Relations of Serum COMP to Cardiovascular Risk Factors and Endothelial Function in Patients with Rheumatoid Arthritis Treated with Methotrexate and TNF-α Inhibitors
Bibliographic record
Abstract
OBJECTIVE: To examine whether serum level of cartilage oligomeric matrix protein (S-COMP) is related to methotrexate (MTX) or to MTX and tumor necrosis factor-α (TNF-α) combination treatment for rheumatoid arthritis (RA); and to investigate whether S-COMP is related to cardiovascular risk factors including endothelial dysfunction and level of anticitrullinated protein antibodies (ACPA) in patients with RA. METHODS: Clinical and laboratory measures, including S-COMP and reactive hyperemic index (RHI), were examined in 55 consecutive patients with RA starting with either MTX (n = 34) or MTX and anti-TNF-α treatment (n = 21) at baseline, and after 6 weeks and 6 months. RESULTS: S-COMP was similar in the 2 treatment regimens during followup. We found a positive relationship between S-COMP at baseline and the use of disease-modifying antirheumatic drugs the last year preceding the study (p = 0.001), and a negative relation to current use of systemic glucocorticosteroids (p = 0.044). The nonsignificant change in S-COMP between baseline and the 6-month followup was positively and independently related to change in ACPA level (p = 0.009). There was no significant association between RHI and level of S-COMP at baseline. CONCLUSION: The cartilage turnover marker S-COMP did not change significantly after 6 months' treatment with MTX with or without a TNF-α inhibitor in patients with RA. The positive association between S-COMP and ACPA suggests that these factors might interact, and could both be contributors to an unknown link between inflammation and cartilage destruction in patients with RA. S-COMP was not related to endothelial function in patients with RA, or to other cardiovascular risk factors studied. Clinical Trials registration number NCT00902005.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".