Relationship Between Smoking and Patient-reported Measures of Disease Outcome in Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between smoking and disease activity, pain, function, and quality of life in patients with ankylosing spondylitis (AS). METHODS: Patients with AS (n = 612) from areas across the United Kingdom took part in a cross-sectional postal survey. Patient-reported outcome measures including the Bath AS Disease Activity Index, the Bath AS Functional Index (BASFI), a numerical rating scale (NRS) of pain, the AS quality of life questionnaire (ASQoL), and the evaluation of AS quality of life measures (EASi-QoL) were analyzed in terms of smoking status and relationship with pack-year history. The influence of potential confounding factors [age, sex, disease duration, and social deprivation (Townsend Index)] were tested in multivariate logistic regression analyses. RESULTS: Median scores of BASFI, pain NRS, ASQoL, and the 4 EASi-QoL domains were all higher in the group that had ever smoked compared to those who had never smoked (p < 0.0001, p = 0.04, p = 0.003, p < 0.02, respectively). In stepwise multivariate logistic regression analyses, high disease activity and more severe pain were associated primarily with current smoking, disease duration, and Townsend Index score, while decreased function and poor quality of life measures were associated more closely with increasing pack-year history, disease duration, and Townsend Index score. These associations were independent of age and sex. CONCLUSION: Smoking has a dose-dependent relationship with measures of disease severity in AS. The association with increased disease activity, decreased function, and poor quality of life in smokers was independent of age, sex, deprivation level, and disease duration.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".