Clinical Manifestations but not Cytokine Profiles Differentiate Adult-onset Still’s Disease and Sepsis
Bibliographic record
Abstract
OBJECTIVE: To analyze clinical manifestations, serum ferritin, and serum cytokine levels in patients with adult-onset Still's disease (AOSD) or bacterial sepsis and to evaluate their potential use for differential diagnosis. METHODS: Twenty-two consecutive patients with the first flare of AOSD and 6 patients with an established diagnosis of AOSD under immunosuppressive therapy were compared with 14 patients with bacterial sepsis. Clinical manifestations were scored in a Pouchot AOSD activity score including elevated serum ferritin levels to obtain a modified Pouchot score. Serum cytokine profiles were analyzed from each patient. RESULTS: The scores of clinical manifestations using a modified Pouchot activity score were significantly higher in patients with active untreated AOSD (mean 5.60 ± 1.93) compared with patients with chronic AOSD (mean 1.16 ± 0.98; p < 0.001) and patients with sepsis (mean 2.38 ± 1.19; p < 0.001). A modified Pouchot score ≥ 4 shows a sensitivity of 92% and a specificity of 93% for active AOSD. Serum cytokine levels of interleukin 1ß (IL-1ß), IL-6, IL-8, IL-10, IL-12, IL-18, interferon-γ, tumor necrosis factor-α, and calprotectin were elevated in acute AOSD and sepsis. Significant differences were detected only in patients with sepsis who had higher levels of IL-6 and IL-8. The overlap of the 2 groups limits the use of cytokines for differential diagnosis in individual patients. CONCLUSION: A modified Pouchot AOSD activity score including elevated serum ferritin levels was more useful to confirm the diagnosis of AOSD compared to patients with sepsis. Elevated serum cytokines correlate with inflammation but are of limited use to differentiate between active AOSD and bacterial sepsis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".