Is the Double Contour Sign Specific for Gout? Or Only for Crystal Arthritis?
Bibliographic record
Abstract
In this issue of The Journal , Löffler, et al describes a study assessing the sonographic double contour (DC) sign in gout, calcium pyrophosphate crystal deposition (CPPD), and other arthritides1. They investigated the diagnostic value of the DC sign alone and in combination with Doppler signals and serum uric acid (SUA) levels in patients presenting with acute arthritis by examining 225 acutely inflamed joints. Cartilage enhancements presenting as a parallel line to the bony articular surface were defined as the DC sign. All patients underwent synovial fluid analysis that was used to make the diagnosis of gout or CPPD or other arthritides, independent of the joint ultrasound (US) findings. The sensitivity of the DC sign for crystal arthritis was 85% and specificity was 80%. Its specificity for gout was 64%, and for CPPD 52%. The combination of DC sign with hypervascularization in Doppler studies and elevated SUA levels increased specificity for gout to 90% and resulted in a 7-fold increase of likelihood of gout (p < 0.01), albeit at the expense of sensitivity (42%). The study has several strengths, including use of a large patient sample, confirmation of diagnosis by crystal examination, and appropriate acute arthritis controls. The study findings must be interpreted considering potential limitations and these findings need to be compared and contrasted with those from other studies of US in gout. A striking finding of this study reporting the use of US in real-world clinical practice was the inability of the DC sign to differentiate between gout and CPPD. In previous US publications, the differential cartilage … Address correspondence to Dr. J.A. Singh, University of Alabama, Faculty Office Tower 805B, 510 20th St. S, Birmingham, Alabama 35294, USA.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".