Optimizing Buffy Coat Pooling: Enhancing Platelet Yield Through Platelet Count-Based Sorting.

Area of Science:

• Transfusion Medicine
• Hematology
• Biotechnology

Background:

• Optimizing platelet yield in pooled buffy coat (BC)-derived platelet products is crucial for efficient blood banking.
• Variability in donor whole blood (WB) platelet counts affects the consistency of platelet concentrate yields.
• Preselection algorithms can potentially improve the standardization of platelet production.

Purpose of the Study:

• To evaluate the efficacy of sorting buffy coats (BCs) based on donor whole blood (WB) platelet counts.
• To compare the yield and divisibility of platelet concentrates produced by random BC pooling versus algorithm-sorted BC pooling.
• To assess the impact of an in-house preselection algorithm on the production of pathogen-inactivated double-dose platelet concentrates.

Main Methods:

• Two BC pooling strategies were compared: random assignment and sorting based on WB platelet counts using a preselection algorithm.
• Donor WB platelet counts were measured using a hematology analyzer prior to pooling.
• Yield and divisibility rates of pathogen-inactivated double-dose platelet concentrates were analyzed using the Wilcoxon Rank-Sum Test.

Main Results:

• Sorting BCs by WB platelet count significantly increased median platelet concentrations (1247 to 1307 ×10³/µL, P = .0434).
• Yields per platelet unit significantly increased from 4.6 to 4.8 ×10¹¹/unit (P = .0191).
• The proportion of divisible pathogen-inactivated platelet units increased from 72.1% to 89.5%.

Conclusions:

• Employing an in-house preselection algorithm for sorting BCs based on WB platelet counts enhances platelet concentrate yields.
• This sorting method leads to more standardized platelet products with improved divisibility rates.
• The algorithm-based approach is effective for producing high-quality, double-dose platelet concentrates.