Early Local Swelling and Tenderness Are Associated with Large-joint Damage After 8 Years of Treatment to Target in Patients with Recent-onset Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To assess whether early swelling and tenderness in large joints in patients with rheumatoid arthritis (RA) is predictive of later local damage and whether this leads to functional disability. METHODS: Two-year clinical and 8-year radiological followup data from the BeSt study (trial numbers NTR262 and NTR265), a randomized controlled treat-to-target trial, were used. The association between early local joint swelling and/or tenderness (at least once, or for ≥ 2 consecutive visits) and later large-joint damage (Larsen score ≥ 1) was assessed using generalized estimating equations. The association between large-joint damage and functional ability [by Health Assessment Questionnaire (HAQ)] was assessed using logistic and linear regression analysis. RESULTS: Clinical and 8-year radiological data were available for 290 patients. Concomitant local joint swelling and tenderness at least once in the first 2 years was independently associated with damage of the large joints (OR 2.5, 95% CI 1.7-3.6), as was swelling without tenderness (OR 2.0, 95% CI 1.1-3.6). Stronger effects were seen for persistent swelling and/or tenderness. Other independent predictors for joint damage were baseline erythrocyte sedimentation rate (OR 1.01, 95% CI 1.01-1.02) and the presence of rheumatoid factor and/or anticitrullinated protein antibodies (OR 2.5, 95% CI 1.5-4.1; and OR 2.2, 95% CI 1.3-3.8, respectively). Patients with large-joint damage had a higher HAQ score after 8 years than patients without (difference 0.15). CONCLUSION: Early local swelling and tenderness are independent predictors of later joint damage in these joints after 8 years of Disease Activity Score-guided treatment in patients with RA. This suggests that suppression of local inflammation could help prevent local damage and functional disability.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".