Diagnosis Of Schizophrenia Research Articles

Perceived stress and delay discounting in schizophrenia, cannabis use disorder, and co-occurring disorders

Steeper delay discounting (DD) reflects greater impulsivity and has been reported in individuals with schizophrenia (SCZ) and those with substance use disorder, who also tend to report high psychological stress. We sought to compare DD in people with SCZ, cannabis use disorder (CUD), and comorbid SCZ-CUD, and determine its relationship to psychological stress in these groups, to inform treatment improvements. Participants were healthy controls (HC; n = 31) and individuals with DSM-IV diagnoses of SCZ (n = 21), CUD (n = 61), and comorbid SCZ-CUD (n = 40). After one week or more of verified abstinence from substances, participants completed the Delay Discounting Questionnaire and the Perceived Stress Scale. DD and perceived stress were greater in all three clinical groups compared to HC, though the clinical groups did not differ. Analyses did not detect a consistent relationship between stress and DD in any group, though females showed greater DD with increased stress when all clinical groups were combined. Findings indicate that, overall, perceived stress cannot account for steeper DD in patients with SCZ, CUD, and SCZ-CUD; thus, interventions for stress would not be expected to impact DD.

Protein Profiles and Novel Molecular Biomarkers of Schizophrenia Based on 4D-DIA Proteomics.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

The complex lived experience of schizophrenia diagnosis: a thematic analysis of online forum posts

Receiving a diagnosis of schizophrenia can be a life-changing experience with both negative and positive consequences. Previous research has identified important aspects of diagnosis, such as disagreement with the label, diagnostic shifts, stigma, and communication of the diagnosis. There is, however, relatively little research from the lived experience perspective. In this study, we investigated the lived experiences of receiving a schizophrenia diagnosis utilising a popular Reddit discussion forum. We used inductive thematic analysis to consider posts from 105 unique usernames and identified five themes. These were (i) Denial and acceptance; (ii) Stigma of diagnosis and selective disclosure; (iii) The complicated process of diagnosis; (iv) Losing, maintaining, and finding a sense of self; and (v) Receiving, finding, and providing support. Diagnosis is a complex personal experience where the same person can simultaneously accept and reject the diagnostic label. Greater attention is required to the lived experience of this diagnostic journey.

Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry

The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medical imaging tasks, such as image segmentation. However, for single-subject prediction problems, recent studies yielded contradictory results when comparing DL with Standard Machine Learning (SML) on top of classical feature extraction. Most existing comparative studies were limited in predicting phenotypes of little clinical interest, such as sex and age, and using a single dataset. Moreover, they conducted a limited analysis of the employed image pre-processing and feature selection strategies. This paper extensively compares DL and SML prediction capacity on five multi-site problems, including three increasingly complex clinical applications in psychiatry namely schizophrenia, bipolar disorder, and Autism Spectrum Disorder (ASD) diagnosis. To compensate for the relative scarcity of neuroimaging data on these clinical datasets, we also evaluate three pre-training strategies for transfer learning from brain imaging of the general healthy population: self-supervised learning, generative modeling and supervised learning with age. Overall, we find similar performance between randomly initialized DL and SML for the three clinical tasks and a similar scaling trend for sex prediction. This was replicated on an external dataset. We also show highly correlated discriminative brain regions between DL and linear ML models in all problems. Nonetheless, we demonstrate that self-supervised pre-training on large-scale healthy population imaging datasets (N≈10k), along with Deep Ensemble, allows DL to learn robust and transferable representations to smaller-scale clinical datasets (N≤1k). It largely outperforms SML on 2 out of 3 clinical tasks both in internal and external test sets. These findings suggest that the improvement of DL over SML in anatomical neuroimaging mainly comes from its capacity to learn meaningful and useful abstract representations of the brain anatomy, and it sheds light on the potential of transfer learning for personalized medicine in psychiatry

Risk prevalence, readiness and confidence to change lifestyle risk factors among clients of community mental health services.

