Serum S100A8/A9, But Not Follistatin-like Protein 1 and Interleukin 18, May Be a Useful Biomarker of Disease Activity in Adult-onset Still’s Disease
Bibliographic record
Abstract
OBJECTIVE: S100A8/A9, follistatin-like protein 1, and interleukin 18 (IL-18) have been suggested as biomarkers of disease activity in patients with systemic juvenile idiopathic arthritis or adult-onset Still's disease (AOSD). We investigated the clinical significance of these factors in AOSD. METHODS: Blood samples were collected from 36 patients with AOSD, 40 patients with rheumatoid arthritis (RA), and 33 healthy controls. Of the patients with AOSD, followup samples were collected from 16 patients after resolution of disease activity. RESULTS: Serum levels of S100A8/A9 (11.77 ± 8.84 μg/ml) in AOSD patients were higher than those in RA patients (3.53 ± 3.43 μg/ml; p < 0.001) and controls (2.49 ± 1.83 μg/ml; p < 0.001). Follistatin-like protein 1 levels in AOSD were not different from those in RA and controls. IL-18 levels in AOSD (7560.3 ± 7577.6 pg/ml) were higher than those in RA (217.7 ± 292.1 pg/ml; p < 0.001) and controls (139.2 ± 86.2 pg/ml; p < 0.001). The sensitivity and specificity of IL-18 for diagnosing AOSD was highest with a cutoff value of 366.1 pg/ml. Serum S100A8/A9 correlated with leukocyte count, erythrocyte sedimentation rate, C-reactive protein, ferritin, and systemic disease score; however, IL-18 correlated only with ferritin and systemic disease score. S100A8/A9 was decreased after disease activity was resolved in followup of AOSD patients (9.96 ± 7.35 μg/ml in active AOSD vs 3.6 ± 4.77 μg/ml in resolved cases; p = 0.001). The change of S100A8/A9 was well correlated with that of systemic disease score. CONCLUSION: The data suggest that serum S100A8/A9 may be a useful biomarker for evaluating disease activity in patients with AOSD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".