Can Magnetic Resonance Imaging Differentiate Undifferentiated Arthritis Based on Knee Imaging?
Bibliographic record
Abstract
OBJECTIVE: To compare findings as observed on enhanced magnetic resonance imaging (MRI) of the knee joints, in oligoarticular-undifferentiated arthritis (UA) in those with established rheumatoid arthritis (RA) and spondyloarthropathy (SpA). METHODS: A total of 55 patients with knee arthritis were consecutively recruited for the study, including 25 with undifferentiated oligoarthritis of the knee joint(s), 15 fulfilling the American College of Rheumatology criteria for RA and 15 with SpA. Laboratory investigations included erythrocyte sedimentation rate, C-reactive protein, complete blood count, aspartate aminotransferase, alanine aminotransferase, serum creatinine, and urine analysis. In all patients in the UA and in the RA group, rheumatoid factor and anti-CCP2 antibody (ELISA) were tested. All patients underwent enhanced MRI of the more symptomatic knee. All groups were compared in terms of demographics, laboratory investigations, and MRI findings. RESULTS: Synovial thickness differed significantly in the RA group compared to UA and SpA groups (p < 0.001). The RA group showed a higher rate of bony and cartilaginous erosions and bone marrow edema compared to UA and SpA groups (p < 0.001). Enthesitis was found in all patients in the SpA group (100%) and differed from RA and UA groups (p < 0.001). CONCLUSION: Patients with RA showed more destructive changes in terms of synovial thickening, bone marrow edema, cartilaginous and bone erosions compared to UA and SpA groups. Enthesitis is a common feature on MRI in SpA, while absent in the RA and UA groups. This latter finding may have important clinical implications for classification purposes, and can help to determine the evolving pattern of patients with UA of the knee joint.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".