Hybrid emergency rooms reduce the requirement of blood transfusion in patients with severe trauma
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1749-7922
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Hybrid emergency rooms reduce the requirement of blood transfusion in patients with severe trauma ; volume:16 ; number:1 ; day:26 ; month:6 ; year:2021 ; pages:1-9 ; date:12.2021
World journal of emergency surgery ; 16, Heft 1 (26.6.2021), 1-9, 12.2021
- Creator
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Watanabe, Hiroaki
Matsumoto, Ryo
Kuramoto, Shunsuke
Muronoi, Tomohiro
Oka, Kazuyuki
Shimojo, Yoshihide
Kidani, Akihiko
Hira, Eiji
Kawamura, Toshihiko
- Contributor
-
SpringerLink (Online service)
- DOI
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10.1186/s13017-021-00377-w
- URN
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urn:nbn:de:101:1-2021101010311210205247
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:31 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Watanabe, Hiroaki
- Matsumoto, Ryo
- Kuramoto, Shunsuke
- Muronoi, Tomohiro
- Oka, Kazuyuki
- Shimojo, Yoshihide
- Kidani, Akihiko
- Hira, Eiji
- Kawamura, Toshihiko
- SpringerLink (Online service)
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Survey on worldwide trauma team activation requirement
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FIBTEM provides early prediction of massive transfusion in trauma
Impact of platelet transfusion on outcomes in trauma patients
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Platelet Transfusion for Trauma Resuscitation
Predicting on-going hemorrhage and transfusion requirement after severe trauma: a validation of six scoring systems and algorithms on the TraumaRegister DGU®
Survey on worldwide trauma team activation requirement
Survey on worldwide trauma-team activation requirement
Blood transfusion and coagulopathy in geriatric trauma patients
User-Centered Design to Reduce Inappropriate Blood Transfusion Orders
The Shock Index revisited – a fast guide to transfusion requirement? A retrospective analysis on 21,853 patients derived from the TraumaRegister DGU®
Nano fuzzy alarming system for blood transfusion requirement detection in cancer using deep learning
FIBTEM provides early prediction of massive transfusion in trauma
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