A Perioperative Smoking Cessation Intervention with Varenicline
Bibliographic record
Abstract
BACKGROUND: The efficacy of perioperative tobacco interventions on long-term abstinence and the safety of smoking cessation less than 4 weeks before surgery is unclear. Our objective was to determine the efficacy and safety of a perioperative smoking cessation intervention with varenicline to reduce smoking in elective surgical patients. METHODS: In a prospective, multicenter, double-blind, placebo-controlled trial, 286 patients were randomized to receive varenicline or placebo. Both groups received in-hospital and telephone counseling during 12 months. The primary outcome was the 7-day point prevalence abstinence rate 12 months after surgery. Secondary outcomes included abstinence at 3 and 6 months after surgery. Multivariable logistic regression was used to identify independent variables related to abstinence. RESULTS: The 7-day point prevalence abstinence at 12 months for varenicline versus placebo was 36.4% versus 25.2% (relative risk: 1.45; 95%: CI: 1.01-2.07; P = 0.04). At 3 and 6 months, the 7-day point prevalence abstinence was 43.7% versus 31.9% (relative risk: 1.37; 95% CI: 1.01 to 1.86; P = 0.04), and 35.8% versus 25.9% (relative risk: 1.43; 95%: CI 1.01-2.04; P = 0.04) for varenicline versus placebo, respectively. Treatment with varenicline (odds ratio: 1.76; 95% CI: 1.03-3.01; P = 0.04), and preoperative nicotine dependence (odds ratio: 0.82, 95% CI: 0.68 to 0.98; P = 0.03) predicted abstinence at 12 months. The adverse events profile in both groups was similar except for nausea, which occurred more frequently for varenicline versus placebo (13.3% vs. 3.7%, P = 0.004). CONCLUSIONS: A perioperative smoking cessation intervention with varenicline increased abstinence from smoking 3, 6, and 12 months after elective noncardiac surgery with no increase in serious adverse events.
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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 | 0.000 | 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".