Special considerations in GI bleeding in VWD patients
Bibliographic record
Abstract
Gastrointestinal (GI) bleeding is an important cause of morbidity and mortality in von Willebrand disease (VWD). It has been noted that GI bleeding caused by angiodysplasia is overrepresented in VWD patients compared to other causes. The bleeding from angiodysplasia is notoriously difficult to treat; recurrences and rebleeds are common. A growing body of basic science evidence demonstrates that von Willebrand factor negatively regulates angiogenesis through multiple pathways. VWD is clinically highly associated with angiodysplasia. The predisposition to angiodysplasia likely accounts for many of the clinical difficulties related to managing GI bleeding in VWD patients. Diagnosis and treatment are challenging with the current tools available, and much further research is needed to further optimize care for these patients with regard to acute treatment, prophylaxis, and adjunctive therapies. In this review we provide an overview of the available literature on GI bleeding in VWD and explore the molecular underpinnings of angiodysplasia-related GI bleeding. Considerations for diagnostic effectiveness are discussed, as well as the natural history and recurrence of these lesions and which therapeutic options are available for acute and prophylactic management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".