Schizophrenia Disorder Research Articles

The Conflict between Top-down and Bottom-up Impairments in Consciousness Disorder in Schizophrenia

Introduction: Schizophrenia, a complex psychiatric disorder, is often associated with consciousness disorders, typically characterized by an elevated threshold of conscious perception. Over the years, a multitude of research has been dedicated to uncovering the primary cause of these disorders, leading to the development of several theories. Methods: In this article, two central answers to this problem have been reviewed. For this, the articles that were more related to the topic were selected. Based on the relevance to the subject of research, the main ideas of targeted articles are reordered to be comprehensible for the readers. Finally, the judgment and conclusion of the authors about the discussed problem are presented in this study. Discussion: The first theory, which we will explore in this article, suggests that the root cause of these disorders lies in defects within bottom-up processes. These processes, fundamental to our understanding of the world, involve the progression of sensory information from low-level perception to high-level awareness. In individuals with schizophrenia, these processes are believed to be compromised, leading to a distorted perception of reality. The second theory, in contrast, attributes the cause to impairments in top-down processes. These processes, which refer to the influence of high-level cognitive functions on lower-level sensory perception, are also considered dysfunctional in schizophrenic patients. This dysfunction is thought to disrupt the integration of sensory information, thereby affecting the individual's consciousness. However, a third perspective has emerged, suggesting the coexistence of impairments in both bottom- up and top-down processing. This perspective argues that to fully comprehend the nature of consciousness disorders in schizophrenia, it is crucial to determine the type and severity of both bottom-up and top-down impairments. Conclusion: In this review, we delve into these theories, examining the evidence supporting each and discussing their implications for our understanding of schizophrenia. Considering both bottom-up and top-down impairments, the third perspective offers a more holistic explanation for these disorders. We further argue that this perspective underscores the need for a more nuanced approach to studying schizophrenia. It suggests that future research should not only focus on these processes in isolation but also explore their interaction and the potential synergistic effects of their impairment. By doing so, we can hope to gain a more comprehensive understanding of consciousness disorders in schizophrenia, which could ultimately lead to more effective treatment strategies.

The role of immunomodulators in severe mental disorders: future perspectives.

The immune system is of pivotal importance with regard to the development and maintenance of mental illness. Aberrant cytokine levels are significant immune markers, and research is increasingly focusing on the complement system and the gut-brain axis. The efficacy and safety of immunomodulatory interventions are currently the subject of clinical studies. Hence, this review is timeline and relevant to evaluate the latest evidence on the clinical value of immunomodulatory treatments from studies over the past 18 months in schizophrenia, bipolar disorder and unipolar depression. While conventional psychotropic drugs (antidepressants, antipsychotics, lithium) appear to have immunomodulatory adverse effects, antibiotics (minocycline), nonsteroid anti-inflammatory drugs (celecoxib) and anti-inflammatory therapeutics in particular are the subject of ongoing clinical trials. Integrative medical interventions such as nutritional supplements (e.g., N-acetyl-l-cysteine, polyunsaturated fatty acids) and exercise interventions (e.g., running, yoga) are being evaluated for their immunomodulatory effects and clinical value. No evidence-based recommendation can be made for the immunomodulatory treatment of depression, although celecoxib appears to be more effective than minocycline and omega-3 fatty acid. N-acetylcysteine (NAC) may be beneficial for the treatment of bipolar and schizophrenia disorders. However, further translational research is required to confirm these findings.

Slow negative potentials in the pre-stimulus period in norm and patients with the first episode of schizophrenia

Behavioral data (correct response latency and errors number increase) indicate a significant decrease in the task performance efficiency in patients with the first episode of schizophrenia, compared to the norm. At the same time the SNP 1, 2, 3 amplitudes were found to enhance in the patients group, compared to the norm, which may reflect a compensatory activation of predictive attention and inhibition cortical networks for increase the response efficiency. Intergroup differences in the topography of the SNP1 and SNP2 peaks amplitude suggest “disorganization” of the left hemisphere cognitive control cortical networks at the early stage of schizophrenia. It is assumed that the SNP 1, 2, 3 components can be considered as potentially significant clinically markers of cognitive control disorders in schizophrenia.

