The Scleroderma Tango: Unraveling the Delicate Dance of Diastolic Dysfunction and Interstitial Lung Disease
Bibliographic record
Abstract
In this issue of The Journal of Rheumatology , Fairley and colleagues investigated the effects of concomitant left ventricular diastolic dysfunction (LVDD) in a small cohort of patients with systemic sclerosis (SSc)-associated interstitial lung disease (ILD) derived from the larger Australian Scleroderma Cohort Study.1 Consistent with prior reports, the authors found that patients with SSc-ILD with LVDD experienced dyspnea and reduced survival. In addition, these patients were older, had longer SSc disease duration exceeding 6 years, received treatment with immunosuppressive drugs, and had additional cardiovascular (CV) comorbidities. SSc-specific features, such as skeletal muscle involvement, chronic inflammation, and gastrointestinal issues, were shown to further elevate the risk of LVDD. The significant correlation of LVDD with muscle atrophy suggests a potential association between LVDD and myopathy or physical frailty in SSc-ILD. Regardless of the underlying mechanism, the presence of LVDD was consistently linked to diminished survival and increased breathlessness in patients with SSc-ILD. Numerous studies have emphasized the significance of SSc-associated LVDD, a disease characterized by pathogenic replacement myocardial fibrosis and … Address correspondence to Dr. M. Mukherjee, Johns Hopkins University School of Medicine, 301 Mason Lord Drive, Suite 2400, Baltimore, MD 21224, USA. Email: mmukher2{at}jhu.edu.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".