Impact of a standardized referral to a community pharmacist-ledsmoking cessation program before elective jointreplacement surgery
Bibliographic record
Abstract
INTRODUCTION: Smokers undergoing total joint replacement (TJR) are more likely to develop infections and be re-admitted than non-smokers. The primary purpose of this study was to evaluate the effectiveness of standardized preoperative referral to a community-based pharmacist-led smoking cessation program compared to usual care for patients undergoing TJR. Secondarily, we evaluated the use of the smoking cessation program. METHODS: A pre-post quasi-experimental study was conducted at a central intake clinic that prepares approximately 3000 TJR patients annually. Participants were recruited at a mean of 13±11.1 weeks preoperatively and provided informed consent. Participants in the 'pre' observational phase (OP) received usual care for smoking cessation. For 'post' intervention phase (IP) participants, a referral was sent to a community-based pharmacist-led smoking cessation program. Smoking status was validated on study entry using exhaled carbon monoxide. Participants' smoking status was re-assessed using self-reported point prevalence abstinence at 6 months post-recruitment. RESULTS: We enrolled 120/150 (80%) potential OP candidates and 104/286 (36%) potential IP candidates. The groups were similar on study entry; overall, the mean age of participants was 58.7±9.1 years and 103 (47%) were male. They reported medium nicotine dependence with 37±11.6 mean years smoked. At 6 months post-recruitment, 8 (7%) OP participants self-reported 30-day point prevalence abstinence compared to 21 (20%) IP participants (p=0.003). Only 58 (56%) IP participants complied with the pharmacist referral, with 19 (33%) of those seeing the pharmacist reporting point prevalence abstinence at 6 months compared to only 2 (4%) of the 45 participants who did not see the pharmacist (p<0.001). CONCLUSIONS: Referral to a community smoking cessation program as preoperative standard of care is feasible and can enhance long-term quit rates, but voluntary participation led to low recruitment to the program.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".