[The Causes of Platelet Aggregation in Version 6.4 Trima Accel Automated Blood Collection System and the Comparison of Two Intervention Measures].

Shu-Ming Huang, Xiao-Mei Lin, Hui-Wei Tang, Jia Zeng
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Abstract

Objective: To explore the causes of platelet aggregation in version 6.4 Trima Accel automated blood collection system and the effect of 2 intervention measures.

Methods: The data on platelet aggregation (n=61) and non-aggregation (n=323) of 61 donors in 2020 were collected and the causes of aggregation were analyzed. Then the 72 donors with platelet aggregation in 2021 were randomized into intervention group A (increasing the anticoagulant-to-blood ratio) and intervention group B (wrapping the donor's arm with an electric blanket to keep warm and improve the blood flow speed). The collection time, average blood flow speed, number of machine alarms, anticoagulant usage, deaggregation and citrate reaction of the two groups were compared.

Results: Platelet aggregation was negatively correlated with the average blood flow speed (r =-0.394) and positively correlated with the collection time (r =0.458). The equations for predicting aggregation and non-aggregation were constructed based on Bayesian and Fisher discriminant analysis, and the predicted accuracy was 77.1%. The comparison of the effects of two intervention measures showed that the average blood flow speed in group B was higher than that in group A; the collection time, number of machine alarms, anticoagulant usage and proportion of citrate reaction in blood donors in group B were all lower than those in Group A, all these differences were significant (P < 0.05). In the entire cohort in 2021, 90.28% of the products were immediately deaggregated after collection, and 9.72% of the products were deaggregated within 4 hours. There was no statistically significant difference in deaggregation between the two intervention groups (P >0.05).

Conclusion: During apheresis platelet collection, the predictive equations for aggregation and non-aggregation can be used to predict the occurrence probability of aggregation, and the intervention can be made in advance. Both intervention measures are effective in reducing platelet aggregation, however, measure B has the advantages of improving the speed of blood collection, shortening the collection time, reducing the alarm frequency and the anticoagulant usage, and reducing the incidence of citrate reaction in blood donors.

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[6.4 版 Trima Accel 自动采血系统中血小板聚集的原因及两种干预措施的比较]。
目的探讨 6.4 版 Trima Accel 自动采血系统中血小板聚集的原因以及 2 项干预措施的效果:收集 2020 年 61 名献血者的血小板聚集(n=61)和不聚集(n=323)数据,分析聚集原因。然后将 2021 年出现血小板聚集的 72 名捐献者随机分为干预组 A(提高抗凝剂与血液的比例)和干预组 B(用电热毯包裹捐献者手臂,以保暖并提高血流速度)。对两组的采集时间、平均血流速度、机器报警次数、抗凝剂用量、脱凝和枸橼酸盐反应进行了比较:结果:血小板聚集与平均血流速度呈负相关(r =-0.394),与采集时间呈正相关(r =0.458)。基于贝叶斯和费雪判别分析构建了预测聚集和不聚集的方程,预测准确率为 77.1%。两种干预措施的效果比较显示,B 组的平均血流速度高于 A 组;B 组献血者的采血时间、机器报警次数、抗凝剂使用量和枸橼酸盐反应比例均低于 A 组,差异均有学意义(P<0.05)。在 2021 年的整个队列中,90.28%的产品在采集后立即进行了血凝分离,9.72%的产品在 4 小时内进行了血凝分离。两个干预组之间的去聚集率差异无统计学意义(P >0.05):结论:在无细胞疗法血小板采集过程中,可利用聚集和非聚集预测方程预测聚集发生的概率,并提前进行干预。两种干预措施都能有效降低血小板聚集,但 B 措施具有提高采血速度、缩短采血时间、减少报警频率和抗凝剂使用量、降低献血者枸橼酸盐反应发生率等优点。
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中国实验血液学杂志
中国实验血液学杂志 Medicine-Medicine (all)
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7331
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