Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Thrombosi...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Thrombosis and Haemostasis
Article . 2013 . Peer-reviewed
License: Elsevier Non-Commercial
Data sources: Crossref
versions View all 2 versions
addClaim

Bleeders, bleeding rates, and bleeding score

Authors: A, Tosetto; G, Castaman; F, Rodeghiero;

Bleeders, bleeding rates, and bleeding score

Abstract

Bleeding symptoms are frequently reported even in otherwise healthy subjects, and differentiating a normal subject from a patient with a mild bleeding disorder (MBD) can be extremely challenging. The concept of bleeding rate, that is, the number of bleeding episodes occurring within a definite time, could be used as the unifying framework reconciling the bleeding risk observed in congenital and acquired coagulopathies into a single picture. For instance, primary prevention trials have shown that the incidence of non-major bleeding symptoms in normal subjects is around five per 100 person-years, and this figure is in accordance with the number of hemorrhagic symptoms reported by normal controls in observational studies on hemorrhagic disorders. The incidence of non-major bleeding in patients with MBDs (e.g. in patients with type 1 VWD carrying the C1130F mutation) is also strikingly similar with that of patients taking antiplatelet drugs, and the incidence in moderately severe bleeding disorders (e.g. type 2 VWD) parallels that of patients taking vitamin K antagonists. The severity of a bleeding disorder may therefore be explained by a bleeding rate model, which also explains several common clinical observations. Appreciation of the bleeding rate of congenital and acquired conditions and of its environmental/genetic modifiers into a single framework will possibly allow the development of better prediction tools in the coming years and represents a major scientific effort to be pursued.

Keywords

Phenotype, Humans, Hemorrhage, Blood Coagulation Disorders

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    63
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
63
Top 10%
Top 10%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!