Type 1 VWD classification revisited: novel insights from combined analysis of the LoVIC and WiN studies
Bibliographic record
Abstract
ABSTRACT: There is significant ongoing debate regarding type 1 von Willebrand disease (VWD) defintion. Previous guidelines recommended patients with von Willebrand factor (VWF) levels <30 IU/dL be diagnosed type 1 VWD, whereas patients with significant bleeding and VWF levels from 30 to 50 IU/dL be diagnosed with low VWF. To elucidate the relationship between type 1 VWD and low VWF in the context of age-induced increases in VWF levels, we combined data sets from 2 national cohort studies: 162 patients with low VWF from the Low VWF in Ireland Cohort (LoVIC) and 403 patients with type 1 VWD from the Willebrand in The Netherlands (WiN) studies. In 47% of type 1 VWD participants, VWF levels remained <30 IU/dL despite increasing age. Conversely, VWF levels increased to the low VWF range (30-50 IU/dL) in 30% and normalized (>50 IU/dL) in 23% of type 1 VWD cases. Crucially, absolute VWF antigen (VWF:Ag) levels and increase of VWF:Ag per year overlapped between low VWF and normalized type 1 VWD participants. Moreover, multiple regression analysis demonstrated that VWF:Ag levels in low VWF and normalized type 1 VWD patients would not have been different had they been diagnosed at the same age (β = 0.00; 95% confidence interval, -0.03 to 0.04). Consistently, no difference was found in the prevalence of VWF sequence variants; factor VIII activity/VWF:Ag or VWF propeptide/VWF:Ag ratios; or desmopressin responses between low VWF and normalized type 1 VWD patients. In conclusion, our findings demonstrate that low VWF does not constitute a discrete clinical or pathological entity. Rather, it is part of an age-dependent type 1 VWD evolving phenotype. Collectively, these data have important implications for future VWD classification criteria.
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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 | 0.029 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".