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[Study on the Influencing Factors of Donation Related Vasovagal Reaction Based on Association Rule Analysis]
Li-Ning Meng1, Qi Yang1, Long Tian1
1Zhangjiakou Central Blood Station, Zhangjiakou 075000, Hebei Province, China.
Objective:
To evaluate the clinical value of association rule analysis for influencing factors of donation related vasovagal reaction (DRVR), using Logistic regression analysis as the reference.
Methods:
A retrospective study was conducted on 10 000 unpaid blood donors from Zhangjiakou Central Blood Station from June 2019 to June 2021. Their baseline data was collected. Blood donors were divided into the test group with DRVR (n=386) and the control group without DRVR (n=9614). Logistic regression analysis was performed on all blood donors. The independent risk factor prediction was established for DRVR. Association rule analysis was performed on the test group. The effective strong association rules including DRVR were calculated. Taking Logistic regression analysis prediction as the reference, the results of association rule analysis were evaluated.
Results:
The logistic regression analysis prediction showed that "age (20-29 years old)", "gender (female)", "BMI (≤18 kg/m2)", "blood pressure (low)", and "hemoglobin level (low)" were the independent risk factors for DRVR (all P < 0.05). There were 8 effective strong association rules including DRVR in total: The two-item rules were "age (20-29 years old), DRVR", "gender (female), DRVR", "BMI (≤18 kg/m2), DRVR", "blood pressure (low), DRVR", "hemoglobin level (low), DRVR". The three-item rules were "age (20-29 years old), gender (female), DRVR", "BMI (≤18 kg/m2), blood pressure (low), DRVR", "BMI (≤18 kg/m2), blood donation volume (400 mL), and DRVR". The results of the two rules in association rule analysis included all independent risk factors leading to DRVR and similar incidence rate change of DRVR. The results of the three rules had determined the range of high-risk groups for DRVR.
Conclusion:
Compared to the Logistic regressive analysis, the results of association rule analysis have more clinical value, which provide a method reference for further improving the accuracy of DRVR prediction.
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