clozapine (GASS-C), Social Performance Scale (PSP) and Short Portable Mental Status Questionnaire (SPMSQ). Clinical, cardiometabolic and hematological data were collected periodically. General linear models (GLM) repeated measures controlling for CLZ dose were utilized to determine differences in variables across the time. Results: Overall, 189 inpatients were screened for study participation. The final sample included twenty-one TRS patients (16 males, 76%) with an average age of 57.6 years, all with 5-year continuous use of clozapine (mean dose 266 mg/day). There was not a significant effect of time on BPRS (p=0.774), PSP (p=0.855) and SPMSQ (p=0.066); differences remained not significant after controlling for CLZ dose (p=0.585, p=0.467 and p=0.105, respectively). No changes were found in blood and clinical parameters except for red blood cell count, which decreased over time (p=0.024; η2= 0.952). Patients reported a significant BMI decrease (− 8.98 kg, p=0.008) between baseline and 5 years last observation. Conclusion: The findings show how the application of a structured dietary, clinical and therapeutic monitoring program in psychiatric care facilities could allow the safe and effective long-term cardiometabolic and hematological management of clozapine. The unique role that clozapine plays in the current treatment of patients with TRS requires greater clinical awareness. Although its acute and chronic side effects are notorious, its safety management is feasible and broadens its potential practical application. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Diagnosis of schizophrenia (SCZ) is made exclusively clinically, since specific biomarkers that can predict the disease accurately remain unknown. Machine learning (ML) represents a promising approach that could support clinicians in the diagnosis of mental disorders. Objectives: A systematic review, according to the PRISMA statement, was conducted to evaluate its accuracy to distinguish SCZ patients from healthy controls. Methods: We systematically searched PubMed, Embase, MEDLINE, PsychINFO and the Cochrane Library through December 2018 using generic terms for ML techniques and SCZ without language or time restriction. Thirty-five studies were included in this review: eight of them used structural neuroimaging, twenty-six used functional neuroimaging and one both, with a minimum accuracy >60% (most of them 75–90%). Sensitivity, Specificity and accuracy were extracted from each publication or obtained directly from authors. Results: Support vector machine, the most frequent technique, if associated with other ML techniques achieved accuracy close to 100%. The prefrontal and temporal cortices appeared to be the most useful brain regions for the diagnosis of SCZ. ML analysis can efficiently detect significantly altered brain connectivity in patients with SCZ (eg, default mode network, visual network, sensorimotor network, frontoparietal network and salience network). Conclusion: The greater accuracy demonstrated by these predictive models and the new models resulting from the integration of multiple ML techniques will be increasingly decisive for early diagnosis and evaluation of the treatment response and to establish the prognosis of patients with SCZ. To achieve a real benefit for patients, the future challenge is to reach an accurate diagnosis not only through clinical evaluation but also with the aid of ML algorithms. [ABSTRACT FROM AUTHOR]