The Challenge of Very Early Systemic Sclerosis: A Combination of Mild and Early Disease?
Bibliographic record
Abstract
OBJECTIVE: To address the hypothesis that very early patients with systemic sclerosis (SSc) are a heterogeneous group with mild or early disease, we analyzed the extent of heterogeneity in clinical, epidemiological, and immunological characteristics of these patients. METHODS: We performed an analysis of very early SSc patients from the Zurich cohort, who fulfilled neither the 2013 American College of Rheumatology (ACR)/European League Against Rheumatism nor the 1980 ACR classification criteria, but had a clinical expert diagnosis of SSc with Raynaud phenomenon (RP) and additional features of SSc (puffy fingers, SSc-specific antibodies, SSc pattern on nailfold capillaroscopy, or any organ involvement characteristic for SSc). Disease duration was defined from first RP symptom. RESULTS: One hundred and two patients fulfilled the inclusion criteria and were analyzed. Their clinical presentation was heterogeneous with the large majority presenting with RP, antinuclear antibodies, and nailfold capillaroscopy changes, but with varying presentations of other features such as SSc-specific antibodies and early signs of organ involvement. While 54.1% (52/96) of patients had a disease duration of < 5 years, as many as 29.1% (28/96) of patients had a disease duration of > 10 years, indicating long-standing mild disease. Patients with very early, potentially progressive disease did not differ from patients with long-standing mild disease in terms of their clinical features at first presentation. CONCLUSION: This study showed that patients with very early SSc are a mixture with mild or early disease. This needs to be considered in clinical practice for risk stratification and for the study design of patients considered as early SSc.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".