Association of GAD1 gene polymorphism rs3749034 with the information processing and cognitive event-related potentials in schizophrenia patients and healthy subjects

ObjectiveGlutamic acid decarboxylase, an enzyme in GABA biosynthesis, is encoded by the GAD1 gene, the transcriptional activity of which is affected by the rs3749034 polymorphism. The aim was to investigate the effects of rs3749034 on cognitive event-related potentials (P300) in healthy subjects and schizophrenic patients. MethodsDetermination of rs3749034 polymorphism was performed in 89 healthy volunteers and 109 schizophrenic patients (males). Two-stimulus oddball task performance and P300 auditory evoked potentials were analyzed and patient symptomatology was assessed using the Positive and Negative Syndrome Scale (PANSS). ResultsAn increased frequency of C allele carriers was disclosed in patients. In controls, superior task performance was observed in cytosine-thymine carriers, while a greater P300 amplitude and shorter latency were found in C/C carriers. Analogous effects were found in patients with a disease onset before 25 years of age. Higher N5 and lower P3 and G5 PANSS scales were revealed in C/C homozygotes. ConclusionsThe findings substantiate an involvement of GABA-ergic mechanisms in maintaining an optimal excitatory-inhibitory balance and an association of rs3749034 with early-onset disorder and negative symptoms of schizophrenia. SignificanceThese results are important for understanding underlying mechanisms and the development of evidence-based methods for assessing the risk of schizophrenia.

Anxiety disorders in schizophrenia - the importance of differentiation and targeted treatment a case report and literature review

Schizophrenia is a chronic mental disorder characterized by severe cognitive and behavioral impairments. It often coexists with multiple and complex anxiety symptoms that exacerbate the clinical challenges associated with schizophrenia. This case report presents the history of a 32-year-old woman with a final diagnosis of both paranoid schizophrenia and mixed anxiety disorders. The patient presented with persistent auditory pseudohallucinations, severe anxiety together with occasional panic attacks, which were treated with a variety of antipsychotics. Treatment adjustments were necessitated by the emergence of side effects, including neutropenia, motor disturbances and the observation of major anxiety symptoms, including panic disorder. Ultimately, the successful use of quetiapine in monotherapy was achieved. This case study emphasizes the need for comprehensive treatment strategies to address the complex interplay of psychotic and anxiety symptoms. Increased clinical awareness and targeted treatment of comorbid anxiety can significantly improve the quality of life of patients with schizophrenia.

PAUSING IN THE ORAL SPEECH OF PATIENTS WITH SCHIZOPHRENIA

The article examines the psycholinguistic analysis of pauses in the spontaneous oral speech of patients with schizophrenia. The purpose of the study is to identify the characteristics of speech pauses in patients with schizophrenia and compare them with pauses in the speech of mentally healthy individuals. The object of the study is the oral speech of patients diagnosed with "schizophrenia", and the subject is the peculiarities of speech pauses in these patients. The study employs general scientific methods (observation, quantitative, descriptive) and specialized methods of psycholinguistic analysis. The research material includes recorded fragments of the oral speech of patients with schizophrenia, totaling 36 minutes and 16 seconds, and the oral speech of mentally healthy individuals, totaling 45 minutes and 23 seconds. The scientific novelty of the research lies in presenting a psycholinguistic analysis of pauses in the speech of patients with schizophrenia and comparing the obtained results with the speech of mentally healthy individuals. The results showed that the average number of pauses in the oral speech of schizophrenic patients is nearly five times higher than the average number of pauses in the speech of mentally healthy individuals (3 pauses versus 14, respectively). It was also found that the speech of mentally ill individuals is quantitatively dominated by filled and unfilled pauses, with hesitation pauses being present only in the speech of schizophrenic patients. The average pause length in schizophrenic patients’ speech is 240 ms longer than in healthy individuals’ speech. The conclusions of the study may indicate difficulties in the organization and planning of speech activity in patients with schizophrenia. The research perspectives involve further study of the psycholinguistic aspects of speech disorders in schizophrenia, which may contribute to the development of diagnostic and speech correction methods for mentally ill individuals at the early stages of the disease.