People with mental health conditions have high rates of chronic physical diseases, partially attributable to lifestyle risks factors. This study examined risk prevalence among community mental health service clients, their readiness and confidence to change, and associations with participant characteristics. Cross-sectional survey of adult clients from 12 community mental health services across 3 local health districts in New South Wales, Australia, collected from 2021 to 2022. Participants (n = 486) completed a telephone interview determining five risk factors, and readiness and confidence to change these. Multiple binary logistic regression models determined associations between readiness and confidence (for each risk), and participant characteristics (demographics and diagnosis). Participants most commonly reported a diagnosis of schizophrenia (36.7%) or depression (21.1%). Risk factors were prevalent: ranging from 26% (harmful alcohol use) to 97% (poor nutrition). High readiness was greatest for smoking (68%), weight (66%) and physical inactivity (63%), while confidence was highest for changing alcohol use (67%). Two significant associations were identified; females were more likely than males to have high readiness to change nutrition (odds ratio = 1.14, confidence interval = [1.13, 2.34], p = 0.0092), with males more likely to have high confidence to change physical activity (odds ratio = 0.91, confidence interval = [0.45, 0.99], p = 0.0109). Many participants were ready and confident to change risk factors. Gender influenced readiness to change nutrition and physical activity confidence. Training to upskill mental health clinicians in provision of preventive care that builds confidence and readiness levels may aid in supporting positive behaviour change.

Diagnosis of Schizophrenia and Psychosis in Māori People Using Speech Assay: A Natural Language Processing Approach

Indigenous peoples and ethnic minorities worldwide have a higher incidence of psychosis, primarily schizophrenia. In New Zealand, Māori individuals experience greater rates of anxiety and depression compared to non-Māori, with a significantly higher incidence of mental illness among Māori. We propose natural language processing (NLP) trained on speech samples from Māori patients as a potential solution to the problem of culturally biased psychometric screening tools for psychosis and schizophrenia. This research examines NLP's ability to diagnose psychosis in Māori patients by analysing speech and language abnormalities as indicators of severe mental illnesses such as schizophrenia. Our research emphasizes the need for inclusive language models and investigates cross-cultural applicability. We employed a three-part method: conducting clinical interviews, pre-processing data with the Natural Language Toolkit (NLTK) and applying language classifiers. The study's results demonstrate the promise of NLP, but limited patient data necessitates further research, including standardizing datasets and integrating NLP with indigenous languages. This research represents a step towards improving diagnostic accuracy and support for Māori people suffering from psychosis, aligning with healthcare's goal of fair and culturally responsive mental health screening.

Sex differences in patient-reported outcome measure of psychotic symptoms in schizophrenia.

to study sex differences in self-reported symptoms measured with the Scale of Patient-Reported Impact of Symptoms in Schizophrenia (PRISS), to investigated sex differences in the degree of agreements between self-reported symptoms and clinical symptoms assessed by professionals, and to identify which clinical and sociodemographic variables predicted a greater presence of self-reported symptoms split by sex. 161 patients (37 females; 124 males), aged between 18 and 65 years, with a diagnosis of schizophrenia assisted in non-acute mental health services at four mental health catchment areas in Andalucia and Catalonia were included. The PRISS scale was administered to asses self-reported symptoms. males reported higher presence of excitement, grandiosity, motor retardation and poor attention) than women. There was less agreement in the presence of psychotic symptoms in men than in women when comparing self-reported symptoms and clinical symptoms assessed by professionals. Finally, in men the predictors variables for the greater presence of self-perceived symptoms were greater psychotic symptomatology and more disability, while in women were greater presence of alogia and higher doses of chlorpromazine. Assessing and being aware of the self-perceived symptoms of patients with schizophrenia should be considered in the clinic, especially in men, as there appears to be a lack of agreement on certain items. This would allow treatments to be more focused on patients' need by sex, and would make them feel part of the therapeutic process, improving their therapeutic adherence, evolution and quality of life.

