Absence of Fibrosis and Inflammation by Cardiac Magnetic Resonance Imaging in Rheumatoid Arthritis Patients with Low to Moderate Disease Activity
Bibliographic record
Abstract
OBJECTIVE: The prevalence of heart failure is increased 2-fold in patients with rheumatoid arthritis (RA); this is not explained by ischemic heart disease or other risk factors for heart failure. We hypothesized that in patients with RA without known heart disease, cardiac magnetic resonance imaging (cMRI) would detect altered cardiac structure, function, and fibrosis. METHODS: We performed 1.5-T cMRI in 59 patients with RA and 56 controls frequency-matched for age, race, and sex, and compared cMRI indices of structure, function, and fibrosis [late gadolinium enhancement (LGE), native T1 mapping, and extracellular volume (ECV)] using Mann-Whitney U tests and linear regression, adjusting for age, race, and sex. RESULTS: Most patients with RA had low to moderate disease activity [28-joint count Disease Activity Score-C-reactive protein median 3.16, interquartile range (IQR) 2.03-4.05], and 49% were receiving anti-tumor necrosis factor agents. Left ventricular (LV) mass, LV end-diastolic and -systolic volumes indexed to body surface area, and LV ejection fraction and left atrial size were not altered in RA compared to controls (all p > 0.05). Measures of fibrosis were not increased in RA: LGE was present in 2 patients with RA and 1 control subject; native T1 mapping was similar comparing RA and control subjects, and ECV (median, IQR) was lower (26.6%, 24.7-28.5%) in patients with RA compared to control subjects (27.5%, 25.4-30.4%, p = 0.03). CONCLUSION: cMRI measures of cardiac structure and function were not significantly altered, and measures of fibrosis were similar or lower in RA patients with low to moderate disease activity compared to a matched control group.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".