Ultrasound is not associated with the presence of systemic autoimmunity or symptoms in individuals at risk for rheumatoid arthritis
Bibliographic record
Abstract
Objective: To identify whether musculoskeletal ultrasound (MSUS) abnormalities are associated with specific phases of rheumatoid arthritis (RA) development in individuals at risk of RA. Methods: This is a prospective cohort study of individuals at risk of developing RA, namely first-degree relatives of patients with RA (RA-FDRs) without evidence of established rheumatic disease at inclusion. The inflammatory activity on MSUS was assessed according to a validated score (SONAR). Active MSUS was defined as a total B-mode score greater than 8, including at least one joint with significant synovitis (grade 2 or 3) or significant synovial hyperaemia (Doppler score greater than 1). We used logistic regression to analyse associations between MSUS findings and recognised preclinical phases of RA development, adjusting for other demographic and biological characteristics. Results: A total of 273 RA-FDRs were analysed, of whom 23 (8%) were anticitrullinated protein autoantibodies-positive, 58 (21%) had unclassified arthritis and 96 (35%) had an active MSUS, which was only associated with unclassified arthritis (OR: 1.8, 95% CI 1.0 to 3.3). Conclusion: In individuals at risk of RA, active MSUS was associated with the presence of unclassified arthritis, but not with any of the earlier described phases of RA development. These findings do not support an indiscriminate use of ultrasound in a screening strategy for preclinical RA.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".