Anti-spike antibody responses to SARS-CoV-2 mRNA vaccines in people with schizophrenia and schizoaffective disorder

ImportanceIndividuals with schizophrenia are at higher risk for severe COVID-19 illness and severe breakthrough infection following vaccination. It is unclear whether immune response to vaccination differs in this population. ObjectiveTo assess whether anti-SARS-CoV-2 spike antibody titers after vaccination differ in people with a diagnosis of schizophrenia or schizoaffective disorder (SZ) compared to controls without a psychiatric disorder. DesignThis cohort study assessed antibody response following the first and second dose of mRNA vaccines at longitudinal timepoints, up to 7 weeks following the first dose of vaccine. SettingA multi-center study including psychiatric healthcare settings in the United States and Europe. Participants205 adults with no history of COVID-19 infection, including 106 individuals with SZ and 99 controls without a psychiatric disorder, who received their first dose of SARS-CoV-2 mRNA vaccine between December 20, 2020 and May 27, 2021. Main outcomes and measuresMean SARS-CoV-2 anti-Spike IgG antibody levels within 7 weeks after the first dose of vaccination. ResultsA total of 205 individuals (mean [SD] age, 44.7 [12.0] years; 90 [43.9%] male) were included, of which 106 (51.7%) were diagnosed with SZ. SZ was associated with lower mean log antibody levels (−0.15; 95% CI, −0.27 to −0.03, P = 0.016) after adjusting for age, sex, body mass index, smoking, days since vaccination, and vaccine manufacturer. In secondary analyses of dose-specific responses, SZ was associated with a lower mean log antibody level after the second dose of vaccine (−0.23; 95% CI -0.39 to −0.06, P = 0.006), but not the first dose of vaccine (0.00; 95% CI -0.18— 0.19, P = 0.96). Conclusions and RelevanceIn this cohort study of individuals with SZ and a control group without psychiatric disorders, SZ was associated with lower SARS-CoV-2 anti-spike antibody levels following 2 doses of SARS-CoV-2 mRNA vaccination. This highlights the need for further studies assessing vaccine immunogenicity in individuals with schizophrenia.

Electroconvulsive therapy in a tertiary Australian mental health facility between 2009 and 2020.

Despite electroconvulsive therapy being one of the most effective treatments in psychiatry, few studies report trends in the provision of electroconvulsive therapy over time. This study aims to investigate the use of electroconvulsive therapy between 2009 and 2020 in an Australian public tertiary mental health facility, and to describe the electroconvulsive therapy patient population and change in courses of treatment. Routinely collected data for 677 patients who received 1669 electroconvulsive therapy courses of treatment at an Australian public tertiary mental health facility between 2009 and 2020 were examined. The provision of acute electroconvulsive therapy was stable across the study period; however, the number of maintenance electroconvulsive therapy courses commenced declined over the study. Schizophrenia was the most common indication for index treatment (37.4%). The majority of patients (85.7%) received acute electroconvulsive therapy only. Voluntary provision of electroconvulsive therapy declined over the study period, reducing from 44.9% in 2009 to 16.3% in 2020. Over the study period, there was a significant reduction in the number of maintenance electroconvulsive therapy courses commenced, and a large increase in involuntary treatment. The provision of electroconvulsive therapy was more likely to occur in males with a diagnosis of schizophrenia. Further studies are needed to generate a greater understanding of the factors influencing the provision of electroconvulsive therapy within differing geographical, social and healthcare landscapes.

Evaluation of Language Dysfunction among Untreated Patients with Psychosis Attending the Psychiatry Inpatient Services of a Tertiary Healthcare Centre from North India: A Cross-sectional Study

Background: Psychosis, encompassing conditions such as schizophrenia and bipolar affective disorder with psychotic features, presents a perplexing landscape where language dysfunction emerges as a notable hallmark. Compared to classical psychotic symptoms (such as delusions and hallucinations), language disorganization can be directly observed, and it is not dependent upon subjective reports of abnormal experiences on part of the patient. Consequently, it has been regarded by researchers as a more objective and informative clinical marker of brain dysfunction in psychosis. There is a dearth of Indian studies in this domain and when compared to international studies, a strong need for revival of research has been felt. Aim: To evaluate language dysfunction among first-admission untreated patients of psychosis using the clinical language disorder rating scale (CLANG). Methodology: In this cross-sectional study, language dysfunction among 60 untreated psychotic patients who attended the psychiatry inpatient services of a tertiary care center from North India in the period from January 2022 to October 2023 were evaluated for the presence of language dysfunction using a valid tool called CLANG after taking approval from the Institutional Ethical Committee and with the informed consent of the patients and/or their caregivers. Data set for 60 patients regarding the sociodemographic-clinical profile and language dysfunction was obtained. The data was analyzed using descriptive and inferential statistics as appropriate. Results: Diagnosis-wise, most of our patients belonged to schizophrenia (n = 26) (43.33%). Rest of them psychotic disorders like bipolar affective disorder with psychotic symptoms (15%) and schizoaffective disorder (11.67%) to name a few. The most commonly affected language domains in our patients were referential failures (65%), discourse failures (46.67%) and lack of semantic association (16.67%). Schizophrenics were differentiated from non-schizophrenic psychosis patients based on lack of semantic association (exclusively seen in schizophrenics). Referential failures and discourse failures were commonly noted in both schizophrenia and non-schizophrenic psychotic disorders. Poverty of speech was rather predominant in mood disorders with psychotic symptoms. Conclusion: The findings of our study put emphasis on the fact that language dysfunction is a core component of the phenomenon of psychosis and perhaps revalidates the neural basis of psychosis. The domain ‘lack of semantic association’ was typically present in patients with a diagnosis of schizophrenia, while other language abnormalities like referential failures and abnormal prosody were generally present in patients of untreated psychosis.

