Hematocrits of red blood cell units increase during storage due to changes in mean corpuscular volume, impacting outcomes of red cell exchange procedures
Authors: Lee Edward , Musante Kayla , Errico John , Rinder Henry , Kleinstein Steven , Tormey Chris , Yurtsever Nalan 
Published: October 2024

Abstract

Introduction
Hematocrits of red blood cell (RBC) units are generally not measured by blood centers or transfusion services. Red blood cell exchange (RCE) is commonly used to treat sickle cell disease, and a key parameter needed in RCE is the average hematocrit of RBC units. However, there is no consensus on the average hematocrit to use or how it is affected by storage. The goal of our study is to determine the average hematocrit of RBC units by measuring hematologic parameters RBC units during storage and performing statistical modeling of hematocrit changes over time.

Methods
We sampled aliquots of leukoreduced RBC units in AS-1 (n=10) using the Terumo TSCD-II Sterile Tubing Welder to sterilely collect ~15mL of RBCs in transfer-pack containers. Aliquots were collected weekly from Day 7 to Day 42 of storage. Complete blood counts were performed using the Sysmex XN-3100 Hematology Analyzer. We statistically modeled changes in RBC units during storage by utilizing Bayesian multilevel linear regression models, allowing for capturing effects at the individual RBC-unit level. Posterior distributions of model parameters were estimated and processed using Stan and the rethinking and rstan packages in R. Posterior distributions are summarized with posterior means and 95%-credible intervals in parentheses. Model selection was done by calculating Akaike weights using the widely applicable information criterion (WAIC) to signify statistical support for each model.

Results
Multilevel linear regression models of hematologic parameters as a function of storage time were developed. Hematocrits increased with a posterior mean of 1.4% (0.98–1.75%) per week of storage, with posterior mean hematocrits of: 61.9% (60.2–63.6%) on Day 7, 63.9% (61.5–66.4%) on Day 21, and 66.0% (62.8–69.7%) on Day 42. These results indicate that a single average cannot be used for RBC units since hematocrits dramatically increase during storage. Mean corpuscular volume (MCV) increased with a posterior mean of 2.31 fL (1.4–3.71) per week whereas hemoglobin remained stable with a posterior mean increase of 0.008 g/dL (-0.016–0.031) per week. Using these results, we subsequently developed a multilevel regression model of hematocrit as a function of MCV. The model using MCV (WAIC=100.2, weight=100%) was favored over the model using time (WAIC=120.0, weight=0%), suggesting that changes in MCV are driving the increasing hematocrits.

Conclusion
Our study is the first to leverage Bayesian statistics to carefully quantify the average hematocrits of RBC units during storage time and to demonstrate that increasing hematocrits are caused by changes in MCV. These results indicate that transfusion protocols must consider the age of RBC units for RCE calculations, and provisions (e.g., requiring use of fresh units for RCE) may help minimize the variability in post-exchange testing. Moreover, our findings suggest that transfusion services should regularly measure hematocrits of RBC units in their inventory.