Comparisons of high-dose and combination nicotine replacement therapy, varenicline, and bupropion for smoking cessation: A systematic review and multiple treatment meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: This review compared the effect of high-dose nicotine replacement therapy (NRT) and combinations of NRT for increasing smoking abstinence rates compared to standard-dose NRT patch, varenicline, and bupropion on smoking abstinence. METHODS: Ten electronic databases were searched (up to January 2012) for randomized controlled trials (RCT) of standard-dose (≤ 22 mg) or high-dose nicotine patch therapy (> 22 mg), combination NRT (e.g. nicotine patch + nicotine inhaler), bupropion, and varenicline. Analysis consisted of random-effects pairwise meta-analysis and a Bayesian multiple treatment comparison (MTC). RESULTS: We identified 146 RCTs (65 standard-doses of the nicotine patch (≤ 22 mg); 6 high-dose NRT patch (> 22 mg); 5 high versus standard-dose NRT patch; 5 combination NRT versus inert controls; 6 combination versus single NRT patch; 48 bupropion; and 11 varenicline). The MTC found that all therapies offered treatment benefits at most time points over controls. Combination NRT and higher-dose NRT did not demonstrate consistent effects over other interventions. With the exception of varenicline, the benefits of treatments over standard-dose NRT were not retained in the long term. CONCLUSIONS: All pharmacologic treatments were significantly more effective than inert controls. Varenicline was the only treatment demonstrating effects over other options. These results should be considered in the development of clinical practice guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| 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) | 0.000 | 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 it