Impact of Cigarette Smoking in High-Risk Patients Participating in a Clinical Trial. A Substudy from the Heart Outcomes Prevention Evaluation (HOPE) Trial
Bibliographic record
Abstract
BACKGROUND: In recent large cardiovascular trials done in stable patients, 14-31% of the participants were smokers; the consequences of smoking in these trials using medications known to reduce cardiovascular events, have not been assessed. DESIGN: We evaluated the cardiovascular outcomes according to smoking status of men and women participating in the Heart Outcomes Prevention Evaluation trial. METHODS: The occurrence of cardiovascular events was documented among participants who did not change their smoking status during the trial. There were 2728 'never smokers', 5241 'former smokers' and 936 'current smokers', and all had stable cardiovascular disease or diabetes with at least one other risk factor. None had previous congestive heart failure or known left ventricular ejection fraction < 0.40. RESULTS: During the 4.5-year follow-up, there were 641 cardiovascular deaths, 978 myocardial infarctions, 358 strokes and 1021 deaths. In comparison to 'never smokers', smokers had relative risks adjusted for confounding variables including medications known to reduce cardiovascular mortality and morbidity, for cardiovascular death of 1.65 [95% confidence interval (CI), 1.28-2.14], for myocardial infarction of 1.26 (95% CI, 1.01-1.58), for stroke of 1.42 (95% CI, 1.00-2.04), and for total mortality of 1.99 (95% CI, 1.63-2.44). The rates of these events among 'former smokers' were not different from those of 'never smokers'. CONCLUSIONS: Smoking increased the risk of mortality and morbidity among high-risk patients despite the use of medications known to reduce cardiovascular events. Smoking cessation programs should be reinforced even for patients participating in clinical trials.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".