Human Brain Aging is Associated with Dysregulation of Cell-Type Epigenetic Identity.

Significant links between aging and DNA methylation are emerging from recent studies. On the one hand, DNA methylation undergoes changes with age, a process termed as epigenetic drift. On the other hand, DNA methylation serves as a readily accessible and accurate biomarker for aging. A key missing piece of information, however, is the molecular mechanisms underlying these processes, and how they are related, if any. Addressing the limitations of previous research due to the limited number of investigated CpGs and the heterogeneous nature of tissue samples, here we have examined DNA methylation of over 20 million CpGs across a broad age span in neurons and non-neuronal cells, primarily oligodendrocytes. We show that aging is a primary predictor of DNA methylation variation, surpassing the influence of factors such as sex and schizophrenia diagnosis, among others. On the genome-wide scale, epigenetic drift manifests as significant yet subtle trends that are influenced by the methylation level of individual CpGs. We reveal that CpGs that are highly differentiated between cell types are especially prone to age-associated DNA methylation alterations, leading to the divergence of epigenetic cell type identities as individuals age. On the other hand, CpGs that are included in commonly used epigenetic clocks tend to be those sites that are not highly cell type differentiated. Therefore, dysregulation of epigenetic cell-type identities and current DNA epigenetic clocks represent distinct features of age-associated DNA methylation alterations.

Dopamine D2 receptor antagonism of antipsychotics and the risk of death due to choking

The risk of fatal choking for people with schizophrenia and associations with antipsychotic medication are largely unknown. Therefore, we calculated the choking-related standardized mortality ratio for schizophrenia relative to the general population (SMRchoking). We also computed adjusted hazard ratios (aHR) of choking-related mortality for antipsychotics in a nationwide cohort of patients with schizophrenia (N = 59,916). SMRchoking was 20.5 (95 % confidence interval (CI)=17.1–23.9). The aHR was 1.74 (95 %CI=1.19–2.55) for strong dopamine 2-antagonists. For other antipsychotics, CIs included 1. Importantly, aHRs were particularly high for high dose categories of strong dopamine D2 receptor (D2R) antagonists. In conclusion, a schizophrenia diagnosis is associated with a 20-fold risk of death due to choking. This risk is elevated during use of strong D2R antagonist antipsychotics, particularly when prescribed in high dosages.

Adherence, health care utilization, and costs between long-acting injectable and oral antipsychotic medications in South Carolina Medicaid beneficiaries with schizophrenia.

