Paroxetine-Induced Increase in Metabolic End Products of Nitric Oxide
Bibliographic record
Abstract
Decreased production of endothelium-derived nitric oxide has been implicated in the pathogenesis of cardiovascular diseases. Metabolic end products of nitric oxide (NO(x)) are often used as markers for endothelial nitric oxide production in humans. Decreased endothelium-derived nitric oxide has been suggested to mediate some of the deleterious effects of conventional cardiovascular risk factors such as hypercholesterolemia, smoking, and physical inactivity. A substantial number of patients with cardiovascular diseases suffer from comorbid major depressive disorder, which is a predictor of a poorer cardiovascular outcome. Paroxetine is a first-line antidepressant and has been reported to decrease plasma NO(x), theoretically suggesting a potential deleterious effect on the cardiovascular system. We assessed the hypothesis that paroxetine would induce a decrease in plasma NO(x) in healthy volunteers. Plasma NO(x) levels were measured by chemiluminescence at baseline, after 8 weeks of paroxetine administration, and at postdiscontinuation. Contrary to our hypothesis, we found that paroxetine administration induced a significant increase in NO(x) that normalized after paroxetine discontinuation. It remains to be demonstrated that the paroxetine-induced increase in NO(x) is associated with a modification of the cardiovascular risk in patients with major depressive disorder.
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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".