Clinical phenotype and pathophysiological mechanisms underlying qualitative low VWF
Bibliographic record
Abstract
ABSTRACT: Previous reports have highlighted that some patients with low von Willebrand factor (VWF) with significant bleeding were diagnosed based on an isolated but persistent reduction in plasma VWF activity levels in the 30 to 50 IU/dL range. These patients had plasma VWF antigen (VWF:Ag) levels >50 IU/dL and thus had qualitative low VWF (low VWF-QL) rather than quantitative low VWF. Although the clinical importance of functional VWF defects in type 2 von Willebrand disease (VWD) is well recognized, the translational implications of mild functional defects in patients with low VWF-QL have not been defined. To address this clinically important question, we combined low VWF data sets from the low VWF in Ireland cohort and the low VWF in Erasmus MC studies. Overall, we observed that low VWF-QL was common and accounted for ∼50% of our combined low VWF cohort. Importantly, our findings demonstrated that many of these patients with mild isolated functional VWF defects in the 30 to 50 IU/dL range had significant bleeding phenotypes, although their plasma VWF:Ag levels were within the normal range. In addition, we further showed that low VWF-QL is a distinct clinicopathological entity compared to type 2 VWD. Finally, our studies highlighted that low VWF-QL is predominantly caused by abnormalities in VWF biosynthesis within endothelial cells that are occurring largely independent of identifiable pathological VWF sequence variants. Cumulatively, these novel observations have important clinical implications for the diagnosis and management of patients with mild functional VWF defects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".