Clinical and Psychometric Features of Cognitive and Negative Disorders in Schizophrenia

Clinical and Psychometric Features of Cognitive and Negative Disorders in Schizophrenia

Sleep, Sleep Disorders, and Mental Health: A Narrative Review

Abstract Evidence suggests that sleep is a vital component of physical and health well-being. However, while sleep problems are present in individuals with mental health problems such as depression, it has not been clear whether these conditions are independent or whether they might be causally related. Indeed, if sleep or sleep disorders predispose or modify onset and outcomes of mental health issues, treatment of these factors could be explored as new mental health prevention or treatment options. The aim of this review was to examine in detail the bidirectional relationship between sleep, sleep disorders, and mental and physical health and well-being. It has considered the evidence that sleep architecture disruption, occurring through both quantity, quality, and timing of sleep as well as through the presence of sleep disorders may both influence mental health and well-being as well as be disrupted by both physical and mental health conditions. Also, the review has explored the effects of sleep disruption on mental health and performance through fatigue, mood, and vigilance. The review has considered the bidirectionality between sleep, sleep disorders, and mental health to examine how these may lead to or exacerbate mental health disorders such as affective, anxiety, autism, depressive and schizophrenia disorders but also considers how these conditions can affect sleep. The review highlights that poor sleep or the presence of a sleep disorder can increase the risks from mental health conditions such as suicidality. Furthermore, mental health conditions such as anxiety and worry can cause racing or repetitive thoughts that can keep an individual awake, leading to shortened sleep. It is important that sleep and sleep disorders are considered potential modifiable factors that could improve mental health outcomes. The important interconnect between both physical and mental health and sleep, in patient evaluations, also needs to be considered as these may affect treatment pathways and patient outcomes. Further, more robust and perspective research is required to establish the triad relationship of physical, mental health, and sleep.

Clinical and neuroimaging aspects of formal thought disorder in schizophrenia: a brief narrative review

Aim. To analyze current sources regarding the clinical and neuroimaging aspects of formal thought disorder (FTD) in patients with schizophrenia to create an up-to-date pathogenetic model of its main forms. Materials and methods. English-language publications in the Medline database (PubMed) were analyzed for this review. We analyzed only structural magnetic resonance imaging (MRI) studies in which a clear clinical assessment of FTD in schizophrenia is provided and the neuroimaging protocol meets generally accepted standards (as in the ENIGMA Schizophrenia Working Group). For the clinical division of FTD, positive and negative FTD were distinguished according to the positive and negative syndrome scale (PANSS). Results. From a clinical point of view, FTD includes at least 30 phenomena. For clinical and neuroimaging studies, division into positive and negative FTD is used according to the PANSS. Positive FTD is manifested by the disorganization of thinking processes and exhibits mainly in violations of its purposeful sequence. Negative FTD is manifested by violations of the abstract-symbolic way of thinking, lack of spontaneity, and stereotyping. According to morphometric MRI data, atrophic changes in brain regions related to neuronal networks of cognition and impulse control (prefrontal and anterior cingulate cortex), emotional processing (amygdala), abstract thinking, and imagination (lateral occipital cortex) are important for the development of both forms of FTD. Negative FTD is mainly associated with damage to the prefronto-cingulate circles, which are the anatomical and functional substrates of executive functions. A unique feature of positive FTD is atrophy of the structures of the left temporal lobe, which leads to language disorders at the semantic level. Using the method of virtual histology, it was established that both forms of FTD are associated with bilateral changes in astrocytes and dendritic spines in the involved anatomical regions. A positive FTD is also associated with pathological changes in microglia in two hemispheres, while with a negative FTD, microglial damages are present only in the right hemisphere. Conclusions. Positive FTD in schizophrenia is mainly associated with atrophic (astroglial-microglial) processes of cognitive control networks, negative – with the atrophy of networks of semantic processing of verbal information. In both forms, networks of emotional processing, abstract thinking, and imagination are involved. Treatment strategies for FTD should include effects on astroglial and microglial dysfunction.

