A Randomized Clinical Trial of St. John's Wort for Smoking Cessation
Bibliographic record
Abstract
INTRODUCTION: St. John's wort (SJW) is a widely used herbal supplement. The predominant mechanism(s) accounting for the activity of SJW in vivo are, however, unclear. The purpose of this study was to investigate the efficacy of SJW for smoking cessation. METHODS: We conducted a randomized, blinded, placebo-controlled, three-arm, dose-ranging clinical trial. A total of 118 subjects were randomly allocated to receive SJW 300 mg, 600 mg, or a matching placebo tablet 3 times a day combined with a behavioral intervention for 12 weeks. Self-reported smoking abstinence was biochemically confirmed with expired air carbon monoxide. RESULTS: Mean age of the study participants was 37.6 +/- 12.4 years; they smoked an average of 20.0 +/- 6.6 cigarettes per day for 20 +/- 12.1 years. The study dropout rate was high (43%). By intention-to-treat analysis, no significant differences were observed in abstinence rates at 12 and 24 weeks between SJW dose groups and placebo. SJW did not attenuate withdrawal symptoms among abstinent subjects. Abstinence rates did not differ by study group among subjects who took at least 75% of their study medication. No significant side-effects were noted with SJW. CONCLUSIONS: In this randomized trial, SJW did not increase smoking abstinence rates. Our data, in combination with data from other studies, suggest that SJW has little role in the treatment of tobacco dependence.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".