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

Dong Xu Chen, Yi Shun Wang, Min Yan, Lei Du, Qian Li

Abstract read

In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

Toward accurate prediction of pediatric epidemic disease patient volume in the Chaoshan region: A deep learning framework.iScience · 2026
Article

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5 · Who and what money

Authors and funding

5 authors.

Dong Xu ChenDepartment of Anesthesiology, West China Hospital, Sichuan University, No. 37 Wainan Guoxue Road, Chengdu, Sichuan 610041, P.R.China.

Yi Shun WangDepartment of Anesthesiology, West China Hospital, Sichuan University, No. 37 Wainan Guoxue Road, Chengdu, Sichuan 610041, P.R.China.

Min YanDepartment of Anesthesiology, The Second Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang 330100, P.R.China.

Lei DuDepartment of Anesthesiology, West China Hospital, Sichuan University, No. 37 Wainan Guoxue Road, Chengdu, Sichuan 610041, P.R.China.

Qian LiDepartment of Anesthesiology, West China Hospital, Sichuan University, No. 37 Wainan Guoxue Road, Chengdu, Sichuan 610041, P.R.China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BioinformaticsCardiovascular medicineSurgical procedure

Identifiers

PMID37744030

DOI10.1016/j.isci.2023.107798

PMCPMC10514444

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.