Effectiveness of clozapine in treatment-resistant schizophrenia
Bibliographic record
Abstract
BACKGROUND: Clozapine has been shown to be superior to chlorpromazine in improving the positive and negative symptoms of schizophrenia. However, technical experience with clozapine in Indian patients has not been documented. AIM: To assess the improvement in psychopathology of treatment-resistant schizophrenia with clozapine therapy and to study the relationship between sociodemographic and various psychopathology variables among patients with treatment-resistant schizophrenia. METHODS: Twenty-two patients with treatment-resistant schizophrenia were evaluated using the Positive and Negative Syndrome Scale (PANSS) for schizophrenia, Calgary Depression Scale, Global Assessment of Functioning (GAF) Scale and Abnormal Involuntary Movement Scale (AIMS). These scales were used to determine the level of psychopathology, depression, overall functioning and severity of abnormal involuntary movements in the patients. The patients were admitted to the hospital for a short time to initiate clozapine therapy. At discharge, patients were stabilized on 300-400 mg/day of clozapine. The patients were re-evaluated after 20 months. RESULTS: The study group showed better global functioning after clozapine therapy. The therapy was well-tolerated though moderate side-effects were seen. Suicidal thoughts declined with clozapine therapy. There was a significant reduction in the negative symptom and general psychopathology scores of PANSS. CONCLUSION: Clozapine has therapeutic efficacy in some but not all treatment-resistant patients with schizophrenia.
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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 | 0.000 |
| 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) | 0.001 | 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 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".