1664 – Evaluation Of The Effectiveness Of Treatment Response Applying Panss, Gaf And Moca In Patients With Schizophrenia
Bibliographic record
Abstract
Introduction Schizophrenia (SCH) is considered the most serious psychiatric disorder with complex pathogenetic and pathophysiological mechanisms and inadequate treatments. Objectives Given the association of psychotropic medication and cognitive, functional, and neuropsychiatric symptoms (NPS), the use of certain measuring instruments among patients who suffer from schizophrenia is important because the quantification of treatment effects is crucial for optimizing the management of patients with schizophrenia. Aims To assess the efficacy of antipsychotic therapy in schizophrenic patients with predominantly negative and positive symptoms, cognitive impairment and social, occupational and psychological dysfunction. Methods Two main groups were selected for analysis: (N=34) included patients taking first-generation antipsychotics (FGAs) and (N=16) included patients taking second generation antipsychotics (SGAs). We used the Positive and Negative Syndrome Scale (PANNS), Global Assessment Functioning (GAF) and Montreal Cognitive Assessment Scale (MOCA). Results Out of the total number of examinees (n=50), 15/50 (30%) were males and 35/50 (70%) were females; the age of onset was 38.4±1.77; duration of illness (mean±SD) 32.5±5.00; SANS-Total (mean±SD) (23.82±9.962); SAPS-Total (mean ±SD) (28.6±9.74). Analysis of the PANSS scale bipolar index shows that patients on SGA, on average, had lower scores (2.37±12.5) compared to patients on FGA (5.91 ±9.61). Conclusions Preliminary evidence showed that there are no significant advantages in the use of atypical antipsychotics compared with typical ones in a group of patients suffering from schizophrenia. It is important to realize what role the advancement of antipsychotics has played and what still needs to be accomplished to further improve the outcome of sch patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".