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Record W2068531455 · doi:10.1182/blood-2012-10-462085

Alloantibodies in von Willebrand disease

2013· review· en· W2068531455 on OpenAlexafffund
Paula D. James, David Lillicrap, Pier Mannuccio Mannucci

Bibliographic record

VenueBlood · 2013
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsVon Willebrand diseaseVon Willebrand factorMedicineComplicationImmunologyCoagulopathyDiseaseInternal medicinePlatelet

Abstract

fetched live from OpenAlex

The development of alloantibodies against von Willebrand factor (VWF) represents a rare but serious complication of treatment of von Willebrand disease (VWD), occurring in ~5% to 10% of type 3 VWD patients. Affected patients can present with a range of symptoms, including lack or loss of hemostatic response to infused VWF concentrates up to anaphylactic reactions in rare cases. It is classically reported in multitransfused patients and occurs most frequently in patients with partial or complete VWF gene deletions. A positive family history of anti-VWF antibodies also appears to be a risk factor. There is a lack of standardization of laboratory methods for antibody identification and characterization. Issues of variability in laboratory approaches as well as the rarity of the complication act as a barrier to future studies. Recombinant factor VIII as well as bypassing agents and immune tolerance have been reported as effective treatments; however, aside from case reports, little exists in the literature to guide management. The imminent clinical availability of recombinant VWF has prompted a resurgence of interest in this area. Additional study is warranted to address the deficiencies in our understanding of this treatment complication.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.030
GPT teacher head0.314
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations118
Published2013
Admission routes2
Has abstractyes

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