Recommendations for the local management of digital ulcers in systemic sclerosis: A report from the World Scleroderma Foundation (WSF) ‘Ad hoc committee’
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Digital ulcers (DUs) stand out as one of the most prevalent and clinically meaningful manifestations of systemic sclerosis (SSc) and are associated with significant morbidity. While systemic (pharmacological) therapy is currently established as the 'standard of care', effective local ulcer management remains crucial for all cases of DUs. This is particularly true for patients who cannot tolerate systemic treatments or in the case of refractory SSc-DUs. On this background, there is a pressing demand for the formulation of evidence-based guidelines to assist clinicians and patients in navigating the local treatment options for DUs. Methods: A steering committee of international experts was established by the World Scleorderma Foundation (WSF) Digital Ulcer (DU) ad hoc committee. Two systematic literature reviews on local non-surgical and surgical treatments for the management of SSc-DUs were performed to inform the development of local treatment recommendations for SSc-DUs. Consensus methodology was used to develop the final treatment recommendations. Results: Six overarching treatment principles and eight local treatment recommendations (five non-surgical and three surgical) were agreed upon for the management of SSc-DU. Among topical non-surgical options, botulin toxin can be conditionally recommended for refractory and/or severe DUs. Among surgical treatments, autologous adipose tissue grafting might be recommended for DU healing when combined with background systemic treatments. Conclusion: These recommendations are specifically tailored to guide treatment decisions concerning both local and non-pharmacological approaches to managing SSc-related DUs. Our work has highlighted a notable quality gap in comparison to systemic treatments, underscoring the scarcity of high-quality studies concerning this topic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it