Biomarkers in Remission According to Different Criteria in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Remission is the primary aim in the treatment of patients with rheumatoid arthritis (RA). In this study, we aimed to evaluate biomarker profiles of patients in remission by different criteria and compare these profiles with controls. METHODS: Serum levels of calprotectin, interleukin 6 (IL-6), type II collagen helical peptide, C-terminal crosslinking telopeptide of type I collagen generated by matrix metalloproteinases (ICTP), matrix metalloproteinase 3 (MMP-3), resistin, and leptin were measured by ELISA in 80 patients. The patients were in Disease Activity Score at 28 joints with erythrocyte sedimentation rate (DAS28-ESR) remission, and had these characteristics: female/male 54/26, mean age 51.4 ± 12.1 years, mean disease duration 11.4 ± 8.1 years, rheumatoid factor positivity 68.7% (n = 55), anticyclic citrullinated peptide positivity 60.7% (n = 48). These patients were also evaluated for the American College of Rheumatology/European League Against Rheumatism (Boolean) and Simple Disease Activity Index (SDAI) remissions. Additionally, 80 age-, sex-, and comorbidity-matched individuals without rheumatic diseases were included in the study as controls. RESULTS: At recruitment of 80 patients in DAS28 remission, 33 patients (41.2%) were found in Boolean remission and 39 patients (48.7%) were in SDAI remission. Serum MMP-3, ICTP, resistin, and IL-6 levels of the 80 patients in DAS28 remission were statistically significantly higher than the controls. Patients in Boolean and SDAI remissions had significantly higher serum ICTP, resistin, and IL-6 levels in comparison with the controls. CONCLUSION: The 3 commonly used remission criteria of RA are almost similar with regard to patients' biomarker levels. Biomarker profiles of patients may provide complementary information to clinical evaluation of remission and may help to determine the patients under the risk of progression.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".