ORIGINAL RESEARCH article
Front. Med.
Sec. Hematology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1566325
Development and evaluation of a dynamic nomogram model for intraoperative blood transfusion decision-making
Provisionally accepted
- 1Sichuan Tianfu New Area People's Hospital, Chengdu, China
- 2West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
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Objective: Develop a dynamic nomogram model to predict intraoperative transfusion probability for precise blood management. Methods: Retrospective analysis of 1410 surgical patients (705 transfused vs 705 controls) from 2019-2023. Lasso and logistic regression identified key predictors using 80% training data. Results: Independent predictors included ASAs III (OR=3.009), grade IV surgery (OR=3.772), EBL (OR=1.003), preHGB (OR=0.932), LVEF (OR=1.063), Temp (OR=57.14), preAPTT (OR=1.147), and preDD (OR=1.127). The model showed excellent discrimination (AUC: 0.983 training, 0.995 testing) and calibration. Optimal threshold: 0.515 probability (sensitivity 0.939, specificity 0.964). Conclusion: This dynamic nomogram enables real-time transfusion risk assessment, aiding clinical decisions and resource optimization.
Keywords: Blood transfusion decision-making, Nomogram modeling, LASSO regression, Peroperative, transfusion
Received: 24 Jan 2025; Accepted: 28 May 2025.
Copyright: © 2025 Li, Jiang, Lin, Du, Shan and Qin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Min Li, Sichuan Tianfu New Area People's Hospital, Chengdu, China
Li Qin, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
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