Increased Prevalence of Diastolic Heart Failure in Patients with Rheumatoid Arthritis Correlates with Active Disease, but Not with Treatment Type
Bibliographic record
Abstract
OBJECTIVE: Although heart failure (HF) is a major cause of premature mortality, there is little information regarding its prevalence and associated risk factors in patients with rheumatoid arthritis (RA). In this study, we evaluated the prevalence of HF in a community-based RA cohort. Further, we investigated the effect of RA activity and present treatment on HF rate and cardiac structure. METHODS: A diagnostic workup for HF according to the European Society of Cardiology recommendations was performed in 157 patients with RA fulfilling the American College of Rheumatology/European League Against Rheumatism criteria (68% women, age 61 ± 13 yrs) from our outpatient clinic and in 77 age- and sex-matched controls. RESULTS: The prevalence of HF in patients with RA (24%) was unexpectedly high and differed significantly from the control sample (6%, p = 0.001). Diastolic HF was the dominant type (23% vs 6%), and clinical symptoms alone were of low diagnostic value. Active RA (28-joint Disease Activity Score ≥ 2.6: OR 3.4, 95% CI 1.3-9.8) was an independent risk factor of HF, as well as systemic inflammation (erythrocyte sedimentation rate > 16 mm/h: OR 5.4, 95% CI 2.1-16; C-reactive protein > 10 mg/l: OR 2.6, 95% CI 0.8-8.0) and RA duration > 10 years (OR 2.6, 95% CI 1.2-5.8). HF in RA was associated with concentric hypertrophy (48% vs 17%, p < 0.001) and reduced longitudinal strain (-17.2% vs -19.7%, p < 0.001). However, the prevalence of HF was equivalent between the treatment groups [conventional synthetic disease-modifying antirheumatic drugs (DMARD) 25%, tumor necrosis factor inhibitors 22%, other biological DMARD 27%]. CONCLUSION: Recognition of all diastolic HF in RA requires a complex diagnostic approach. Active rather than inactive RA places patients at a higher risk for HF, whereas influence of RA treatment on HF risk needs to be elucidated in further studies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".