A model based on electronic health records to predict transfusion events in on-pump cardiac surgery

Abstract

Summary: Perioperative blood transfusion is costly and raises safety concerns. We developed and validated a model for predicting minor, moderate, or major transfusion given to patients during on-pump cardiac procedures based on two centers’ database. Model performance incorporating 7 variables on the development set had an AUC of 0.803 [95% CI, 0.790–0.815] for minor transfusion; moderate transfusion, giving an AUC of 0.822 (95% CI, 0.803–0.841); and major transfusion, giving an AUC of 0.813 (95% CI, 0.759–0.866). Model performance on the validation set had an AUC of 0.739 (95% CI 0.714–0.765), 0.730 (95% CI 0.702–0.758), and 0.713 (95% CI 0.677–0.749), respectively. A model based entirely on readily available electronic health records can accurately predict intraoperative minor, moderate, or major transfusion and provide individualized transfusion risk profiles before surgery among those on-pump cardiac surgical patients, and may help guide patient management.

Keywords

• Cardiovascular medicine
• Surgical procedure
• Bioinformatics