A Comparison of Radiographic Joint Space Width Measurements Versus Ultrasonographic Assessment of Cartilage Thickness in Children with Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Joint space narrowing (JSN) is a measurable outcome of tissue degeneration in arthritis. JSN is usually assessed by conventional radiography. Ultrasonographic (US) measurement of joint cartilage thickness has been validated in healthy children, and US measurement of the distal femoral cartilage has been validated in a group of patients with juvenile idiopathic arthritis (JIA). Our aim was to compare the measures of cartilage thickness of the proximal cartilage site in the second metacarpophalangeal (MCP), second proximal interphalangeal (PIP), and knee joints as assessed by US to joint space width (JSW) as measured by computerized radiography in children with JIA. METHODS: The study included 74 children with JIA aged 5-15 years (median 11.3 yrs). MCP and PIP joints were assessed at one midline spot. Knee joints were assessed at the medial and lateral femoral condylar areas. Only the proximal cartilage site in the joints was assessed by US, whereas the complete JSW was assessed by radiography. RESULTS: We assessed 136 second MCP, 138 second PIP, and 146 knee joints. We found a high level of agreement between US and radiographic measures of cartilage thickness and JSW: r = 0.82-0.86 (second MCP), r = 0.50-0.55 (second PIP), and r = 0.52-0.81 (knee); p < 0.001 for all 8 assessed sites. CONCLUSION: US measurements of cartilage thickness of the proximal site of the second MCP, second PIP, and knee joints correlated well with radiographic JSW measurements in the finger and knee joints of children with JIA. However, US does not measure the distal cartilage, which may limit its use in the assessment of JSN.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".