Smoking and the Risk of Mortality and Vascular and Respiratory Events in Patients Undergoing Major Surgery
Bibliographic record
Abstract
IMPORTANCE: The effects of smoking on postoperative outcomes in patients undergoing major surgery are not fully established. The association between smoking and adverse postoperative outcomes has been confirmed. Whether the associations are dose dependent or restricted to patients with smoking-related disease remains to be determined. OBJECTIVE: To evaluate the association between current and past smoking on the risk of postoperative mortality and vascular and respiratory events in patients undergoing major surgery. DESIGN: Cohort study using the American College of Surgeons National Surgical Quality Improvement Program database. We obtained data on smoking history, perioperative risk factors, and 30-day postoperative outcomes. We assessed the effects of current and past smoking (>1 year prior) on postoperative outcomes after adjustment for potential confounders and effect mediators (eg, cardiovascular disease, chronic obstructive pulmonary disease, and cancer). We also determined whether the effects are dose dependent through analysis of pack-year quintiles. SETTING AND PARTICIPANTS: A total of 607,558 adult patients undergoing major surgery in non-Veterans Affairs hospitals across the United States, Canada, Lebanon, and the United Arab Emirates during 2008 and 2009. MAIN OUTCOMES AND MEASURES: The primary outcome measure was 30-day postoperative mortality; secondary outcome measures included arterial events (myocardial infarction or cerebrovascular accident), venous events (deep vein thrombosis or pulmonary embolism), and respiratory events (pneumonia, unplanned intubation, or ventilator requirement >48 hours). RESULTS: The sample included 125,192 current (20.6%) and 78,763 past (13.0%) smokers. Increased odds of postoperative mortality were noted in current smokers only (odds ratio, 1.17 [95% CI, 1.10-1.24]). When we compared current and past smokers, the adjusted odds ratios were higher in the former for arterial events (1.65 [95% CI, 1.51-1.81] vs 1.20 [1.09-1.31], respectively) and respiratory events (1.45 [1.40-1.51] vs 1.13 [1.08-1.18], respectively). No effects on venous events were observed. The effects of smoking mediated through smoking-related disease were minimal. The increased adjusted odds of mortality in current smokers were evident from a smoking history of less than 10 pack-years, whereas the effects of smoking on arterial and respiratory events were incremental with increased pack-years. CONCLUSIONS AND RELEVANCE: Smoking cessation at least 1 year before major surgery abolishes the increased risk of postoperative mortality and decreases the risk of arterial and respiratory events evident in current smokers. These findings should be carried forward to evaluate the value and cost-effectiveness of intervention in this setting. Our study should increase awareness of the detrimental effects of smoking-and the benefits of its cessation-on morbidity and mortality in the surgical setting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".