The association between cigarette smoking and radiographic progression in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: The association between smoking and radiographic damage has been established in axial spondyloarthritis and rheumatoid arthritis, but not in psoriatic disease. We aimed to investigate this relationship in psoriatic arthritis (PsA). METHODS: We included patients with PsA from our observational cohort. Smoking status was assessed at each clinic visit and categorized as non-smoker, past smoker, or current smoker. We used linear mixed models to identify factors associated with the overall change in damage, as measured by the modified Steinbrocker score. RESULTS: Of 1736 patients included in the study, 952 (54.9 %) were males; the mean (standard deviation) age at baseline was 44.9 (13.3) years. 906 (52.2 %) patients were non-smokers, 211 (12.2 %) were past smokers, and 311 (17.9 %) were current smokers; 308 (17.7 %) patients had missing smoking data. The median [interquartile range] modified Steinbrocker score at baseline was 2.0 [0.0, 10.0]. In the multivariable linear mixed model, a longer duration between the first and last sets of radiographs, a higher baseline modified Steinbrocker score, and the use of conventional synthetic DMARDs were significantly associated with an increase in joint damage. Cigarette smoking-both current (estimate -0.18, 95 % confidence interval [CI] -0.94 to 0.58) and past (estimate -0.67, 95 % CI -1.51 to 0.17)-showed no significant association with the change in modified Steinbrcoker score. CONCLUSION: Cigarette smoking does not appear to be significantly associated with the progression of joint damage in PsA. Further studies are required to confirm our findings.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".