Smoking trajectories and residual cardiovascular risk in patients with stable coronary artery disease: an international cohort study
Bibliographic record
Abstract
AIMS: There is a variety of smoking habits trajectories in patients with established stable coronary artery disease (CAD), with unclear consequences on cardiovascular (CV) events. We aimed to clarify the impact of smoking cessation and reduction on long-term cardiovascular outcomes in stable CAD patients, evaluating whether quitting at any stage still provides significant benefits and to what extent. METHODS AND RESULTS: The CLARIFY registry included 32 378 outpatients with stable CAD. Smoking history and status were recorded annually during the 5-year follow-up. In active smokers, we studied the effect of smoking cessation or reduction. In former smokers, we analysed the timing of smoking cessation relative to CAD diagnosis and residual CV risk based on years of abstinence. The primary outcome was a composite of CV death and MI. At inclusion, 46.2% of patients were former smokers and 12.5% current smokers. Amongst active smokers, smoking cessation in the stable phase of the disease was associated with improved outcomes, irrespective of timing (aHR 0.56, 95% CI: 0.42-0.76, P < 0.001). However, smoking quantity reduction was not associated with improved CV outcomes. Among former smokers, 55.7% had quit within a year of CAD diagnosis. Each additional year of smoking post-CAD diagnosis increased CV risk. Former smokers never returned to the CV risk level of never smokers, regardless of years of abstinence. CONCLUSION: In stable CAD patients, smoking cessation is associated with significantly better CV outcomes and survival, irrespective of the timing of cessation, and should therefore always be a priority. Smoking reduction was not associated with improved CV outcomes. Most former smokers quit within a year of CAD diagnosis, and CV risk increases with each subsequent year of active smoking. LAY SUMMARY: In a cohort of over 32 000 patients with stable coronary artery disease (CAD) with a 5-year follow-up, the evolution of smoking habits revealed that:Quitting smoking at any point-even years after diagnosis-is associated with a 50% reduction in the risk of subsequent cardiovascular events and death. However, only 12% of active smokers quit each year on average. Conversely, reducing the number of cigarettes without fully quitting is not associated with a lower risk of adverse cardiovascular events.Most former smokers quit within a year of their CAD diagnosis, with cardiovascular risk increasing for each additional year of continued smoking afterward. Finally, former smokers never returned to the cardiovascular risk level of never smokers, regardless of years of abstinence.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".