Detection of Active Disease in Juvenile Idiopathic Arthritis: Sensitivity and Specificity of the Physical Examination vs Ultrasound
Bibliographic record
Abstract
OBJECTIVE: To determine sensitivity and specificity of the physical examination (PE) for identifying synovitis in the knee and ankle joints of children with juvenile idiopathic arthritis (JIA), and to identify cases in which ultrasound (US) screening augments the PE. METHODS: Nineteen patients with JIA were referred for US. Both knees and ankles were examined using US with and without power Doppler. Active arthritis on PE was defined as (1) non-bony swelling or (2) limitation of motion with either pain on motion or tenderness to palpation. Active arthritis on US was defined as synovial hyperplasia, effusion, or increased vascularity on power Doppler scan. RESULTS: There was agreement between US and PE in 75% of cases. PE was 64% sensitive and 86% specific for identifying active arthritis. PE was 100% specific if (1) the patient was positive for both PE criteria or (2) if arthritis was present on PE in the knees. When the PE was negative and the US was positive, 21.4% developed active disease on PE within 6 months. In cases where the PE was positive and US was negative, the joint involved was most often the ankle and frequently the subtalar joint. CONCLUSION: PE is neither highly sensitive nor specific for identifying active synovitis when compared to US, and screening with US can identify subclinical disease. In joints with both non-bony swelling and limitation of motion with pain on motion or tenderness, and in the knee joint, little additional information is gained by US. This has implications for classification and treatment of JIA.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| 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".