Smoking and Outcomes After Knee and Hip Arthroplasty: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Studies have suggested higher rates of perioperative and postoperative complications in smokers compared to nonsmokers. The objective of this systematic review was to assess the association of smoking and postoperative outcomes following total hip arthroplasty (THA) or total knee arthroplasty (TKA). METHODS: A search of 6 databases (The Cochrane Library, Scopus, Proquest Dissertation abstracts, CINAHL, Ovid Medline, and Embase) was performed by a Cochrane librarian. All titles and abstracts were screened by 2 independent reviewers with expertise in performing systematic reviews. Studies were included if they were fully published reports that included smoking and any perioperative or postoperative clinical outcome in patients with TKA or THA. RESULTS: A total of 21 studies were included for the review, of which 6 provided multivariable-adjusted analyses, 14 univariate analyses, and one statistical modeling. For most outcomes, results from 1-2 studies could be pooled. Current smokers were significantly more likely to have any postoperative complication (risk ratio 1.24, 95% CI 1.01 to 1.54) and death (risk ratio 1.63, 95% CI 1.06 to 2.51) compared to nonsmokers. Former smokers were significantly more likely to have any post-operative complication (risk ratio 1.32, 95% CI 1.05 to 1.66) and death (risk ratio 1.69, 95% CI 1.08 to 2.64) compared to nonsmokers. CONCLUSION: This systematic review found that smoking is associated with significantly higher risk of postoperative complication and mortality following TKA or THA. Studies examining longterm consequences of smoking on implant survival and complications are needed. Smoking cessation may improve outcomes after THA or TKA.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".