Related Experiment Video
Updated: Jul 15, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
A model based on electronic health records to predict transfusion events in on-pump cardiac surgery
Dong Xu Chen1,2, Yi Shun Wang1,2, Min Yan3
1Department of Anesthesiology, West China Hospital, Sichuan University, No. 37 Wainan Guoxue Road, Chengdu, Sichuan 610041, P.R.China.
Abstract:
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.
More Related Videos
09:54A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats
Published on: March 23, 2018
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018