Cigarette Smoking Increases the Prevalence of Hip Joint Involvement in Ankylosing Spondylitis: A Real-World Case-Control Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between cigarette smoking and hip joint involvement in ankylosing spondylitis (AS). METHODS: This case-control study compared patients with AS with and without hip involvement, as defined by the Bath Ankylosing Spondylitis Radiology Hip Index. Logistic regression analysis, subgroup analysis, and sensitivity analysis were conducted to estimate the association between smoking and hip involvement in AS. RESULTS: This study included 103 patients with hip involvement (cases) and 89 patients without hip involvement (controls). In univariate analysis, patients who had juvenile-onset AS (JAS), were younger, were male, had peripheral arthritis history, or had cigarette exposure were prone to hip involvement. After adjusting for confounding factors, JAS (adjusted odds ratio [aOR] 2.52, 95% CI 1.26-5.06), male sex (aOR 2.89, 95% CI 1.14-7.33), and cigarette smoking (aOR 7.23, 95% CI 2.27-23.05) were regarded to be independently associated with hip involvement in AS. Moreover, patients who smoked with exposure of less than 10 pack-years were 2.2 times more likely to have hip involvement than those without (aOR 2.21, 95% CI 1.09-4.47). This association was reproduced in subgroup analyses of males and propensity score-matched subjects, and it withstood sensitivity analysis. CONCLUSION: Smoking is a novel independent risk factor for hip involvement in AS; even exposure of less than 10 pack-years could contribute to increased prevalence of hip involvement in AS, which underlines the significance of smoking cessation in patients with AS, especially for JAS.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".