He Yiwen, Feng Huihui, Yu Lu, Deng Gang
Department of Blood Transfusion, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang 315010 China.
Institute of Blood Transfusion, Ningbo Blood Center, Ningbo, 315010 China.
Indian J Hematol Blood Transfus. 2025 Jul;41(3):656-664. doi: 10.1007/s12288-024-01857-0. Epub 2024 Sep 11.
This study aims to explore the factors that affect the efficacy of apheresis platelet transfusion in patients with hematologic diseases and construct a nomogram prediction model to predict the possibility of obtaining satisfactory platelet transfusion efficacy and guide scientific and rational platelet transfusion. The basic information of 2,007 hematologic patients who received apheresis platelet transfusions from June 2022 to April 2023 and the corresponding donor information and apheresis platelet data are collected. The risk factors that cause ineffective platelet transfusions are screened through a logistic regression analysis. Then, the risk factors are introduced into R software, and a nomogram prediction model is established and validated. The regression analysis shows that the independent risk factors for ineffective platelet transfusion are platelet count before transfusion, white blood cell count, hemoglobin content and mean corpuscular hemoglobin, cumulative platelet transfusion times, platelet antibody positivity, fever, splenomegaly, graft-versus-host disease, bleeding, and platelet storage days. These factors are included in the nomogram, and the calibration curve for predicting transfusion efficiency reveals good consistency between the nomogram-predicted results and the actual observations. The area under the curve obtained through internal repeated sampling is 0.756. This study comprehensively assessed the risks associated with factors leading to ineffective platelet transfusion and successfully constructed and validated a nomogram prediction model. This model provides an important predictive tool for assessing the efficacy of platelet transfusion in patients with hematologic diseases, with the potential to guide scientific and rational platelet transfusion practices.
The online version contains supplementary material available at 10.1007/s12288-024-01857-0.
本研究旨在探讨影响血液系统疾病患者单采血小板输注疗效的因素，并构建列线图预测模型，以预测获得满意血小板输注疗效的可能性，指导科学合理的血小板输注。收集了2007例在2022年6月至2023年4月接受单采血小板输注的血液系统疾病患者的基本信息、相应的供者信息及单采血小板数据。通过逻辑回归分析筛选出导致血小板输注无效的危险因素。然后，将这些危险因素引入R软件，建立并验证列线图预测模型。回归分析显示，血小板输注无效的独立危险因素为输血前血小板计数、白细胞计数、血红蛋白含量及平均红细胞血红蛋白含量、累计血小板输注次数、血小板抗体阳性、发热、脾肿大、移植物抗宿主病、出血及血小板储存天数。这些因素被纳入列线图，预测输血效率的校准曲线显示列线图预测结果与实际观察结果具有良好的一致性。通过内部重复抽样获得的曲线下面积为0.756。本研究全面评估了导致血小板输注无效的因素相关风险，并成功构建和验证了列线图预测模型。该模型为评估血液系统疾病患者血小板输注疗效提供了重要的预测工具，有可能指导科学合理的血小板输注实践。
在线版本包含可在10.1007/s12288-024-01857-0获取的补充材料。
