Inflammation and Disease Activity are Associated with High Circulating Cardiac Markers in Rheumatoid Arthritis Independently of Traditional Cardiovascular Risk Factors
Bibliographic record
Abstract
OBJECTIVE: To measure concentrations of high-sensitivity cardiac troponin (HS-cTnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with rheumatoid arthritis (RA) and to examine correlates. METHODS: The plasma concentrations of HS-cTnT and NT-proBNP were measured in consecutive patients with RA and compared to values obtained from age-matched and sex-matched healthy controls. RESULTS: We included 236 unrelated patients with RA (192 females, 57 ± 13 yrs) and 213 controls (170 females, 55 ± 15 yrs). Seventy-one patients with RA were free of cardiovascular (CV) risk factors. HS-cTnT and NT-proBNP concentrations were significantly higher in the total cohort of patients with RA (p = 0.03 and p < 0.0001, respectively) and in the subgroup free of CV risk factors (p = 0.02 and p < 0.0001, respectively) compared to controls. In addition, both the total cohort of patients with RA and the subgroup free of CV risk factors were more likely to have levels above the cutoff concentrations of HS-cTnT (p = 0.003 and p = 0.007, respectively) and NT-proBNP (p = 0.0001 and p < 0.0001, respectively) than controls. Patients with RA and increased C-reactive protein (CRP) levels had higher HS-cTnT (p = 0.03) and NT-proBNP (p = 0.02) concentrations. HS-cTnT levels positively correlated with the 28-joint Disease Activity Score (DAS28-CRP; r = 0.2, p = 0.020). Multivariate logistic regression analysis indicated that increased HS-cTnT levels were independently associated with a DAS28-CRP > 5.1 (OR 11.8; 95% CI 1.6-35.5) and a body mass index > 30 kg/m(2) (OR 2.7; 95% CI 1.3-5.5). CONCLUSION: HS-cTnT and NTproBNP are increased in patients with RA, independent of CV risk factors. The association between HS-cTnT, NT-proBNP, and CRP, together with the correlation between HS-cTnT and disease activity, support the link between myocardial injury/dysfunction and inflammation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".