Childhood-Onset Sacroiliitis
Bibliographic record
Abstract
OBJECTIVE: The aims of this study were to describe disease associations of magnetic resonance imaging (MRI)-confirmed and clinically symptomatic sacroiliitis in pediatric patients with rheumatic diseases and to examine the relationship between patient characteristics and MRI findings of the sacroiliac joint (SIJ). METHODS: Demographic and clinical data were extracted from the electronic medical records of the patients with sacroiliitis followed in the last 5 years. Active inflammatory and structural damage lesions of the SIJ-MRI were examined by the modified Spondyloarthritis Research Consortium of Canada scoring system, and correlation analysis of these results with clinical characteristics was evaluated. RESULTS: A total of 46 symptomatic patients were found to have MRI-proven sacroiliitis of 3 different etiologies: juvenile idiopathic arthritis (JIA) (n = 17), familial Mediterranean fever (FMF) (n = 14), and chronic nonbacterial osteomyelitis (CNO) (n = 8). Seven patients, FMF and JIA (n = 6) and FMF and CNO (n = 1), had a co-diagnosis that might cause sacroiliitis. Although inflammation scores and structural damage lesions did not statistically differ between the groups, capsulitis and enthesitis on the MRI were more frequently detected in the CNO group. There was a negative correlation between symptom onset and inflammation scores of bone marrow edema. Disease composite scores and acute phase reactants were correlated with MRI inflammation scores. CONCLUSIONS: We demonstrated that JIA, FMF, and CNO were the major rheumatic causes of sacroiliitis in children originating from the Mediterranean region. Quantitative MRI scoring tools can be used to assess the inflammation and damage of the SIJ in rheumatic diseases, show discrepancies between them, and have an important correlation with various clinical and laboratory features.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".