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Predicting the Need for Blood Transfusions in Cardiac Surgery: A Comparison between Machine Learning Algorithms and Established Risk Scores in the Brazilian Population.
Brazilian Journal of Cardiovascular Surgery ( IF 1.3 ) Pub Date : 2024-03-01 , DOI: 10.21470/1678-9741-2023-0212
Cristiano Berardo Carneiro da Cunha, Tiago Andrade Lima, Diogo Luiz de Magalhães Ferraz, Igor Tiago Correia Silva, Matheus Kennedy Dionisio Santiago, Gabrielle Ribeiro Sena, Verônica Soares Monteiro, Lívia Barbosa Andrade

Blood transfusion is a common practice in cardiac surgery, despite its well-known negative effects. To mitigate blood transfusion-associated risks, identifying patients who are at higher risk of needing this procedure is crucial. Widely used risk scores to predict the need for blood transfusions have yielded unsatisfactory results when validated for the Brazilian population.

中文翻译:

预测心脏手术中的输血需求:机器学习算法与巴西人口既定风险评分之间的比较。

尽管输血有众所周知的负面影响,但它是心脏手术中的常见做法。为了降低与输血相关的风险,识别需要此手术的风险较高的患者至关重要。广泛使用的风险评分来预测是否需要输血,但在巴西人群中进行验证时,结果并不令人满意。
更新日期:2024-03-01
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