Quality Of Life In Patients With Schizophrenia Disorder Exhibiting Manifestations In Oral Cavity During Severe Acute Respiratory Syndrome, Corona Virus Disease 19 And Omicron Pandemic Era: An Original Research

Quality Of Life In Patients With Schizophrenia Disorder Exhibiting Manifestations In Oral Cavity During Severe Acute Respiratory Syndrome, Corona Virus Disease 19 And Omicron Pandemic Era: An Original Research

Linguistic Creativity and Formal Thought Disorder in Schizophrenia

Linguistic Creativity and Formal Thought Disorder in Schizophrenia

Daily temperature variability and mental health-related hospital visits in New York State

BackgroundDespite plausible behavioral and physiological pathways, limited evidence exists on how daily temperature variability is associated with acute mental health-related episodes. ObjectivesWe aimed to explore associations between daily temperature range (DTR) and mental health-related hospital visits using data of all hospital records in New York State during 1995–2014. We further examined factors that may modify these associations, including age, sex, hospital visit type and season. MethodsUsing a case-crossover design with distributed lag non-linear DTR terms (0–6 days), we estimated associations between ZIP Code-level DTR and hospital visits for mood (4.6 million hospital visits), anxiety (2.4 million), adjustment (∼368,000), and schizophrenia disorders (∼211,000), controlling for daily mean temperature, via conditional logistic regression models. We assessed potential heterogeneity by age, sex, hospital visit type (in-patient vs. out-patient), and season (summer, winter, and transition seasons). ResultsFor all included outcomes, we observed positive associations from period minimum DTR (0.1 °C) until 25th percentile (5.2 °C) and between mean DTR (7.7 °C) and 90th percentile (12.2 °C), beyond which we observed negative associations. For mood disorders, an increase in DTR from 0.1 °C to 12.2 °C was associated with a cumulative 16.0% increase (95% confidence interval [CI]: 12.8, 19.2%) in hospital visit rates. This increase was highest during transition seasons (32.5%; 95%CI: 26.4, 39.0%) compared with summer (10.7%; 95%CI: 4.8, 16.8%) and winter (−1.6%; 95%CI: −7.6, 4.7%). For adjustment and schizophrenia disorders, the strongest associations were seen among the youngest group (0–24 years) with almost no association in the oldest group (65+ years). We observed no evidence for modification by sex and hospital visit type. DiscussionDaily temperature variability was positively associated with mental health-related hospital visits within specific DTR ranges in New York State, after controlling for daily mean temperature. Given uncertainty on how climate change modifies temperature variability, additional research is crucial to comprehend the implications of these findings, particularly under different scenarios of future temperature variability.

A confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer's disease using resting-state functional network connectivity.

Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer's disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it is also of interest to directly compare AD and SZ patients with each other to identify potential biomarkers shared between the disorders. However, comparing patient groups collected in different studies can be challenging due to potential confounds, such as differences in the patient's age, scan protocols, etc. In this study, we compared and contrasted resting-state functional network connectivity (rs-FNC) of 162 patients with AD and late mild cognitive impairment (LMCI), 181 schizophrenia patients, and 315 cognitively normal (CN) subjects. We used confounder-controlled rs-FNC and applied machine learning algorithms (including support vector machine, logistic regression, random forest, and k-nearest neighbor) and deep learning models (i.e., fully-connected neural networks) to classify subjects in binary and three-class categories according to their diagnosis labels (e.g., AD, SZ, and CN). Our statistical analysis revealed that FNC between the following network pairs is stronger in AD compared to SZ: subcortical-cerebellum, subcortical-cognitive control, cognitive control-cerebellum, and visual-sensory motor networks. On the other hand, FNC is stronger in SZ than AD for the following network pairs: subcortical-visual, subcortical-auditory, subcortical-sensory motor, cerebellum-visual, sensory motor-cognitive control, and within the cerebellum networks. Furthermore, we observed that while AD and SZ disorders each have unique FNC abnormalities, they also share some common functional abnormalities that can be due to similar neurobiological mechanisms or genetic factors contributing to these disorders' development. Moreover, we achieved an accuracy of 85% in classifying subjects into AD and SZ where default mode, visual, and subcortical networks contributed the most to the classification and accuracy of 68% in classifying subjects into AD, SZ, and CN with the subcortical domain appearing as the most contributing features to the three-way classification. Finally, our findings indicated that for all classification tasks, except AD vs. SZ, males are more predictable than females.

