Levels of Plasma-soluble Triggering Receptor Expressed on Myeloid Cells-1 (sTREM-1) Are Correlated with Disease Activity in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To determine whether levels of plasma-soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) are elevated in patients with rheumatoid arthritis (RA) and whether levels are correlated with disease activity and other variables. METHODS: Our study included 71 patients with RA and 50 age- and sex-matched healthy controls. Clinical characteristics and laboratory measures, including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and 28-joint Disease Activity Score (DAS28) were assessed. Plasma levels of sTREM-1 and tumor necrosis factor-α (TNF-α) were measured by ELISA. RESULTS: Patients with RA had significantly higher plasma sTREM-1 levels than healthy controls (170.10 ± 84.71 pg/ml vs 97.41 ± 40.64 pg/ml; p < 0.001). In patients with RA, plasma sTREM-1 levels were found to be correlated with DAS28, ESR, CRP, white blood cell counts, neutrophil counts, and plasma TNF-α levels (r = 0.329, p = 0.005; r = 0.241, p = 0.043; r = 0.314, p < 0.001; r = 0.261, p = 0.028; r = 0.278, p = 0.019; and r = 0.313, p = 0.009, respectively). Plasma sTREM-1 levels in patients with active disease status (DAS28 > 3.2) were significantly higher than in those with low disease status (DAS28 ≤ 3.2; 208.89 ± 100.14 pg/ml vs 150.29 ± 68.70 pg/ml; p = 0.005). CONCLUSION: Patients with RA had higher plasma sTREM-1 levels than healthy controls, and plasma sTREM-1 levels were correlated with disease activity measures, suggesting that plasma sTREM-1 could play a role in the inflammatory process associated with TNF-α, and that it may be a useful disease activity marker in RA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".