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Record W2171200151 · doi:10.1111/hae.12254

Desmopressin (<scp>DDAVP</scp>) in the management of patients with congenital bleeding disorders

2013· review· en· W2171200151 on OpenAlexaff
Cindy Leissinger, Manuel Carção, Joan Cox Gill, Janna M. Journeycake, Tammuella Singleton, Leonard A. Valentino

Bibliographic record

VenueHaemophilia · 2013
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsDesmopressinMedicineVon Willebrand diseaseAntidiureticIntensive care medicineHemostasisVasopressinHaemophiliaVon Willebrand factorTranexamic acidPediatricsSurgeryPlateletInternal medicineBlood loss

Abstract

fetched live from OpenAlex

Bleeding disorders, including haemophilia, von Willebrand disease, and platelet function abnormalities pose a substantial, ongoing management challenge. Patients with these disorders not only require treatment during bleeding events but also need effective management strategies to prepare for events ranging from minor dental procedures to major surgery and childbirth. Moreover, women with bleeding disorders often require ongoing treatment to prevent menorrhagia during childbearing years. Desmopressin (DDAVP), a synthetic derivative of the antidiuretic hormone l-arginine vasopressin, has become a well-established tool for the management of patients with bleeding disorders in a variety of clinical settings. However, despite the widespread use of DDAVP, the available clinical evidence on its efficacy and safety in these settings is limited, and there has not been a recent comprehensive review of its role in the clinical management of patients with bleeding disorders. As such, this article provides a review of the mechanism of action and pharmacokinetic properties of DDAVP, followed by a concise summary of the available evidence for its use in the treatment and prevention of bleeding.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.281
Teacher spread0.255 · 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 teacher head, not a consensus.

Study designOther design
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

Citations86
Published2013
Admission routes1
Has abstractyes

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