PsiOvi Staging Model for Schizophrenia (PsiOvi SMS): A New Internet Tool for Staging Patients with Schizophrenia.

BACKGROUND: One of the challenges of psychiatry is the staging of patients, especially those with severe mental disorders. Therefore, we aim to develop an empirical staging model for schizophrenia. METHODS: Data were obtained from 212 stable outpatients with schizophrenia: demographic, clinical, psychometric (PANSS, CAINS, CDSS, OSQ, CGI-S, PSP, MATRICS), inflammatory peripheral blood markers (C-reactive protein, interleukins-1RA and 6, and platelet/lymphocyte [PLR], neutrophil/lymphocyte [NLR], and monocyte/lymphocyte [MLR] ratios). We used machine learning techniques to develop the model (genetic algorithms, support vector machines) and applied a fitness function to measure the model's accuracy (% agreement between patient classification of our model and the CGI-S). RESULTS: Our model includes 12 variables from 5 dimensions: 1) psychopathology: positive, negative, depressive, general psychopathology symptoms; 2) clinical features: number of hospitalizations; 3) cognition: processing speed, visual learning, social cognition; 4) biomarkers: PLR, NLR, MLR; and 5) functioning: PSP total score. Accuracy was 62% (SD = 5.3), and sensitivity values were appropriate for mild, moderate, and marked severity (from 0.62106 to 0.6728). DISCUSSION: We present a multidimensional, accessible, and easy-to-apply model that goes beyond simply categorizing patients according to CGI-S score. It provides clinicians with a multifaceted patient profile that facilitates the design of personalized intervention plans.

What factors should we modify to promote high functioning and prevent functional decline in people with schizophrenia?

Background: Since research in schizophrenia mainly focuses on deficits and risk factors, we need studies searching for high-functioning protective factors. Thus, our objective was to identify protective (PFs) and risk factors (RFs) separately associated with high (HF) and low functioning (LF) in patients with schizophrenia. Methods: We collected information (sociodemographic, clinical, psychopathological, cognitive, and functional) from 212 outpatients with schizophrenia. Patients were classified according to their functional level (PSP) as HF (PSP > 70, n = 30) and LF (PSP ≤ 50, n = 95). Statistical analysis consisted of Chi-square test, Student's t-test, and logistic regression. Results: HF model: variance explained: 38.4-68.8%; PF: years of education (OR = 1.227). RFs: receiving a mental disability benefit (OR = 0.062) and scores on positive (OR = 0.719), negative-expression (OR = 0.711), and negative-experiential symptoms (OR = 0.822), and verbal learning (OR = 0.866). LF model: variance explained: 42.0-56.2%; PF: none; RFs: not working (OR = 6.900), number of antipsychotics (OR = 1.910), and scores on depressive (OR = 1.212) and negative-experiential symptoms (OR = 1.167). Conclusion: We identified specific protective and risk factors for high and low functioning in patients with schizophrenia and confirmed that high functioning factors are not necessarily the opposite of those associated with low functioning. Only negative experiential symptoms are a shared and inverse factor for high and low functioning. Mental health teams must be aware of protective and risk factors and try to enhance or reduce them, respectively, to help their patients improve or maintain their level of functioning.

Is it possible to stage schizophrenia? A systematic review.

INTRODUCTION: A staging model is a clinical tool used to define the development of a disease over time. In schizophrenia, authors have proposed different theoretical staging models of increasing complexity. Therefore, the aims of our study were to provide an updated and critical view of the proposed clinical staging models for schizophrenia and to review the empirical data that support them. METHODS: Systematic literature review following PRISMA guidelines. From the PubMed database and backward reference search, a total of 141 records were retrieved, but only 20 were selected according to the inclusion criteria: (a) available in English; (b) participants with schizophrenia ≥ 18 years; and (c) theoretical and empirical research studies intended to develop, validate, and/or improve staging models of schizophrenia. RESULTS: Different clinical staging models for schizophrenia were identified, information about the proposed stages was tabulated and presented in the Results section (Tables 1, 2). Most of which include neuroimaging, functioning, and psychopathology, but only two models add objective biomarkers and none include patient point of view. However, few models have been psychometrically tested or used small samples and thus have been validated only partially. In addition, five studies proposed therapeutic interventions according to the stage of the disorder from a theoretical point of view. DISCUSSION: In conclusion, it is possible to stage schizophrenia, but the models developed have several limitations. Empirical validation and inclusion of more specific biomarkers and measures of other life areas affected by schizophrenia could help in the development of more valid models.

Real-World Functioning in Patients With Schizophrenia: Beyond Negative and Cognitive Symptoms.

Introduction: Interest in the idea of recovery for certain patients with schizophrenia has been growing over the last decade. Improving symptomatology and functioning is crucial for achieving this. Our study aims to identify those factors that substantially contribute to real-world functioning in these patients. Methods: We carried out a cross-sectional study in stable outpatients with schizophrenia on maintenance antipsychotic monotherapy. Patients: We studied 144 outpatients with schizophrenia (DSM-IV-TR criteria) meeting the following criteria: (1) 18-65 years of age; (2) being clinically stable for at least the previous three months; (3) on maintenance antipsychotic monotherapy (prescriptions ≤ 10 mg olanzapine, ≤200 mg quetiapine, or ≤100 mg levomepromazine as hypnotics were also allowed); and (4) written informed consent. Assessment: We collected information on demographic and clinical variables by using an ad hoc questionnaire. For psychopathology, we employed the Spanish versions of the following psychometric instruments: the Positive and Negative Syndrome Scale (PANSS), the Brief Negative Symptom Scale (BNSS-Sp), and the Calgary Depression Scale (CDS). In addition, cognitive domains were assessed using the Verbal Fluency Test (VFT), the Digit Symbol Substitution Test (DSST), and the Trail Making Test, parts A and B (TMT-A and TMT-B). Finally, we employed the Spanish versions of the University of California San Diego Performance-based Skills Assessment (Sp-UPSA) and the Personal and Social Performance (PSP) for assessing functional capacity and real-world functioning, respectively. Statistical analysis: A forward stepwise regression was conducted by entering those variables significantly associated with PSP total score into the univariate analyses (Student's t-test, ANOVA with Duncan's post-hoc test, or bivariate Pearson correlation). Results: A total of 144 patients; mean age 40 years, 64% males, mean length of illness 12.4 years, PSP total score 54.3. The final model was a significant predictor of real-world functioning [F (7, 131) = 36.371, p < 0.001] and explained 66.0% of the variance. Variables retained in the model: BNSS-Sp abulia, asociality, and blunted affect, PANSS general psychopathology, Sp-UPSA transportation, TMT-B, and heart rate. Conclusion: Our model will contribute to a more efficient and personalized daily clinical practice by assigning specific interventions to each patient based on specific impaired factors in order to improve functioning.