(P-CB-5) Apheresis Platform May Influence Platelet Quality and Function in Day 0 Fresh Platelet Units: The Role of Lactate Level - Insights from the Chilled Platelet Study in Vitro (CHIPSiv)

Background/Case Studies: Lactate (Lac) accumulation is a marker of metabolic stress and may impair platelet (PLT) function. Differences between apheresis platforms could also contribute to variability in PLT quality. Although baseline Lac differences between platforms were not anticipated on Day 0, variability in Lac may explain differences in PLT functionality. The in vitro arm of the Chilled Platelet Study (CHIPSiv) assesses PLT quality across collecting methods. In this analysis, we evaluated the relationship between Lac levels, apheresis platform, and PLT function in freshly collected units.

Study

Design/Methods: Thirty-two platelet-rich plasma (PRP) samples were collected from two apheresis platforms: Amicus (AP, n = 19) and Trima (TP, n = 13). Lac concentrations and PLT function assays were measured on Day 0. Statistical analyses included Spearman correlation and multiple linear regression models, with and without interaction terms between lactate and platform. Lactate was analyzed both as a continuous variable and as a categorical variable (high ≥2 mmol/L vs. low < 2 mmol/L). Platform, age, and sex were included as covariates to identify the most predictive models.

Results/Findings: Lac levels were significantly higher in AP compared to TP PLT products (Figure 1; mean ± SD: 2.96 ± 2.01 vs. 1.38 ± 0.43 mmol/L; p = 0.001). Lac showed strong negative correlations with PLT aggregation: (ADP-Max A: r = –0.64, E-Max A: r = –0.55, AE-Max A: r = –0.55). and with markers of clot/thrombin initiation (Extem-CT: r ≈ –0.59, Fibtem-CT: r ≈ –0.47, CAT lag time: r = –0.67); all correlations were statistically significant, suggesting Lac impairs both aggregation and clot formation.

In this study, two regression models were used to identify predictors of ADP-Max A. In Model 1, which included Lac group, platform, age, and sex, Lac group (p = 0.042) and platform (p = 0.018) were independent predictors of ADP-Max A, while age and sex were not significant (R = 0.587; df = 27). Compared to other tested models, it had lowest Akaike Information Criterion (AIC = 18.64) and Bayesian Information Criterion (BIC = 25.97), favoring simplicity and interpretability.

In Model 2, with an interaction term (platform × Lac group), Lac group was the only significant predictor (p = 0.008).

When stratified by platform, AP PLTs were more sensitive to elevated Lac levels, with ADP-Max A significantly reduced in the high Lac group. In contrast, TP PLTs showed no significant differences between Lac groups.

Conclusions: At Day 0, elevated Lac levels are independently associated with impaired PLT aggregation across multiple agonists. Significant correlations with ROTEM and CAT parameters suggest that Lac-induced metabolic stress affects both PLT aggregation and clot initiation. Platform differences also influenced PLT function. Further analysis is needed to determine if these differences persist during storage and which platform yields PLTs best suited for storage.