Processing speed in first episode of psychosis and first-degree relatives: A candidate endophenotype of spectrum schizophrenia disorders.

The processing speed (PS) is highly impacted in individuals experiencing their first episode of psychosis (FEP). Conducting family studies can help to determine whether PS can serve as an endophenotype of schizophrenia spectrum disorders (SSDs), offering valuable insights into the prevention and diagnosis of SSDs. A comprehensive cognitive battery, encompassing tests for PS, verbal memory, visual memory, working memory, executive functions, motor dexterity, and attention, was administered to a sample consisting of 133 FEP patients, 146 parents, 98 siblings, and 202 healthy controls (HCs). Univariate analyses (analysis of covariance [ANCOVA]) were conducted to compare the different cognitive domains between groups, utilizing sex, age, and years of education as covariates and Bonferroni corrections. Effect sizes (ESs) were calculated for estimating the magnitude of differences between groups. Group comparisons revealed significant differences in all cognitive domains. PS was the most impaired function in patients. Parents and siblings had intermediate PS performance between FEP patients and HC. Large ES were observed in PS between FEP versus siblings, FEP versus controls, parents versus controls, and parents versus siblings. Despite not meeting all the necessary criteria, the PS observed in FEP patients and their first-degree relatives suggests its potential as a promising endophenotype of SSDs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring the Role of Complexity in Health Care Technology Bottom-Up Innovations: Multiple-Case Study Using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability Complexity Assessment Tool.

New digital technology presents new challenges to health care on multiple levels. There are calls for further research that considers the complex factors related to digital innovations in complex health care settings to bridge the gap when moving from linear, logistic research to embracing and testing the concept of complexity. The nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework was developed to help study complexity in digital innovations. This study aims to investigate the role of complexity in the development and deployment of innovations by retrospectively assessing challenges to 4 digital health care innovations initiated from the bottom up. A multicase retrospective, deductive, and explorative analysis using the NASSS complexity assessment tool LONG was conducted. In total, 4 bottom-up innovations developed in Region Västra Götaland in Sweden were explored and compared to identify unique and shared complexity-related challenges. The analysis resulted in joint insights and individual learning. Overall, the complexity was mostly found outside the actual innovation; more specifically, it related to the organization's readiness to integrate new innovations, how to manage and maintain innovations, and how to finance them. The NASSS framework sheds light on various perspectives that can either facilitate or hinder the adoption, scale-up, and spread of technological innovations. In the domain of condition or diagnosis, a well-informed understanding of the complexity related to the condition or illness (diabetes, cancer, bipolar disorders, and schizophrenia disorders) is of great importance for the innovation. The value proposition needs to be clearly described early to enable an understanding of costs and outcomes. The questions in the NASSS complexity assessment tool LONG were sometimes difficult to comprehend, not only from a language perspective but also due to a lack of understanding of the surrounding organization's system and its setting. Even when bottom-up innovations arise within the same support organization, the complexity can vary based on the developmental phase and the unique characteristics of each project. Identifying, defining, and understanding complexity may not solve the issues but substantially improves the prospects for successful deployment. Successful innovation within complex organizations necessitates an adaptive leadership and structures to surmount cultural resistance and organizational impediments. A rigid, linear, and stepwise approach risks disregarding interconnected variables and dependencies, leading to suboptimal outcomes. Success lies in embracing the complexity with its uncertainty, nurturing creativity, and adopting a nonlinear methodology that accommodates the iterative nature of innovation processes within complex organizations.

