Pulse Wave Velocity in Systemic Sclerosis: Potential Beneficial Effects of Bosentan on Forearm Arterial Stiffness? An Exploratory Study
Bibliographic record
Abstract
To the Editor: Treatment of digital ischemia in systemic sclerosis (SSc) remains a challenge. Although vasculopathy is generally thought to occur on a microvascular level, some observations suggest the involvement of medium-sized arteries as well. In patients with advanced disease, obliteration of the ulnar artery is frequently observed, associated with an adverse outcome1. A potential mechanism is arterial wall fibrosis. Arterial stiffness may be an easily identifiable sign of vasculopathy, early in the disease course, assessed noninvasively by pulse wave velocity (PWV). Although several studies have assessed aortic and upper extremity PWV in SSc, studies specifically on forearm PWV are limited2–8. Further, the effect of treatment on PWV has not been previously studied in SSc. Since endothelin-1 plays an important role in SSc vasculopathy and promotes arterial stiffness in animal models9, we hypothesize that the dual endothelin receptor antagonist bosentan may potentially improve arterial stiffness in SSc. This exploratory study compared PWV in patients with limited cutaneous SSc (lcSSc) with age- and sex-matched healthy controls (HC) at baseline. Second, the effect of bosentan (62.5 mg twice daily, titrated to 125 mg twice daily after 1 mo if tolerated) was investigated on PWV … Address correspondence to Dr. A.M. van Roon, University Medical Center Groningen, Huispostcode AA41, Hanzeplein 1, Postbus 30 001, Groningen, the Netherlands. Email: a.m.van.roon01{at}umcg.nl.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".