Evaluation of whether extremely high enthesitis or Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) scores suggest fibromyalgia and confound the anti-TNF response in early non-radiographic axial spondyloarthritis.
Bibliographic record
Abstract
OBJECTIVES: Differentiating between pain from spondyloarthritis (SpA) and pain from fibromyalgia is challenging. We evaluated patients with non-radiographic axial SpA (nr-axSpA) to determine the percentage of patients with extremely high enthesitis and/or Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) scores, the relationship between extreme scores and depression, and the effect of extreme scores on treatment outcomes with etanercept. METHODS: Patients with nr-axSpA received double-blind etanercept 50 mg or placebo weekly and were divided into those who did vs did not have extreme scores at baseline. Extreme scores were defined as the highest quintile for enthesitis score (≥6), and/or scores ≥8 on three of five BASDAI items (excluding morning stiffness duration). Depression was assessed with the Hospital Anxiety and Depression Scale, depression subscale (HADS-D) and medication use. Week 12 outcomes included Assessment of SpondyloArthritis (ASAS) 40 and ASAS partial remission. RESULTS: At baseline, 35/213 (16.4%) patients met extreme enthesitis criteria, 31 (14.6%) met extreme BASDAI criteria, 12 (5.6%) met both, and 135 (63.4%) met neither. More patients with extreme scores than without met the HADS-D definition of depression: 35/68 (51.5%) vs. 27/118 (22.9%), p<0.0001. For patients with vs. without extreme scores who received etanercept, no significant difference existed in week 12 ASAS 40: 13/41 (31.7%) vs. 21/60 (35.0%), respectively, or ASAS partial remission: 8/41 (19.5%) vs. 19/60 (31.7%). CONCLUSIONS: Extreme enthesitis and/or BASDAI scores were associated with measurements of depression, but did not affect week 12 ASAS 40 or ASAS partial remission.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".