Enhanced thrombin generation potential and endothelial dysfunction in chronic spontaneous urticaria
Bibliographic record
Abstract
Enhanced thrombin generation potential and endothelial dysfunction in chronic spontaneous urticariaTo the Editor, Chronic spontaneous urticaria (CSU) is characterized by recurrent hives that last longer than 6 weeks.The relationship between the coagulation cascade, endothelial cell (EC) activation and urticaria pathogenesis is acknowledged but remains poorly understood.1,2 Examination of these pathways may offer opportunities for improved disease endotyping, prognostication and novel therapeutic avenues.Mast cells and eosinophils are known to be important in CSU pathogenesis.3,4 Mast cell degranulation results in the generation of leukotrienes and mast cell-derived mediators.Resulting EC activation promotes vascular permeability.Activated eosinophils express tissue factor, which initiates coagulation via Factor VII. 3 Despite our understanding of these pathways, the distinct profiles of coagulation times than those who were receiving anti-IgE therapy (p = 0.0264, 95% confidence interval -2.903 to -0.2045).This implies that patients who were on anti-IgE therapy took longer to generate thrombin.A previous study on the effect of anti-IgE therapy on TG in CSU found a significant effect on Factor 1 and Factor 2 with no other significant change in TGA parameters.8 Future research may benefit from examining the links between disease control and TG profiles.Despite the interpretive constraints of our small sample size, this study identifies for the first time, a relationship between VWF:Ag, FVIII:C and TG in CSU.Elevated plasma VWF has been reported as a marker of EC dysfunction in a range of clinical conditions reflecting acute and chronic endothelial activation.6,7,9 Our findings point to
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".