Outcomes of Bupropion Therapy for Smoking Cessation During Routine Clinical Use
Bibliographic record
Abstract
BACKGROUND: Knowledge pertaining to the effectiveness of smoking cessation treatments and patient characteristics that may affect success may enable smokers and clinicians to select individualized treatment for each patient and ultimately increase the success rate of smoking cessation in general. OBJECTIVE: To evaluate the effectiveness of bupropion as a smoking cessation agent when used in routine clinical practice. METHODS: This was a prospective, observational study with a one year follow-up period. Adult smokers presenting to community pharmacies in British Columbia, Canada, with an index prescription for bupropion for smoking cessation (N = 205) were eligible. The primary outcome was the biochemically validated 12 month point abstinence (PA) rate from smoking. Secondary outcomes included the frequency of adverse events, patterns of bupropion use in routine clinical practice, and possible predictors of bupropion effectiveness. RESULTS: The validated 12 month PA rate was 21.0%. Of subjects who reported taking at least one dose of bupropion, 70.4% (126/179) experienced at least one adverse event and 29.6% (53/179) reported stopping the drug due to adverse effects. Greater length of time on bupropion (OR 0.98) and a lower cigarette pack-year history (OR 1.05) were associated with an increase in the odds of smoking cessation. CONCLUSIONS: Subjects receiving bupropion in a real-life setting exhibited a similar abstinence rate at 12 months as has been observed in the active drug groups of placebo-controlled clinical trials. However, the patterns of use and discontinuation rate due to adverse events differed substantially from those observed in early efficacy studies.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".