Analysis of Factors Related to Vasovagal Response in Apheresis Blood Donors and the Establishment of Prediction Model Based on BP Neural Network Algorithm  

作　　者：Xin Hu Hua Xu Fengqin Li 

机构地区：[1]Xi'an Central Blood Station,Shaanxi Blood Center,Xi'an 710000,China

出　　处：《Journal of Clinical and Nursing Research》2024年第6期276-283,共8页临床护理研究（英文）

基　　金：Xi'an Municipal Bureau of Science and Technology,Science and Technology Program,Medical Research Project。

摘　　要：Objective:To analyze the factors related to vessel vasovagal reaction(VVR)in apheresis donors,establish a mathematical model for predicting the correlation factors and occurrence risk,and use the prediction model to intervene in high-risk VVR blood donors,improve the blood donation experience,and retain blood donors.Methods:A total of 316 blood donors from the Xi'an Central Blood Bank from June to September 2022 were selected to statistically analyze VVR-related factors.A BP neural network prediction model is established with relevant factors as input and DRVR risk as output.Results:First-time blood donors had a high risk of VVR,female risk was high,and sex difference was significant(P value<0.05).The blood pressure before donation and intergroup differences were also significant(P value<0.05).After training,the established BP neural network model has a minimum RMS error of o.116,a correlation coefficient R=0.75,and a test model accuracy of 66.7%.Conclusion:First-time blood donors,women,and relatively low blood pressure are all high-risk groups for VVR.The BP neural network prediction model established in this paper has certain prediction accuracy and can be used as a means to evaluate the risk degree of clinical blood donors.

关 键 词：Vasovagal response Related factors Prediction BP neural network 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]