Success Rate and Utility of Ultrasound-guided Synovial Biopsies in Clinical Practice
Bibliographic record
Abstract
OBJECTIVE: The utility of synovial biopsy in increasing our understanding of the pathogenesis of inflammatory arthropathies, as well as in evaluating treatments, is well established. Ultrasound (US) allows synovial assessment and therefore assists in biopsying synovial tissue in a safe and well-tolerated manner. This study's objectives were to (1) determine the rate of success in retrieving synovial tissue using US guidance, (2) describe the indications for US-guided synovial biopsies in the clinical setting, (3) determine how frequently the synovial biopsy can lead to a clear diagnosis, and (4) assess the quality of the synovial tissue obtained using this technique. METHODS: Synovial biopsies of small and large joints were performed under US guidance between February 2007 and December 2014 using a semiautomatic core biopsy needle. The biopsy procedure was considered successful if synovial tissue was found at histological examination. RESULTS: Seventy-four patients with undifferentiated arthritis underwent 76 synovial biopsies. The success rate in retrieving synovial tissue was 81.6% (62/76). One patient taking acetyl salicylic acid at 75 mg at the time of the biopsy presented with hemarthrosis 48 h after the procedure, which resolved following simple arthrocentesis. A definitive diagnosis was achieved in 16% of the patients where synovial tissue was sampled successfully. CONCLUSION: US-guided synovial biopsies in clinical practice can be performed safely on patients with undifferentiated arthritis and with heterogeneous presentations. The rate of success in acquiring synovial tissue is high. The procedure usually retrieves quality tissue and leads to a definite diagnosis in a significant minority of patients.
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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 | 0.007 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".