Varenicline and Adverse Cardiovascular Events: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Varenicline is an efficacious smoking-cessation drug. However, previous meta-analyses provide conflicting results regarding its cardiovascular safety. The publication of several new randomized controlled trials (RCTs) provides an opportunity to reassess this potential adverse drug reaction. METHODS AND RESULTS: We searched MEDLINE, EMBASE, and the Cochrane Library for RCTs that compare varenicline with placebo for smoking cessation. RCTs reporting cardiovascular serious adverse events and/or all-cause mortality during the treatment period or within 30 days of treatment discontinuation were eligible for inclusion. Relative risks (RRs) with 95% CIs were generated by using DerSimonian-Laird random-effects models. Thirty-eight RCTs met our inclusion criteria (N=12 706). Events were rare in both varenicline (57/7213) and placebo (43/5493) arms. No difference was observed for cardiovascular serious adverse events when comparing varenicline with placebo (RR 1.03, 95% CI 0.72-1.49). Similar findings were obtained when examining cardiovascular (RR 1.04, 95% CI 0.57-1.89) and noncardiovascular patients (RR 1.03, 95% CI 0.64-1.64). Deaths were rare in both varenicline (11/7213) and placebo (9/5493) arms. Although 95% CIs were wide, pooling of all-cause mortality found no difference between groups (RR 0.88, 95% CI 0.50-1.52), including when stratified by participants with (RR 1.24, 95% CI 0.40-3.83) and without (RR 0.77, 95% CI 0.40-1.48) cardiovascular disease. CONCLUSIONS: We found no evidence that varenicline increases the rate of cardiovascular serious adverse events. Results were similar among those with and without cardiovascular disease. Given varenicline's efficacy as a smoking cessation drug and the long-term cardiovascular benefits of cessation, it should continue to be prescribed for smoking cessation.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.031 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".