A new risk predictive scoring system of vasovagal reactions in patients with preoperative autologous blood donation

被引:1
作者
Jiang, Ying [1 ]
Lin, Jie [1 ]
Ding, Ruiqing [2 ]
Li, Lingling [1 ]
Chi, Hongxu [1 ]
Zhang, Leiying [1 ]
Xia, Xingqiu [3 ]
Yu, Yang [1 ]
Pi, Hongying [4 ]
机构
[1] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Transfus Med Dept, 28 yard Fu Xing Rd, Beijing 100853, Peoples R China
[2] Peking Univ, Minist Educ, Key Lab High Confidence Software Technol, Sch Comp Sci, Beijing, Peoples R China
[3] Beijing HealSci Technol Co Ltd, Beijing, Peoples R China
[4] Chinese Peoples Liberat Army Gen Hosp, Hlth Serv Training Ctr, 28 yard Fu Xing Rd, Beijing 100853, Peoples R China
关键词
Vasovagal response; Preoperative autologous blood donation; Patient blood management; Nomogram; Scoring system; WHOLE-BLOOD; DONORS; FEAR; AGE;
D O I
10.1016/j.transci.2023.103791
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background and objectives: Vasovagal response (VVR) is the most common adverse reaction during blood donation and it is the main element for the safety of the patients with preoperative autologous blood donation (PABD). Accurate identification high-risk group is of great significance for PABD. Our study aimed to establish a scoring system based on the nomogram to screen the high-risk population and provide evidence for preventing the occurrence of VVRs. Materials and methods: A number of 4829 patients underwent PABD between July 2017 and June 2020 in the first medical center of Chinese PLA Hospital were recruited, 3387 of whom were included in the training group (70 %; 108 VVRs patients vs 3279 Non-VVRs patients), 1442 were included in the validation group (30 %; 46 VVRs patients vs 1396 Non-VVRs patients). The data were analyzed by univariate and multivariate logistic regression. The nomogram of the scoring system was created by using the RMS tool in R software. Results: Seven variables including BMI, hematocrit, pre-phlebotomy heart rate and systolic blood pressure, history of blood donation, age group and primary disease were selected to build the nomogram, which was shown as prediction model. And the score was 0-1 for BMI, 0-2 for hematocrit, systolic blood pressure, heart rate and no blood donation history, 0-10 for age, 0-3 for primary disease. When the total cutoff score was 11, the predictive system for identifying VVRs displayed higher diagnostic accuracy. The area under the curve, specificity, and sensitivity of the training group were 0.942, 82.41 % and 97.17 %, respectively, whereas those of the validation group were 0.836, 78.26 % and 78.15 %, respectively.Conclusion: A risk predictive scoring system was successfully developed to identify high-risk VVRs group form PABD patients that performed well.
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页数:6
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