A Systematic Literature Review Analysis of Ultrasound Joint Count and Scoring Systems to Assess Synovitis in Rheumatoid Arthritis According to the OMERACT Filter
Bibliographic record
Abstract
OBJECTIVE: The OMERACT Ultrasound Task Force is currently developing a global synovitis score (GLOSS) with the objective of feasibly measuring global disease activity in patients with rheumatoid arthritis (RA). In order to determine the minimal number of joints to be included in such a scoring system, and to analyze the metric properties of proposed global (i.e., patient level) ultrasound (US) scoring systems of synovitis in RA, a systematic analysis of the literature was performed. METHODS: A systematic literature search of Pubmed and Embase was performed (January 1, 1984, to March 31, 2010). Original research reports written in English including RA, ultrasound, Doppler, and scoring systems were included. The design, subjects, methods, imaging protocols, and performance characteristics studied were analyzed, as well as the ultrasound definition of synovitis. RESULTS: Of 3004 reports identified, 14 articles were included in the review. We found a lack of clear definition of synovitis as well as varying validity data with respect to the proposed scores. Scoring systems included a wide range and number of joints. All analyzed studies assessed construct validity and responsiveness by using clinical examination, laboratory findings, and other imaging modalities as comparators. Both construct validity and responsiveness varied according to the number and size of joints examined and according to the component of synovitis measured [i.e., gray-scale (GS) or power Doppler (PD) alone or in combination]. With regard to feasibility, time of evaluation varied from 15 to 60 min and increased with the number of joints involved in the examination. CONCLUSIONS: Ultrasound can be regarded as a valuable tool for globally examining the extent of synovitis in RA. However, it is presently difficult to determine a minimal number of joints to be included in a global ultrasound score. Further validation of proposed scores is needed.
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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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".