Cardiothoracic & vascular anesthesia
A precise blood transfusion evaluation model for aortic surgery: a single-center retrospective study
Authors' conclusion
The novel intraoperative blood transfusion prediction model for cardiac aorta surgery in this study effectively assists clinicians in accurately calculating blood transfusion volumes and achieving effective utilization of blood resources.
Study context
- Population
- Patients who received aortic surgery in Beijing Anzhen Hospital between January 2018 and September 20224,285 analysed retrospectively
- Participants
- 3,654 patients
- Exposure
- 13 mainstream machine learning models for predicting intraoperative RBC transfusion volume
- Training setn = 2,557
- Testing setn = 1,097
- Outcome
- Prediction of intraoperative RBC transfusion volume
Methodological detailssingle-centre, machine learning prediction model
- Single-centre
- Machine learning prediction model
Main finding
As reported in the abstract
Mean absolute error, best-performing extremely randomized forest model
1.17 U
R2, extremely randomized forest model
0.50
Observational data: associations, not effects.
Further findings
Most significant risk factors for intraoperative transfusion
- Six most significant risk factors: erythrocytes, estimated operation duration, body weight, sex, red blood cell count, D-dimer
Original publication
A precise blood transfusion evaluation model for aortic surgery: a single-center retrospective study. J Clin Monit Comput. Published 27 December 2023. doi:10.
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