Factors Associated With Residual Disease in Axial Spondyloarthritis: Results From a Clinical Practice Registry
Bibliographic record
Abstract
OBJECTIVE: To explore residual disease, defined as substantial symptoms and disease burden despite a remission or low disease activity (LDA) state, in patients with axial spondyloarthritis (axSpA), and to determine which factors are associated with residual disease. METHODS: For this cross-sectional observational study, 1 timepoint per patient was used from SpA-Net, a web-based monitoring registry for SpA. Patients with an Ankylosing Spondylitis Disease Activity Score (ASDAS) < 2.1 (LDA) were included. Indicators of residual disease (outcomes) included fatigue (primary outcome), pain, physical functioning, health-related quality of life (HRQOL), and peripheral symptoms. Sex was the primary explanatory factor for residual disease. Other explanatory factors included demographics and disease-related factors. Associations between these factors and presence and extent of residual disease were explored using logistic and linear regression. RESULTS: = 3.29, 95% CI 1.74-6.20). Other indicators of residual disease (ie, pain, peripheral symptoms, physical HRQOL) were also more severe and/or more prevalent in females. CONCLUSION: Residual disease is frequent in patients with axSpA who are in an LDA state, including remission, and it is particularly prevalent in female patients. Future studies should address how to manage or prevent residual disease in axSpA.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".