Schizophrenia and schizoaffective disorder require long-term antipsychotic treatment with antipsychotic medications, but poor medication adherence can lead to increased health care utilization and costs. Long-acting injectable antipsychotics (LAIs) offer potential therapeutic advantages in that they require less frequent dosing and improved medication adherence. South Carolina has the highest adoption of LAIs among US states, making it an ideal population for comparing the effectiveness of LAIs vs oral antipsychotics (OAPs) in treating schizophrenia or schizoaffective disorder. To evaluate the effect of LAIs compared with OAPs on medication adherence, health care resource utilization, and costs among South Carolina Medicaid beneficiaries with schizophrenia or schizoaffective disorder. South Carolina Medicaid beneficiaries with at least 1 claim for an LAI or OAP between January 1, 2015, and December 31, 2018, aged 18 to 65, with at least 2 claims with diagnoses of schizophrenia or schizoaffective disorder were included. Propensity scores (PSs) were calculated using logistic regression adjusting for confounders and predictors of the outcome. We estimated the "average treatment effect on the treated" by employing PS-weighted t-tests and chi-square tests. A total of 3,531 patients met the inclusion criteria, with 1,537 (44.5%) treated with LAIs and 1,994 (56.5%) treated with OAPs. In PS-weighted analyses, the LAI cohort had a greater proportion of days covered than the OAP cohort with a 365-day fixed denominator (69% vs 64%; P < 0.0001), higher medication possession ratio with a variable denominator while on therapy (85% vs 80%; P < 0.0001), and higher persistence (82% vs 64%; P < 0.0001). The average number of inpatient visits and emergency department visits did not significantly differ between cohorts (0.28 hospitalizations, P = 0.90; 3.68 vs 2.96 emergency department visits, P = 0.19). The number of outpatient visits, including visits for medication administration, were greater in the LAI cohort (23.1 [SD 24.2]) vs OAP (16.9 [SD 21.2]; P < 0.0001); however, including the costs for medication administration visits, outpatient costs (per member) were approximately $2,500 lower in the LAI cohort (P < 0.0001). The number of pharmacy visits was greater in the OAP cohort (LAI 21.0 [SD 17.0] vs OAP 23.0 [SD 15.0]; P = 0.006). All-cause total costs were greater in the LAI cohort ($26,025 [SD $29,909]) vs the OAP cohort ($17,291 [SD $25,261]; P < 0.0001) and were driven by the difference in pharmaceutical costs (LAI $15,273 [SD $16,183] vs OAP $4,696 [SD $10,371]; P < 0.0001). Among South Carolina Medicaid beneficiaries, treatment with LAIs for schizophrenia or schizoaffective disorder was associated with greater medication adherence rates. Patients using LAIs had higher drug costs and total costs, but lower outpatient and total nondrug costs compared with those using OAPs.

Pengaruh Art Therapy (Painting) dengan Media Tote Bag terhadap Self Efficacy pada Pasien Skizofrenia di RSJD Dr. Amino Gondohutomo Provinsi Jawa Tengah

Abstract Background: Schizophrenia is a group of psychotic symptoms that affect different areas of the functioning of a person. Schizophrenics will experience impaired social functioning that is influenced by self-efficacy. Self-efficacy is a very important motivating factor to achieve success. One of the non-pharmacological therapies that can be given is art therapy (painting). Objectives: This study was used to determine the effect of art therapy (painting) with tote bag media on self-efficacy in schizophrenia patients at RSJD Dr. Amino Gondohutomo Province of Central Java. Methods: This research is a pre-experimental quantitative research with one group pre and post-test design. The sampling technique uses purposive sampling with a population of 35 samples. Self-efficacy was measured using the Indonesian version of the General Self-Efficacy Scale (GSES) instrument. Hypothesis testing uses the Wilcoxon test. Results: The results showed that the age was predominantly late adulthood (45.7%), the majority were female (65.7%), the work history was predominantly non-working (37.1%), the majority of the sample had a marital status of being unmarried (60.0%), education level was dominated by SMA/MAN/SMK (42.9%), and the majority of the sample had an unspecified diagnosis of schizophrenia (65.7%). The average pre-test score is 21.91 and the post-test score is 29.89 with a difference of 7.98, which means there are differences in the results of the self-efficacy examination in the research sample. The results of this research were measured using the Wilcoxon test, obtaining a p-value of 0.000 (p-value &lt;0.05). Conclusion Activities of art therapy (painting) with tote bag media influence self-efficacy in schizophrenia patients at RSJD Dr. Amino Gondohutomo Province of Central Java. It is hoped that the results of this research can become a routine therapeutic activity for schizophrenia patients at RSJD Dr. Amino Gondohutomo Province of Central Java. Keywords : Art Therapy (Painting), Self Efficacy, Schizophrenia

Reduction of DUP in early intervention programmes: No pain… almost no gain.