Impact of Patients’ Motivation and Scheme of Positive and Negative Symptoms among Patients with Psychotic Disorders

Positive motivations toward treatment are an important factor that plays a significant role in the treatment outcomes and patients' recovery process. The present study investigates the impact of patients’ motivation toward treatment and its impact on patients positive, negative, and general psychopathological symptoms among patients with psychosis. A total of 200 participants diagnosed with psychotic disorders were approached from different hospitals and clinics in Faisalabad and Karachi. 11 out of 200 participants were excluded due to comorbid conditions and unclarity in diagnostic symptoms. 189 participants met the inclusion and exclusion criteria of the study. Both male 112(59.26%) and females 77(40.74%). patients were included in this study. Participants were taken from all socioeconomic statuses. Participants’ age range was between 20 to 45 years with M±SD=34.53±2.57. Findings show that patients a significant difference was estimated in positive, negative and general psychopathological symptoms between patients with low motivation and high motivation. Furthermore, results indicate that a significant difference was estimated in positive, negative and general psychopathological symptoms between patients with schizophrenia disorder and other psychotic disorders among patients with psychotic disorders. It is concluded that low motivation toward treatment is suspected a lower chance of engagement in treatment as compared to those who have high motivation. Patients with schizophrenia disorder perceived relevantly high symptom severity on positive, negative, and general psychopathological symptoms as compared to other psychotic disorders.

The Correlation Between Peripheral Blood Micro-Ribonucleic Acid Expression Level and Personality Disorder in Patients with Schizophrenia.

Schizophrenia patients often have personality disorders; schizophrenia patients with personality disorders are more difficult to treat and have a worse prognosis. Early identification of this group of patients and early intervention can achieve better prognosis. Therefore, it is very important to explore effective biomarkers and early diagnosis for the prognosis of schizophrenia. The primary purpose of this paper is to explore the relationship between plasma miRNA expression level and personality disorder with schizophrenia. Gene microarrays in miRNA files were employed, and the plasma of peripheral blood of 82 schizophrenic patients and 43 healthy control subjects were examined. Real-time reverse transcription polymerase chain reaction detection were performed to explore the results. Spearman correlation analysis was used to analyze the correlation between expression level of miRNAs and Personality Diagnosis Questionnaire-4 score. The results showed that miR-1273d, miR-1303, miR-3064-5p, miR-3131, miR-3687, miR-4428, miR-4725-3p, and miR-5096 were up-regulated in schizophrenic patients. Compared to healthy control subjects, the difference was statistically significant (P < .05). Schizophrenic patients with schizoid, paranoid, schizotypal, and obsessive compulsive traits had negative correlation with miR-1303, miR-3131, miR-4428, and miR-5096 expression level (r = -0.40 to -0.62, P < .05); there were no significant differences in the other miRNAs. Correlation with other personality traits was not significant (P > .05). The stepwise regression analysis indicated that miR-5096, miR-3131, and miR-1273d have a significant predictive effect on the schizoid trait (P < .01). MiR-4428 and miR-1303 had a significant predictive effect on the schizotypal trait (P < .01). MiR-5096, miR-4428, and miR-4725-3P had a significant predictive effect on the paranoid trait (P < .05). MiR-4428, miR-1303, and miR-5096 had a significant predictive effect on the obsessive compulsive trait (P < .05). The expression levels of miR-1273d, miR-1303, miR-3064-5p, miR-3131, miR-3687, miR-4428, miR-4725-3p, and miR-5096 were up-regulated in the peripheral blood of patients with schizophrenia, and these miRNAs are expected to be diagnostic biomarkers for accurate diagnosis of schizophrenia. The expression levels of miR-1303, miR-3131, miR-1273d, miR-4428, miR-4725-3p, and miR-5096 have significant predictive effects on personality disorder in schizophrenia.

The Swedish version of the Motivation and Pleasure Scale self-report (MAP-SR): psychometric properties in patients with schizophrenia or depression

