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Effect of donor, component and recipient characteristics on hemoglobin increments following red blood cell transfusion

Nareg Roubinian, Colleen Plimier, Jennifer Woo, Catherine Lee, Roberta Bruhn, Vincent Liu, Gabriel Jorge Escobar, Steven H Kleinman, Darrell J Triulzi, Edward L. Murphy and Michael P Busch

Key Points

  • Blood donor, component, and recipient characteristics are significant predictors of hemoglobin increments after red blood cell transfusion.

  • Collectively, these factors account for the variation observed in practice and allow prediction of changes in hemoglobin with transfusion.

Abstract

Significant research has focused individually on blood donors, product preparation and storage, and optimal transfusion practice. To better understand the interplay between these factors on measures of red blood cell (RBC) transfusion efficacy, we conducted a linked analysis of blood donor and component data with patients who received single-unit RBC transfusions between 2008 and 2016. We analyzed hemoglobin levels prior to and after RBC transfusions and at 24 and 48-hour intervals following transfusion. Generalized estimating equation (GEE) linear regression models were fit to examine hemoglobin increments after RBC transfusion adjusting for donor and recipient demographics, collection method, additive solution, gamma irradiation, and storage duration. We linked data on 23,194 transfusion recipients who received one or more single-unit RBC transfusions (n=38,019 units) to donor demographic and component characteristics. Donor and recipient sex, Rh-D status, collection method, gamma irradiation, recipient age and body mass index, and pre-transfusion hemoglobin levels were significant predictors of hemoglobin increments in univariate and multivariable analyses (p<0.01). For hemoglobin increments 24 hours after transfusion, the coefficient of determination for GEE models was 0.25 with estimated correlation between actual and predicted values of 0.5. Collectively, blood donor demographics, collection and processing methods, and recipient characteristics accounted for significant variation in hemoglobin increments related to RBC transfusion. Multivariable modeling allows the prediction of changes in hemoglobin using donor, component, and patient-level characteristics. Accounting for these factors will be critical for future analyses of donor and component factors, including genetic polymorphisms, on post-transfusion increments and other patient outcomes.

  • Submitted March 25, 2019.
  • Revision received July 25, 2019.
  • Accepted July 17, 2019.