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Blood Transfusion

Blood Transfusion

Blood transfusion is a critical medical procedure that saves lives and treats various medical conditions. It involves transferring blood from a donor to a recipient. This process requires a thorough understanding of the ABO blood group system and its associated antigens and antibodies.
Blood Transfusion Overview
A blood transfusion is a medical procedure used to replace blood lost due to injury, surgery, or to treat conditions such as anemia or cancer. During a transfusion, donor blood is...

Blood Transfusion and Agglutination

Blood Transfusion and Agglutination

Blood transfusion is a therapeutic measure to restore the blood volume after extensive blood loss due to an accident or a medical procedure. Blood transfusion involves drawing a certain amount of blood from a suitable donor and infusing it into the recipient.
History
The history of blood transfusion dates back to the 17th century, when early attempts were made in animals. In 1818 James Blundell, a British doctor, performed the first successful human blood transfusion. Later in 1900, Karl...

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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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Data Driven Methods for Predicting Blood Transfusion Needs in Elective Surgery.

Dieter Hayn¹, Karl Kreiner¹, Peter Kastner¹

¹AIT Austrian Institute of Technology GmbH, Austria.

Studies in Health Technology and Informatics

|May 4, 2016

Summary

This summary is machine-generated.

Predicting patient blood transfusion needs can be improved by using individual pre-surgical data. This approach supports Patient Blood Management (PBM) to reduce costs and enhance patient outcomes.

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Area of Science:

Transfusion Medicine
Healthcare Management

Background:

Traditional focus on Donor Blood Management.
Growing interest in recipient-focused Patient Blood Management (PBM).
PBM aims to reduce transfusion rates but has room for individual optimization.

Purpose of the Study:

Investigate predicting blood transfusion needs using existing datasets.
Enhance individual patient transfusion prediction.
Identify key predictors of transfusion practice.

Main Methods:

Utilized datasets from two previous studies.
Employed predictive modeling incorporating pre-surgical parameters.
Analyzed data across various treatment phases.

Main Results:

Prediction of blood transfusion needs can be significantly improved.
Individual pre-surgical parameters are key predictors.
Identified main factors influencing transfusion decisions.

Conclusions:

Predictive modeling offers a valuable tool for Patient Blood Management.
Potential to reduce healthcare costs and improve patient outcomes.
Further validation in prospective datasets is recommended.