Serum Interleukin 18 as a Diagnostic Remission Criterion in Systemic Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
To the Editor: With the development of new therapeutic agents and combination treatment strategies, more children with systemic juvenile idiopathic arthritis (sJIA) can experience protracted periods of low disease activity levels and, in some cases, complete disease quiescence. These advances create a need for the development of validated criteria that precisely describe the clinical state of disease quiescence. We previously reported that serum interleukin 18 (IL-18) levels in patients with sJIA were extremely high during the active phase and remained significantly elevated even when other markers of disease activity normalized1. We also reported that serum IL-18 levels at birth in a healthy infant born to a woman with active adult-onset Still’s disease were markedly increased, and this increase persisted for about 1 month2. These findings indicate that it takes several months for extremely elevated serum IL-18 levels to normalize under physiological conditions. In our study, we serially measured serum IL-18 levels in 11 patients with sJIA (age 10.2 ± 7.6 yrs, male:female = 3:8) until they had relapsed or achieved remission to investigate the kinetics of serum IL-18 levels from the active phase to remission. Further, we investigated the correlation between serum IL-18 and IL-6 levels in these patients. Among 11 patients, 4 patients were enrolled in our previous study1, while 7 patients … Address correspondence to Dr. M. Shimizu, Department of Pediatrics, School of Medicine, Institute of Medical, Pharmaceutical, and Health Sciences, Kanazawa University, 13-1 Takaramachi, Kanazawa 920-8641, Japan. E-mail: shimizum{at}staff.kanazawa-u.ac.jp
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".