From periphery immunity to central domain through clinical interview as a new insight on schizophrenia.

Identifying disease predictors through advanced statistical models enables the discovery of treatment targets for schizophrenia. In this study, a multifaceted clinical and laboratory analysis was conducted, incorporating magnetic resonance spectroscopy with immunology markers, psychiatric scores, and biochemical data, on a cohort of 45 patients diagnosed with schizophrenia and 51 healthy controls. The aim was to delineate predictive markers for diagnosing schizophrenia. A logistic regression model was used, as utilized to analyze the impact of multivariate variables on the prevalence of schizophrenia. Utilization of a stepwise algorithm yielded a final model, optimized using Akaike's information criterion and a logit link function, which incorporated eight predictors (White Blood Cells, Reactive Lymphocytes, Red Blood Cells, Glucose, Insulin, Beck Depression score, Brain Taurine, Creatine and Phosphocreatine concentration). No single factor can reliably differentiate between healthy patients and those with schizophrenia. Therefore, it is valuable to simultaneously consider the values of multiple factors and classify patients using a multivariate model.

Risk factors for weight gain in patients with first-episode psychosis. / Czynniki ryzyka przyrostu masy ciala u pacjentów z pierwszym epizodem psychozy.

OBJECTIVES: Assessment of the association between weight gain in patients with first-episode psychosis (FEP) and biopsychosocial and sociological factors. METHODS: 25 subjects with FEP aged 14-35 examined in week 1 (P1) and after three months of hospitalization (P3) were enrolled in the study. Within 3 months all patients were diagnosed with schizophrenia. The study used: a socio-demographic survey, Positive and Negative Syndrome Scale (PANSS), State-Trait Anxiety Inventory (STAI), Coping Inventory for Stressful Situations (CISS), Questionnaire Eating Behaviors (QEB), and routine biochemical test findings. For some variables, the differences (variable_D) between the values at P1 and P3 were calculated. RESULTS: Statistically significant correlations were shown between body weight_P1, _P3, _D, and healthy diet index_P1, _P3, severity of psychotic symptoms measured by the PANSS_P1 and _D, the CISS focused on emotions and task_P1, _P3 and _D, mother's body weight in youth and now, father's body weight in youth and now, and the number of the patient's siblings. In the linear regression analysis, body weight_P1 and the CISS focused on emotions_P1 turned out to be significant predictors of body weight_P3. CONCLUSIONS: Multifactorial influence of weight gain in FEP in schizophrenia was observed. Countermeasures against weight gain should refer not only to the diet, but also to the way the eating habits are related to psychopathology associated with psychosis and to the emotional functioning of the patient.