Ultrasound of Synovitis in Rheumatoid Arthritis: Advantages of the Dorsal over the Palmar Approach to Finger Joints
Bibliographic record
Abstract
OBJECTIVE: To compare the dorsal and palmar ultrasound (US) examination of finger joints in early rheumatoid arthritis (RA) with regard to the concurrence of greyscale (GSUS) and power Doppler (PDUS) positivity, and to correlate both approaches with clinical variables. METHODS: Patients with newly diagnosed RA were assessed by clinical examination and US. GSUS and PDUS of metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints were performed using the dorsal and palmar approach. Findings of synovitis in GSUS and PDUS were graded semiquantitatively from 0 to 3. Clinical and sonographic reevaluation was performed after 6 months. RESULTS: With 44.6% versus 32.2% positive findings, palmar GSUS identified significantly more joints with synovitis than did dorsal GSUS. With 22.1% versus 8.9%, PDUS abnormalities were detected significantly more often from the dorsal side. With 71.2% versus 21.8% for the MCP and 57.5% versus 17.4% for the PIP joints, significantly more GSUS and PDUS double-positive joints were found with the dorsal as opposed to the palmar approach. These differences remained significant at Month 6. Both palmar and dorsal GSUS and PDUS correlated with comparable strength with clinical variables such as the Disease Activity Score 28, Clinical Disease Activity Index, and Simple Disease Activity Index. CONCLUSION: Although the dorsal approach detected fewer GSUS findings than the palmar approach, PDUS signals were significantly more frequently detected by dorsal US. In addition, the prevalence of double-positive joints with concurrent GSUS and PDUS findings was significantly higher with the dorsal approach. These data argue in favor of the dorsal US approach to finger joints in 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".