S240. DETERMINANT FACTORS OF REAL-WORLD FUNCTIONING IN SCHIZOPHRENIA
Bibliographic record
Abstract
Negative, cognitive and depressive symptoms, as well as physical comorbidities, have a great impact on the real-world functioning in patients with schizophrenia (SZ) (1, 2, 3). However, not all the studies have employed accurate psychometric instruments to assess these symptoms, nor have all these factors been studied simultaneously. The aim of the current study is to analyze the determinants of functionality in SZ measured by the Personal and Social Performance (PSP) scale, and considering not exclusively psychopathological and cognitive variables, but also aspects related to physical health and inflammation. Sample: 73 outpatients with SZ, duration of illness ≤10 years, under stable maintenance treatment [mean age (31.7 ± 6.5), males (61.6%)]. Clinical variables: PANSS, CGI-Severity, Clinical Assessment Interview of Negative Symptoms (CAINS) -Motivation/Pleasure (MAP) & Expression (EXP) domains-, Brief Negative Symptom Scale (BNSS), Calgary Depression Scale (CDS), MATRICS Consensus Cognitive Battery (MCCB), PSP. Biological variables: Glucose, cholesterol, LDL, HDL, triglycerides, TSH, prolactin, insulin, uric acid, alkaline phosphatase (APh), C-reactive protein (CRP), TNF-α, interleukin(IL)-6, IL-2, IL-1β, IL-1RA, homocysteine, HT (% hemolysis), lipid peroxidation (LPO), catalase. Pearson correlations were performed to select variables significantly related to PSP scores which were later included in stepwise multiple linear regression analyses. Age, sex, education, smoking, alcohol use, BMI, antipsychotic equivalent doses and other confounding factors were considered. Final model for PSP total score (R2=0.778, F=45.564, p<0.001) identified that CGI-Severity (β= -0.279), PANSS-NM (negative Marder Factor) (β = -0.218), Asociality subscale of BNSS (β= -0.383) and IL-2 (β= -0.269) were significant predictors. Predicting variables included in regression models for specific PSP domains: - Self-care (R2=0.661, F=22.947, p<0.001): PANSS-NM (β=0.458), Avolition subscale of BNSS (β=0.248), IL-2 (β=0.221), APh (β=0.201). - Useful activities (R2=0.563, F=42.473, p<0.001): CGI-S (β=0.245), Avolition (β=0.557). - Social relationships (R2=0.731, F=56.998, p<0.001): Asociality (β=0.578), PANSS-GP (β=0.276), CAINS-EXP (β=0.178). - Aggresive behaviour (R2=0.335, F=16.892, p<0.001): PANSS-P (β=0.408), CDS (β=0.273). 1.Negative symptoms are the most important determinants of a deficit in the real-world functioning in SZ, especially “asociality.” 2.“Apathy” has a negative impact on self-care and useful activities domains. 3.Proinflammatory cytokine IL-2 marks poor functionality. 1. Harvey (2014). Assessing disability in schizophrenia: tools and contributors. J Clin Psychiatry. 2. Strassnig et al. (2015). Determinants of different aspects of everyday outcome in schizophrenia: The roles of negative symptoms, cognition, and functional capacity. Schizophr Res. 3. Menendez-Miranda et al. (2015). Predictive factors of functional capacity and real-world functioning in patients with schizophrenia. Eur Psychiatry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".