Mononitrate Isosorbide as an Adjunctive Therapy in Schizophrenia
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is a complex disabling mental disorder, and many patients present poor response to available treatments. Accumulating evidence about the role of the glutamate/nitric oxide pathway in mediating the positive and negative symptoms of schizophrenia suggests potential benefits of drugs that modulate this system. The aim of this study was to test the efficacy of isosorbide mononitrate (ISMN) as an adjunctive therapy for symptomatic outpatients with schizophrenia. METHODS: This was a 2-month randomized, double-blind, placebo-controlled trial with 24 schizophrenia patients. Participants were treated with ISMN 50 mg for 1 month and placebo for another month in a crossover design. The Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression Scale, Global Assessment of Functioning, and MATRICS Cognitive Consensual Battery were used for symptom assessment and arterial spin labeling was used to assess brain activation patterns. RESULTS: We found significant differences in the total, general, and positive subscales of the PANSS, Global Assessment of Functioning scores, and Clinical Global Impression scores during treatment with ISMN relative to placebo. No treatment effects were found comparing scores in the MATRICS Cognitive Consensual Battery and the negative subscale of the PANSS between the active and placebo conditions. A post hoc analysis of neuroimaging data showed reduced activity in the thalamus in subgroup of patients with severe psychopathology. CONCLUSIONS: Schizophrenia patients with persistent symptoms showed significant improvement after 4 weeks of treatment with ISMN 50 mg/d compared with placebo. Isosorbide mononitrate added beneficial effects to antipsychotic treatment in terms of positive symptoms and functioning.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".