Predictive Models and Algorithms for the Need of Transfusion Including Massive Transfusion in Severely Injured Patients
about
Clinical presentation and blood gas analysis of multiple trauma patients for prediction of standard coagulation parameters at emergency department arrival.[Trauma bay haemoglobin level. Predictor of coagulation disorder in major trauma].Let technology do the work: Improving prediction of massive transfusion with the aid of a smartphone application.Defining when to initiate massive transfusion: a validation study of individual massive transfusion triggers in PROMMTT patients.Trauma-induced coagulopathy: impact of the early coagulation support protocol on blood product consumption, mortality and costs.Patient Blood Management: Clinical Hemotherapy and Hemostasis Management in Perioperative Settings.The Massive Transfusion Score as a decision aid for resuscitation: Learning when to turn the massive transfusion protocol on and offDevelopment and validation of a prehospital prediction model for acute traumatic coagulopathy.Albumin and fibrinogen levels' relation with orthopedics traumatic patients' outcome after massive transfusion.Recursive partitioning identifies greater than 4 U of packed red blood cells per hour as an improved massive transfusion definition.Protocols for massive blood transfusion: when and why, and potential complications.Algorithm for activation of coagulation support treatment in multiple injured patients--cohort study.External Validation of a Smartphone App Model to Predict the Need for Massive Transfusion Using Five Different Definitions.The coagulopathy of trauma.
P2860
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P2860
Predictive Models and Algorithms for the Need of Transfusion Including Massive Transfusion in Severely Injured Patients
description
2012 nî lūn-bûn
@nan
2012年の論文
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2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
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2012年論文
@zh-tw
2012年论文
@wuu
2012年论文
@zh
2012年论文
@zh-cn
name
Predictive Models and Algorith ...... n in Severely Injured Patients
@en
type
label
Predictive Models and Algorith ...... n in Severely Injured Patients
@en
prefLabel
Predictive Models and Algorith ...... n in Severely Injured Patients
@en
P2093
P2860
P356
P1476
Predictive Models and Algorith ...... n in Severely Injured Patients
@en
P2093
Christian Probst
Herbert Schoechl
Klaus Görlinger
Marc Maegele
Philip Spinella
Thomas Brockamp
Ulrike Nienaber
P2860
P356
10.1159/000337243
P577
2012-03-08T00:00:00Z