Impaired Fibrinolysis Is Linked With Digital Vasculopathy and Onset of New Digital Ulcers in Systemic Sclerosis
Bibliographic record
Abstract
Objective. To assess thrombin generation, fibrin formation, and structure together with the fibrinolytic status in patients with systemic sclerosis (SSc) in relation to the occurrence of digital ulcers (DUs) during the course of disease. Methods. We studied variables of endothelial dysfunction, thrombin generation, overall hemostatic potential, and fibrin clot turbidity in plasma from 58 patients with SSc (39 with DU history and 19 DU-naïve) and 46 matched healthy controls (HCs). Fibrin structure was visualized using scanning electron microscopy (SEM). Finally, 39 patients with a history of DUs were followed for 1.5 years and the predictive value of all investigated markers for new DU onset was explored. Results. Significantly enhanced endogenous thrombin potential (ETP) and prolonged clot lysis time (CLT) were found in patients with DUs compared to HCs. CLT was prolonged in patients with DUs compared to those without, showing good validity in identifying DUs with an area under the curve of 0.7 (95% CI 0.6–0.8). The levels of ETP and intercellular adhesion molecule 1 were independently associated with CLT. Over the follow-up period, 20 patients developed new DUs. CLT was prolonged (P < 0.001) in patients with new DU episodes, especially those with recurrent DUs. Regression analysis showed that the Raynaud phenomenon visual analog scale and CLT were predictors of new DUs (OR 1.1, 95% CI 1.0–1.1 and OR 1.2, 95% CI 1.1–1.3, respectively). SEM confirmed denser fibrin clots in patients with new DUs. Conclusion. Our results suggest that impaired fibrinolysis might have an emerging role in underlying digital vasculopathy and its progression in 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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".