Hand and Wrist Involvement in Systemic Sclerosis: US Features
Bibliographic record
Abstract
PURPOSE: To characterize ultrasonographic (US) features in the hand of patients with systemic sclerosis (SSc) and to evaluate the sensitivity of US in the detection of calcinosis and acroosteolysis. MATERIALS AND METHODS: The local ethics committee approved this study, and oral informed consent was obtained. A total of 44 consecutive patients with SSc (34 women; mean age, 56.1 years ± 12.1 [standard deviation]; 10 men; mean age, 45.0 years ± 14.0) and 30 healthy control subjects (20 women; mean age, 46.3 years ± 12.1; 10 men; mean age, 39.6 years ± 10.8) were included between October 2010 and December 2011. Bilateral US, including Doppler assessment of the wrists, hands, and fingers, was performed, and presence of synovitis, tenosynovitis with or without a layered appearance, calcifications, acroosteolysis, and distal vascularization was recorded. Radiography of both hands was performed to assess for acroosteolysis and calcinosis. Frequency of US features, sensitivity of US for calcinosis and acroosteolysis, and respective confidence intervals were calculated. RESULTS: Synovitis was found in 17 patients (39%). Tenosynovitis was found in 12 patients (27%), and it had a layered pattern in 15 (41%) of 37 cases. Calcinosis was found in 17 patients (39%) with US, with a sensitivity of 89%. Acroosteolysis was found in nine (20%) patients with US and in 10 (23%) patients with radiography, with 90% sensitivity for US. Distal vascularization was detected in 26 patients (59%) and 30 control subjects (100%) and was in contact with the acroosteolysis bed in seven (78%) of nine patients with SSc. CONCLUSION: US can be used to assess features of SSc, including synovitis, tenosynovitis, calcinosis, acroosteolysis, and distal vascularization and is sensitive for calcinosis and acroosteolysis detection. A layered pattern (similar to the appearance of an artichoke heart) of tenosynovitis was seen commonly. Online supplemental material is available for this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".