Considering the negative impact of long duration of untreated psychosis (DUP) on outcome, its reduction has become one of the aims of early intervention programmes. The TIPP programme (Treatment and early Intervention in Psychosis Program) was implemented in 2004 in Lausanne and hoped to reduce DUP, without any specific campaign in this regard, through the provision of accessible and specialized treatment. The aim of this study was to evaluate the evolution of patients' DUP over time and the characteristics of patients with extreme DUP. Clinical follow-up data of 380 patients aged 18-35 years with a first psychotic episode who entered the TIPP programme between 2004 and 2017 were analysed. The evolution of DUP over time as well as referring entities and destination after the programme were assessed. The characteristics of patients with extreme DUPs (>percentile 90) were compared with that of other patients. The mean value of the DUP was 452.11 days with a median of 88 days. DUP decreased only moderately over time. We also observe a decrease in discharges to specialized outpatient care at our university hospital. The main characteristics of patients with extreme DUP were early age of onset of psychosis, diagnosis of schizophrenia and presence of history of psychiatric treatment for other conditions before onset of psychosis. These figures suggest that the DUP has reduced over time but that without specific interventions at this level, this reduction is only moderate.

#841 Healthcare workload amongst people with chronic kidney disease: what impact do mental disorders have?

Abstract Background and Aims People with chronic kidney disease (CKD) often experience a high healthcare workload in the form of medication management, contacts with healthcare services, and other tasks. Co-existing health conditions can increase healthcare workload, with mental disorders generating additional workload alongside physical conditions. We hypothesised that mental disorders in people with CKD would be common and that healthcare workload would be elevated for people with mental disorders. Method Data were used from the Secure Anonymised Information Linkage Databank: primary care data for people living in Wales, UK, with linkage to hospital records. We studied adults over the age of 18 with CKD G3-5 not on kidney replacement therapy. We defined “mental disorder” as any primary care-recorded diagnosis of anxiety, depression, eating disorders, schizophrenia, and/or bipolar disorder. We estimated healthcare workload by quantifying visits to accident and emergency (A&amp;E), days spent in hospital during emergency admissions (general hospitals and psychiatric hospitals), number of outpatient clinic appointments, locations of clinic appointments, and number of long-term medications prescribed. We estimated associations between mental disorders and healthcare workload using negative binomial models, making adjustments for age, sex, diabetes, ischaemic heart disease, smoking status, and socioeconomic deprivation. Results Of 173 388 people with CKD, mean age was 77 years, 54 537 (31.5%) had one or more mental disorder and 20 374 (11.8%) had two or more. Over a median follow-up period of 5.5 years, people with CKD and mental disorders spent a median 1.9 days in hospital (interquartile interval [IQI] 0.0 to 14.7) compared to people with CKD without mental disorders: 1.0 (IQI 0.0 to 9.9) days. People with CKD and mental disorders attended a median of 2.6 clinics (IQI 1.0 to 5.5) compared to people with CKD without mental disorders: 2.3 (IQI 0.8 to 4.9). The presence of any mental disorder was associated with more days spent in hospital: adjusted rate ratio (aRR) 1.58 (95% confidence interval 1.54-1.62), more A&amp;E attendances: aRR 1.37 (1.35-1.39) and more clinic appointments: aRR 1.13 (1.11-1.14). The association with hospital days was strongest for people with eating disorders: aRR 3.70 (2.50-5.49). People with any mental disorder attended a similar number of locations for clinics than those without mental disorders: median 2 for both groups (IQI 1 to 3). However, people with schizophrenia, bipolar disorder or eating disorders attended more locations: median 3 (IQI 2 to 4). People with mental disorders took more medications (median 9: IQI 6 to 13) than those without mental disorders (median 7: IQI 4 to 10). Conclusion Mental disorders are common amongst people with CKD and healthcare workload is greater for people with than without mental disorders. Although a proportion of the increased healthcare workload might be expected (such as people taking medications for their mental health), the additional days spent in hospital is a notable finding. This may reflect problems with how these people experience healthcare and it is likely to have an impact on their quality of life. Targeted work is required to understand the specific healthcare needs of people with CKD and mental health disorders.

A 12-month longitudinal naturalistic follow-up of cariprazine in schizophrenia.