Purpose Negative symptoms are commonly regarded as a symptom dimension belonging to schizophrenia spectrum disorders but are also present in depression. The recently developed Clinical Assessment Interview for Negative Symptoms (CAINS) has shown to be reliable and valid. A corresponding self-report questionnaire has also been developed, named the Motivation and Pleasure Scale - Self Report (MAP-SR). The purpose was to evaluate the psychometric properties of the Swedish version of the MAP-SR in patients with either schizophrenia or depression. Materials and Methods The MAP-SR was translated to Swedish. Participants were 33 patients with schizophrenia spectrum disorders and 52 patients with a depressive disorder and they completed the MAP-SR, the CAINS and other measures assessing adjacent psychopathology, functioning and cognition. Results The internal consistency for the MAP-SR was adequate in both groups (schizophrenia spectrum α = .93, depressive disorder α = .82). Furthermore, the MAP-SR had a large correlation to the motivation and pleasure subscale of the CAINS in patients with schizophrenia disorders (r = −0.75, p < .001), however among patients with depression this correlation was medium-to-large (r = −0.48, p < 0.001). Conclusions Findings suggest that the Swedish version of the MAP-SR shows promise as a useful measure of motivation and pleasure, especially in patients with schizophrenia spectrum disorders. Furthermore, results also suggest that the MAP-SR does not assess negative symptoms specifically, but that there is an overlap between depressive and negative symptoms.

Association of antiseizure medications and adverse cardiovascular events: A global health federated network analysis.

A diagnosis of epilepsy has been associated with adverse cardiovascular events (CEs), but the extent to which antiseizure medications (ASMs) may contribute to this is not well understood. The aim of this study was to compare the risk of adverse CEs associated with ASM in patients with epilepsy (PWE). A retrospective case-control cohort study was conducted using TriNetX, a global health federated network of anonymized patient records. Patients older than 18 years, with a diagnosis of epilepsy (International Classification of Diseases, 10th Revision code G40) and a medication code of carbamazepine, lamotrigine, or valproate were compared. Patients with cardiovascular disease prior to the diagnosis of epilepsy were excluded. Cohorts were 1:1 propensity score matched (PSM) according to age, sex, ethnicity, hypertension, heart failure, atherosclerotic heart disease, atrial and cardiac arrythmias, diabetes, disorders of lipoprotein metabolism, obesity, schizophrenia and bipolar disorder, medications, and epilepsy classification. The primary outcome was a composite of adverse CEs (ischemic stroke, acute ischemic heart disease, and heart failure) at 10 years. Cox regression analyses were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) following 1:1 PSM. Of 374 950 PWE included; three cohorts were established after PSM: (1) carbamazepine compared to lamotrigine, n = 4722, mean age 37.4 years; (2) valproate compared to lamotrigine, n = 5478, mean age 33.9 years; and (3) valproate compared to carbamazepine, n = 4544, mean age 37.0 years. Carbamazepine and valproate use were associated with significantly higher risk of composite cardiovascular outcome compared to lamotrigine (HR = 1.390, 95% CI = 1.160-1.665 and HR = 1.264, 95% CI = 1.050-1.521, respectively). Valproate was associated with a 10-year higher risk of all-cause death than carbamazepine (HR = 1.226, 95% CI = 1.017-1.478), but risk of other events was not significantly different. Carbamazepine and valproate were associated with increased CE risks compared to lamotrigine. Cardiovascular risk factor monitoring and careful follow-up should be considered for these patients.

A deep learning approach for diagnosis of schizophrenia disorder via data augmentation based on convolutional neural network and long short-term memory.

Schizophrenia (SZ) is a severe, chronic mental disorder without specific treatment. Due to the increasing prevalence of SZ in societies and the similarity of the characteristics of this disease with other mental illnesses such as bipolar disorder, most people are not aware of having it in their daily lives. Therefore, early detection of this disease will allow the sufferer to seek treatment or at least control it. Previous SZ detection studies through machine learning methods, require the extraction and selection of features before the classification process. This study attempts to develop a novel, end-to-end approach based on a 15-layers convolutional neural network (CNN) and a 16-layers CNN- long short-term memory (LSTM) to help psychiatrists automatically diagnose SZ from electroencephalogram (EEG) signals. The deep model uses CNN layers to learn the temporal properties of the signals, while LSTM layers provide the sequence learning mechanism. Also, data augmentation method based on generative adversarial networks is employed over the training set to increase the diversity of the data. Results on a large EEG dataset show the high diagnostic potential of both proposed methods, achieving remarkable accuracy of 98% and 99%. This study shows that the proposed framework is able to accurately discriminate SZ from healthy subject and is potentially useful for developing diagnostic tools for SZ disorder.