Lifestyle Factors and Disease Activity Over Time in Early Axial Spondyloarthritis: The SPondyloArthritis Caught Early (SPACE) Cohort
Bibliographic record
Abstract
Objective Our aim was to study the importance of baseline BMI, smoking, and alcohol consumption (AC) for disease activity (DA) over 1 year in early axial spondyloarthritis (axSpA), stratified by sex. Methods In the SPondyloArthritis Caught Early cohort (patients with chronic back pain onset at age < 45 yrs, with pain for ≥ 3 months and ≤ 2 yrs), the Ankylosing Spondylitis Disease Activity Score (ASDAS) was recorded at inclusion, 3, and 12 months. All patients included in the analysis had axSpA based on a high physician’s level of confidence at baseline. Differences in ASDAS over 1 year by BMI (normal < 25 kg/m2, overweight 25–29.9 kg/m2, and obese ≥ 30 kg/m2), smoking history (never/previous/current), and AC (none, 0.1–2 units/week, 3–5 units/week, and ≥ 6 units/week) at baseline were estimated using mixed linear regression models. Results There were 344 subjects (mean age of 30.3 yrs; 49.4% men). In women, obesity was associated with 0.60 (95% CI 0.28–0.91) higher ASDAS compared to normal BMI. In both sexes, AC tended to be associated with lower DA over 1 year, with a significant association only in women with the highest AC (mean difference of –0.55, 95% CI –1.05 to –0.04). Smoking was associated with higher ASDAS over 1 year compared to never smoking in both sexes, although the difference reached statistical significance only in female former smokers. Results were similar in multivariable analysis, adjusted for all lifestyle factors and other confounders. Conclusion In early axSpA, BMI and smoking are associated with higher DA over 1 year, and AC with lower DA. The magnitude of the modest associations may differ between men and women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".