ArticleAnnals of translational medicine2021
Machine learning models to predict red blood cell transfusion in patients undergoing mitral valve surgery.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in the prediction of intraoperative red blood cell transfusion in cardiac surgery: a systematic review and diagnostic test accuracy meta-analysis.Brazilian journal of anesthesiology (Elsevier)Pooled it
- Unified comparison of machine learning paradigms for blood transfusion prediction in pediatric congenital heart surgery.iScience · 2026Article
- Evaluation of the Factors Influencing Blood Transfusion during Minimally Invasive Direct Coronary Artery Bypass Surgery.Cardiology · 2025Article
- Mapping the landscape of machine learning models used for predicting transfusions in surgical procedures: a scoping review.BMC medical informatics and decision making · 2024Article
- A precise blood transfusion evaluation model for aortic surgery: a single-center retrospective study.Journal of clinical monitoring and computing · 2024Article
- Prediction of intraoperative red blood cell transfusion in valve replacement surgery: machine learning algorithm development based on non-anemic cohort.Frontiers in cardiovascular medicine · 2024Article
- Machine learning in transfusion medicine: A scoping review.Transfusion · 2024Article
- Forecasting demand for blood products: Towards inventory management of a perishable product.Bioinformation · 2024Article
- Multivariable statistical models to predict red cell transfusion in elective surgery.Blood transfusion = Trasfusione del sangue · 2023Article
- Prediction of Red Blood Cell Demand for Pediatric Patients Using a Time-Series Model: A Single-Center Study in China.Frontiers in medicine · 2022Article
- Identification and Validation of the Pyroptosis-Related Molecular Subtypes of Lung Adenocarcinoma by Bioinformatics and Machine Learning.Frontiers in cell and developmental biology · 2021Article
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11 authors.
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Abstract
backgroundRed blood cell (RBC) transfusion therapy has been widely used in surgery, and has yielded excellent treatment outcomes. However, in some instances, the demand for RBC transfusion is assessed by doctors based on their experience. In this study, we use machine learning models to predict the need for RBC transfusion during mitral valve surgery to guide the surgeon's assessment of the patient's need for intraoperative blood transfusion.
methodsWe retrospectively reviewed 698 cases of isolated mitral valve surgery with and without combined tricuspid valve operation. Seventy percent of the database was used as the training set and the remainder as the testing set for 13 machine learning algorithms to build a model to predict the need for intraoperative RBC transfusion. According to the characteristic value of model mining, we analyzed the risk-related factors to determine the main effects of variables influencing the outcome.
resultsA total of 166 patients of the cases considered had undergone intraoperative RBC transfusion (24.52%). Of the 13 machine learning algorithms, CatBoost delivered the best performance, with an AUC of 0.888 (95% CI: 0.845-0.909) in testing set. Further analysis using the CatBoost model revealed that hematocrit (<37.81%), age (>64 y), body weight (<59.92 kg), body mass index (BMI) (<22.56 kg/m
conclusionsMachine learning models can be used to accurately predict the outcomes of RBC transfusion, and should be used to guide surgeons in clinical practice.
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