Electronic cigarettes versus nicotine-replacement therapy forsmoking cessation: A systematic review and meta-analysis ofrandomized controlled trials
Bibliographic record
Abstract
INTRODUCTION: Nicotine-replacement therapy (NRT) and electronic cigarettes (e-cigarettes) have been frequently used for smoking cessation. The aim of this review is to investigate the effectiveness and safety of e-cigarettes versus NRT for smoking cessation. METHODS: We searched PubMed, EMBASE, the Cochrane Library from inception to 10 October 2021. We included randomized controlled trials (RCTs) comparing e-cigarettes versus NRT for smoking cessation. Two authors independently screened titles, abstracts and full texts for eligibility. Paired authors extracted data, assessed risk of bias, and used GRADE (Grades of Recommendation, Assessment, Development, and Evaluation) to rate the certainty of evidence. RESULTS: The study included five RCTs with 1748 participants. The meta-analysis suggested the e-cigarettes versus NRT increased the ≥6 months continuous abstinence rate (RR=1.67; 95% CI: 1.21-2.28; 55 more per 1000 participants, low certainty), and 7-day point abstinence rate at ≥6 months follow-up (RR=1.43; 95% CI: 1.19-1.72; 84 more per 1000, low certainty). However, we found no evidence that e-cigarettes versus NRT increased 3-6 months continuous abstinence rate (RR=1.07; 95% CI: 0.73-1.57; 10 more per 1000, very low certainty) and <3 months continuous abstinence rate (RR=1.20; 95% CI: 0.90-1.60; 54 more per 1000, low certainty); similar results were found at <3 months follow-up (RR=1.19; 95% CI: 0.92-1.54; 55 more per 1000, very low certainty) and 3-6 months follow-up in 7-day point abstinence rate (RR=1.01; 95% CI: 0.70-1.44; 2 more per 1000, very low certainty). The adverse events were not significant between e-cigarettes and NRT other than throat irritation (RR=1.27; 95% CI: 1.13-1.42; 118 more per 1000, low certainty). CONCLUSIONS: E-cigarettes appeared to be superior to NRT in ≥6 months continuous abstinence rate and 7-day point abstinence rate. At short-term duration, we found no evidence that e-cigarettes compared to NRT increased the <6 months continuous abstinence rate and 7-day point abstinence rate.
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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 | 0.034 | 0.078 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.042 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".