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Record W2724904788 · doi:10.1182/blood.v128.22.875.875

Characterization of Bleeding in Hemophilia Carriers and Comparison to Women with Type 1 Von Willebrand Disease, Type 3 Von Willebrand Disease Obligate Carriers and Controls

2016· article· en· W2724904788 on OpenAlexaffabout
Natasha Satkunam, Johnny Mahlangu, Christoph Bidlingmaier, María Eva Mingot‐Castellano, Meera Chitlur, Patrick Fogarty, Adam Cuker, Maria Elisa Mancuso, Pål André Holme, Julie Grabell, Wilma M. Hopman, Prasad Mathew, Paula James

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineVon Willebrand diseaseHemarthrosisVon Willebrand factorPediatricsCarrier testingInternal medicineSurgeryPrenatal diagnosisPregnancyPlatelet

Abstract

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Abstract Background: Hemophilia carriers report abnormal bleeding, even when factor VIII or IX levels are normal. Information comparing bleeding events between carriers and women with other inherited bleeding disorders is lacking. Purpose: The purpose of our study was to characterize bleeding in hemophilia carriers using the International Society on Thrombosis and Hemostasis Bleeding Assessment Tool (ISTH-BAT) and to compare it with bleeding in normal controls, women with Type 1 VWD and Type 3 VWD obligate carriers (OC). Method: This was a prospective, observational, cross-sectional study performed by members of GEHEP (Global Emerging HEmostasis Panel). Study participants were recruited from GEHEP members' clinics in North America (Kingston, Canada, Detroit and Philadelphia, USA), Europe (Malaga, Spain; Milan, Italy; Munich, Germany; Oslo, Norway) and South Africa (Johannesburg). Potential participants were identified through local patient databases and approached during clinic visits. All participants signed informed consent. Hemophilia carriers were defined by a documented FVIII or FIX mutation and/or by an appropriate family history (daughter of a man with hemophilia or mother of two sons with hemophilia or mother of one son with hemophilia with at least one other affected male relative). Demographic information was collected using a CRF and the ISTH-BAT was completed for each participant by study personnel. Existing ISTH-BAT data for women with Type 1 VWD, Type 3 VWD OC and age-matched female controls were used for comparison. Results: A total of 329 participants were included in this study; 168 hemophilia carriers, 83 women with Type 1 VWD, 32 Type 3 VWD OC and 46 female normal controls. Hemophilia carriers and normal controls were similar in age (40.1 vs 41.6, p=0.445). The mean overall ISTH-BAT bleeding score (BS) was significantly higher in carriers than in controls (5.7 vs 2.48, p<0.0001). Carriers reported significantly more bleeding in the categories of cutaneous, minor wounds, oral cavity bleeding, post-dental bleeding, surgical bleeding, menorrhagia, post-partum bleeding and other when compared with controls. Carriers were older than Type 1 VWD patients (40.1 vs 36.4 years, p=0.042). While women with Type 1 VWD had higher total ISTH-BAT BS (8.7 vs 5.7, p<0.0001) as well as higher scores for epistaxis, cutaneous bleeding, minor wounds, oral cavity bleeding and menorrhagia, hemophilia carriers had significantly higher scores for muscle hematomas and hemarthrosis. Carriers were younger than Type 3 VWD OC (40.1 vs 45.2 years, p = 0.02), had higher overall ISTH-BAT BS (5.7 vs 3.0, p=0.009) and reported more bleeding in the following categories: total score, epistaxis, hematuria, dental, muscle hematomas, hemarthrosis, and other. In fact, hemophilia carriers reported more musculoskeletal bleeding than all other groups. Importantly, given the concern about over-reporting of joint bleeds by hemophilia carriers because of familiarity with hemarthrosis in affected male relatives, no Type 3 VWD OC reported joint bleeds. See Table 1 for detailed results. Conclusion: In summary, our study showed that hemophilia carriers report significantly more bleeding by overall ISTH-BAT BS than age-matched female controls. Carriers experience both mucocutaneous bleeding as well as musculoskeletal bleeding. They score higher for mucocutaneous bleeding when compared with controls and when compared with Type 3 VWD OC. Overall Type 1 VWD patients experience more severe mucocutaneous bleeding than hemophilia carriers. However, hemophilia carriers report more musculoskeletal bleeding in the form of hemarthrosis and hematomas than all other groups. A comparison of overall ISTH-BAT BS between groups shows that bleeding in women with Type 1 VWD > hemophilia carriers > Type 3 VWD OC > controls. Additional research into the underlying pathophysiology of this abnormal bleeding is a critical next step in understanding and determining how to appropriately manage these patients. Disclosures Bidlingmaier: Novo Nordisk: Honoraria; Sobi: Honoraria; Pfizer: Honoraria; Biotest: Honoraria; Baxalta: Honoraria; Bayer: Honoraria; CSL Behring: Honoraria, Research Funding. Mingot-Castellano:Amgen: Consultancy; Pfizer: Consultancy; Novo Nordisk: Consultancy, Research Funding; Baxalta: Consultancy, Research Funding; Novartis: Consultancy; Bayer: Consultancy, Research Funding. Chitlur:Novo Nordisk: Consultancy; Baxalta: Honoraria; Bayer: Honoraria; Biogen-Idec: Honoraria; Pfizer: Honoraria. Fogarty:Bayer Healthcare: Membership on an entity's Board of Directors or advisory committees, Research Funding; Baxter/Baxalta: Membership on an entity's Board of Directors or advisory committees, Research Funding; Biogen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Membership on an entity's Board of Directors or advisory committees; CSL Behring: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novo Nordisk: Membership on an entity's Board of Directors or advisory committees; Pfizer: Employment, Membership on an entity's Board of Directors or advisory committees, Research Funding; Spark Therapeutics: Research Funding. Cuker:T2 Biosystems: Research Funding; Genzyme: Consultancy; Biogen-Idec: Consultancy, Research Funding; Amgen: Consultancy; Stago: Consultancy. Mancuso:Bayer Healthcare: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Baxalta: Consultancy, Speakers Bureau; CSL Behring: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novo Nordisk: Consultancy, Speakers Bureau; Sobi/Biogen Idec: Consultancy, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kedrion: Consultancy. Holme:Baxalta, now part of Shire: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Investigator Clinical Studies. Mathew:Bayer: Employment. James:CSL Behring: Research Funding; Octapharma: Research Funding; Biogen: Consultancy; Basalt: Consultancy; Bayer: Research Funding.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.259
Teacher spread0.247 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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