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 Release 22.0, Sept. 2008
 
Chapter : ch5. Transfusion Medicine Section : Estimation of Blood Loss and Prediction of Blood Transfusion Needs
  Model of Moore et al for Predicting the Probability of Massive Blood Transfusion in a Trauma Patient

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Copyright (c) 2008-2010, Institute for Algorithmic Medicine, Houston, TX, USA. All rights reserved.

Overview :

Moore et al developed a model for predicting the need for massive blood transfusion in a trauma patient soon after arrival to the trauma center. The authors are from multiple hospitals in the United States and Canada.

 

Parameters:

(1) Injury Severity Score (ISS)

(2) minimum pH during first hour after arrival

(3) mininum systolic blood pressure during first hour after arrival in mm Hg

 

Parameter

Finding

Points

Injury Severity Scale (ISS)

<= 25

0

 

> 25

1

 

X =

= (0.7 * (points for ISS)) - (5.6 * (minimum pH)) - (0.04 * (minimum systolic blood pressure)) + 42.1

 

probability of massive blood transfusion =

= 1 / (1 + EXP((-1) * X))

 

Performance:

• The area under the ROC curve was 0.8.

 

  References:

Moore F, McKinley B, et al. Need for massive transfusion can be predicted early after trauma center arrival (Abstract). J Trauma. 2007; 62: 270.

 

 

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