Comparison of Clinical Examination versus Whole-body Magnetic Resonance Imaging of Enthesitis in Patients with Early Axial Spondyloarthritis during 3 Years of Continuous Etanercept Treatment
Bibliographic record
Abstract
OBJECTIVE: To compare clinical examination versus whole-body magnetic resonance imaging (WB-MRI) of enthesitis in patients with early axial spondyloarthritis during 3 years of continuous etanercept (ETN) treatment. METHODS: Forty-one patients underwent clinical and WB-MRI examinations for enthesitis at baseline and after 2 and 3 years of treatment. Twenty-one sites were assessed in 4 anatomic regions - anterior chest wall, pelvis, knee, and foot. RESULTS: Clinical examination at baseline detected enthesitis in 57% of the patients (85 lesions, mean 2.1 lesions, SD 2.9), most of them in the pelvis (42 lesions in 17 patients) and anterior chest wall (19 lesions in 10 patients). The proportion of patients with clinically detected enthesitis decreased to 19% at Year 2 (mean 0.5, SD 1.5) and 14% at Year 3 (mean 0.7, SD 1.8). WB-MRI detected enthesitis at baseline in 21% of patients (22 lesions, mean 0.5 lesions, SD 1.1), also most frequently in the pelvis (12 lesions) and anterior chest wall (7 lesions). MRI-positive enthesitis decreased to 13% at Year 2 (mean 0.2 lesions, SD 0.5) and 14% at Year 3 (mean 0.2 lesions, SD 0.5). There was positive correlation of clinical and MRI findings at baseline at the anterior chest wall (p = 0.001) and the pelvis (p = 0.0001). No correlation was found at the knee and foot at baseline and for all regions at followup. CONCLUSION: Both clinical examination and WB-MRI show a decrease in enthesitis after 2 and 3 years of ETN treatment, but correlation was limited to the pelvis and anterior chest wall at baseline.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".