Effect of smoking on age at the time of coronary artery bypass graft surgery; baseline data results from the ROSETTA-CABG registry
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease (CAD) is a leading cause of death. The aetiology of this disease is not known, but many important risk factors have been recognised. OBJECTIVE: To evaluate the effect of smoking on age at the time of coronary artery bypass graft surgery (CABG), and to examine this finding in the light of medical literature. METHODS: The authors recruited patients immediately after CABG in a prospective, study in 16 centres and enrolled 408 patients, of which 395 were ultimately analysed. RESULTS: Among the 395 patients analysed, there were 60 smokers and 335 non-smokers. The smokers were 8.4 years younger than non-smokers at the time of index CABG. The average age of smokers was 55.79.0 years, and that of non-smokers was 64.1±9.9 years (p<0.001). Hyperlipidaemia was present in 76.7% of smokers and 74.6% of non-smokers (p-NS). Hypertension was present in 58.3% of smokers and 63.9% of non-smokers (p-NS). Diabetes mellitus was present in 21.3% of smokers and 29.3% of non smokers (p-NS). Left ventricular ejection fraction was 53.0±10.5% in smokers and 53.3 ±13.8% in non-smokers (p-NS). Myocardial infarction had occurred in 41.7% of smokers and 35.5% of non-smokers (p-NS). CONCLUSION: Smoking accelerates atherosclerosis and coronary thrombosis resulting in severe form of CAD that cannot be managed by medications or PCI, and requires coronary artery bypass graft surgery (CABG) 8.4 years earlier than non-smokers.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".