Early prediction of rheumatoid arthritis by magnetic resonance imaging in the absence of anti‐cyclic citrullinated peptide antibodies and radiographic erosions in undifferentiated inflammatory arthritis patients: a prospective study
Bibliographic record
Abstract
OBJECTIVE: To assess the practicability of magnetic resonance imaging (MRI) in confirming the diagnosis of clinically suspected rheumatoid arthritis (RA), when anti-cyclic citrullinated peptide antibody and radiographic erosions are absent. METHODS: We prospectively involved 31 treatment-naive patients with early inflammatory arthritis. At the initial visit, X-rays and gadolinium-enhanced MRI of both hands, as well as serological examinations and acute phase reactants were performed. The scores of synovitis, bone edema, bone erosion and tenosynovitis of metacarpophalangeal and wrist joints were evaluated using the RA-MRI scoring system. For all the patients, radiographs at baseline were normal and anti-cyclic citrullinated peptide antibodies were negative. RESULTS: At the end of follow-up(median 15 months, range 12-20 months), 22 patients were diagnosed as having RA according to 1987 American College of Rheumatology criteria. Bone edema, erosions, synovitis and tenosynovitis were observed in all the patients. However, the frequency of symmetric synovitis in wrists was significantly higher in the RA group. Moreover this group turned out to have significantly higher MRI bone erosion score in wrists. Further, receiver operating characteristic curve analysis revealed a positive wrist bone erosion score at 5, with a specificity of 78% and a sensitivity of 68%. There was no significant difference between the two groups with respect to metacarpophalangeal synovitis, metacarpophalangeal bone erosion, bone edema or tenosynovitis. CONCLUSION: MRI evidence of symmetric synovitis at wrist and a high bone erosion score at that site may assist in making an early diagnosis of RA in those patients who are negative for anti-cyclic citrullinated peptide antibody.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".