Whole-body Magnetic Resonance Imaging Inflammation in Peripheral Joints and Entheses in Axial Spondyloarthritis: Distribution and Changes during Adalimumab Treatment
Bibliographic record
Abstract
OBJECTIVE: To investigate the distribution of whole-body magnetic resonance imaging (WB-MRI) inflammatory lesions of peripheral joints and entheses, and their response to adalimumab (ADA) treatment and agreement with clinical measures of disease activity in patients with axial spondyloarthritis (axSpA). METHODS: Explorative analysis of an investigator-initiated randomized controlled trial of ADA. WB-MRI was performed at weeks 0, 6, 24, and 48. Detailed analyses of WB-MRI lesions in peripheral joints and entheses were performed, including agreement with clinical measures of disease activity. RESULTS: WB-MRI inflammatory lesions were most frequently observed in the acromioclavicular, metatarsophalangeal, and wrist joints (> 10% of joints), and at the greater trochanter, calcaneal insertion of the Achilles tendon, and ischial tuberosity (> 15% of entheses). Inflammation resolved in ≥ 2/3 of involved sternoclavicular, metacarpophalangeal, first carpometacarpal, hip, and tarsometatarsal joints, and pubic symphyses and medial femoral condyles. In contrast, inflammation resolved in ≤ 1/6 of involved acromioclavicular joints, knee joints, and supraspinatus tendon insertions at humerus. Tenderness of joints and entheses agreed poorly with WB-MRI inflammation (κ < 0.40). Joint tenderness resolved more frequently in MRI-positive than MRI-negative joints (8/13, 62% vs 9/34, 26%) after 6 weeks of active treatment. CONCLUSION: Inflammatory lesions of peripheral joints and entheses in patients with predominantly axSpA, and changes therein, can be mapped using WB-MRI, and it may contribute to differentiate between inflammatory and noninflammatory joint tenderness. (Trial registration: ClinicalTrials NCT01029847).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".