Comparative effect of varenicline and nicotine patches on preventing repeat cardiovascular events
Bibliographic record
Abstract
OBJECTIVE: To determine the comparative effectiveness of postdischarge use of varenicline versus prescription nicotine replacement therapy (NRT) patches for the prevention of recurrent cardiovascular events and mortality and whether this association differs by sex. METHODS: Our cohort study used routinely collected hospital, pharmaceutical dispensing and mortality data for residents of New South Wales, Australia. We included patients hospitalised for a major cardiovascular event or procedure 2011-2017, who were dispensed varenicline or prescription NRT patches within 90day postdischarge. Exposure was defined using an approach analogous to intention to treat. Using inverse probability of treatment weighting with propensity scores to account for confounding, we estimated adjusted HRs for major cardiovascular events (MACEs), overall and by sex. We fitted an additional model with a sex-treatment interaction term to determine if treatment effects differed between males and females. RESULTS: Our cohort of 844 varenicline users (72% male, 75% <65 years) and 2446 prescription NRT patch users (67% male, 65% <65 years) were followed for a median of 2.93 years and 2.34 years, respectively. After weighting, there was no difference in risk of MACE for varenicline relative to prescription NRT patches (aHR 0.99, 95% CI 0.82 to 1.19). We found no difference (interaction p=0.098) between males (aHR 0.92, 95% CI 0.73 to 1.16) and females (aHR 1.30, 95% CI 0.92 to 1.84), although the effect among females deviated from the null. CONCLUSION: We found no difference between varenicline and prescription NRT patches in the risk of recurrent MACE. These results should be considered when determining the most appropriate choice of smoking cessation pharmacotherapy.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".