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Updated: May 5, 2026
Platelet Adhesion and Aggregation Under Flow using Microfluidic Flow Cells
Published on: October 27, 2009
[The Causes of Platelet Aggregation in Version 6.4 Trima Accel Automated Blood Collection System and the Comparison
Shu-Ming Huang1, Xiao-Mei Lin1, Hui-Wei Tang1
1Fujian Blood Center, Fuzhou 350004, Fujian Province,China.
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.
