Nitric Oxide Plasma/Serum Levels In Patients With Schizophrenia: A Systematic Review And Meta-Analysis
Bibliographic record
Abstract
For the last 40 years, schizophrenia has been considered to be the result primarily of a dysfunction in brain dopaminergic pathways. In this review, it is described and discussed findings concerning nitric oxide-mediated neurotransmission in schizophrenia. Studies were searched in PubMed, SciELO, and LILACS using the terms schizophrenia and nitric oxide plasma levels or nitric oxide serum levels, with no time limit. The reference lists of selected articles were also hand-searched for additional articles. From 15 potential reports, 10 were eligible to be included in the review and meta-analysis. These studies included a total of 505 patients with schizophrenia and 339 healthy volunteers. No significant difference was found between patients and healthy controls regarding total nitrite plasma/serum levels (effect size g = 0.285, 95%CI = -0.205 to 0.774, p = 0.254). However, when studies with patients under antipsychotic treatment were examined separately, there was a significant difference between patients and healthy volunteers (effect size g = 0.663, 95%CI = 0.365 to 0.961, p < 0.001), showing that patients under treatment have higher levels of plasma/serum nitric oxide than controls. These results suggest that antipsychotics increase nitric oxide plasma/serum levels and that the nitrergic pathway would be a fertile target for the development of new treatments for 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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.019 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".