Cariprazine, a third-generation antipsychotic (TGAs), has demonstrated efficacy in the treatment of schizophrenia with good tolerability profile. Actual real-world literature data are lacking, particularly when exploring its efficacy in the long term. The present study examined the effects of cariprazine treatment on specific psychopathological domains with a particular focus on outcomes and side effects in real-life experience, after a long-term treatment. The present 12-month longitudinal naturalistic study included a sample of subjects with a DSM-5-TR diagnosis of schizophrenia, recruited in the outpatients' psychiatric services of university and community hospitals in Italy, naturally treated with cariprazine. The assessments included: a sociodemographic data sheet, the Structured Clinical Interview for the DSM-5 (SCID-5), the Positive and Negative Symptom Scale (PANSS) and the St. Hans Rating Scale (SHRS). The PANSS was also administered after 6 (T1) and 12 (T2) months of treatment with cariprazine while the SHRS at T1. The total sample consisted of 31 patients, 15 males and 16 females. A significant decrease of the PANSS' subscales, Marder factors and total mean scores emerged at both T1 and T2 with respect to T0. Extrapyramidal symptoms occurred in a minority of patients and in mild or mild/moderate forms: no patient showed moderate forms of psychic/motor akathisia or dystonia, three subjects showed moderate parkinsonism. This study confirms a good efficacy profile of cariprazine in both positive and negative symptoms in patients with Schizophrenia, combined with a good tolerability profile in extrapyramidal symptoms.

Decreased serum levels of SETD1A protein in patients with schizophrenia

ObjectiveSET domain-containing protein 1A (SETD1A) histone lysine N-methyltransferase may serve as a biomarker for the auxiliary diagnosis and treatment assessment of schizophrenia (SCZ). The aim of this study was to compare serum levels of SETD1A protein between patients with SCZ and health controls. MethodsPatients with SCZ and health controls were recruited from the Sixth Hospital of Changchun and the ’Survey on Chronic Diseases and Risk Factors among Adults in Jilin Province’, respectively. The quantifications of lysine N-methyltransferase in peripheral serum were conducted by the ELISA method, and data was analyzed using the R software. ResultsForty patients with SCZ (mean age: 33.97 ± 5.99 years) and forty healthy controls (mean age: 39.07 ± 4.62 years) were included. There was significantly lower concentration of SETD1A protein in the SCZ group compared with the control group (P < 0.001). This significant difference still exists after stratification by sex (P < 0.05). ConclusionOur study demonstrates that decreased levels of serum SETD1A protein may be utilized as a possible peripheral biomarker for schizophrenia.

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features.

Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification. Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions. Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research. Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.

Connections between specific mental health diagnoses of schizophrenia, bipolar disorder and schizoaffective disorder and primary substance use

PurposeThis study aims to use the database of consumers referred to the dual diagnosis shared care service to examine those connections. The Eastern Dual Diagnosis Service, based in Melbourne, Australia, has established a database of consumers with co-occurring mental health disorders and problematic substance use. An examination of mental health and substance-use information obtained over a two-year period in the delivery of dual diagnosis shared care to consumers of mental health services is supporting an improved understanding of substance use and the connections to specific mental health diagnoses of schizophrenia, bipolar disorder and schizoaffective disorder.Design/methodology/approachThis research uses a quantitative approach to review the prevalence of primary substance use and mental health diagnoses for consumers referred to as dual diagnosis shared care. Reviewed are referrals from adult mental health community and rehabilitation teams operating within a mental health and well-being program between January 2019 and December 2020 inclusive.FindingsOf the 387 clients referred to the specialist dual diagnosis shared care, methamphetamine, alcohol and cannabis are associated with 89.4% of the primary mental health diagnosis (PMHD). The most common PMHDs are schizophrenia, schizoaffective disorder and bipolar disorder. The most common PMHD and substance-use connection was schizophrenia and methamphetamine. Nicotine was reported to be used by 84% of consumers and often occurred in addition to another problematic primary substance.Originality/valueImproved dual diagnosis data collection from a community-based clinical mental health service is increasing understanding of the mental health and substance-use relationship. This is now providing clarity on routes of investigation into co-occurring mental health and problematic substance-use trends and guiding improved integrated treatments within a contemporary mental health setting.