Literature DB >> 31350268

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

Nareg H Roubinian1,2,3, Colleen Plimier1, Jennifer P Woo4, Catherine Lee1, Roberta Bruhn2,3, Vincent X Liu1, Gabriel J Escobar1, Steven H Kleinman5, Darrell J Triulzi6, Edward L Murphy3,2, Michael P Busch2,3.   

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. Hemoglobin levels before and after RBC transfusions and at 24- and 48-hour intervals after transfusion were analyzed. Generalized estimating equation linear regression models were fit to examine hemoglobin increments after RBC transfusion adjusting for donor and recipient demographic characteristics, 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 pretransfusion hemoglobin levels were significant predictors of hemoglobin increments in univariate and multivariable analyses (P < .01). For hemoglobin increments 24 hours after transfusion, the coefficient of determination for the generalized estimating equation models was 0.25, with an estimated correlation between actual and predicted values of 0.5. Collectively, blood donor demographic characteristics, 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 posttransfusion increments and other patient outcomes.
© 2019 by The American Society of Hematology.

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Year:  2019        PMID: 31350268      PMCID: PMC6764268          DOI: 10.1182/blood.2019000773

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  70 in total

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2.  Contemporary Risk Factors and Outcomes of Transfusion-Associated Circulatory Overload.

Authors:  Nareg H Roubinian; Jeanne E Hendrickson; Darrell J Triulzi; Jerome L Gottschall; Michael Michalkiewicz; Dhuly Chowdhury; Daryl J Kor; Mark R Looney; Michael A Matthay; Steven H Kleinman; Donald Brambilla; Edward L Murphy
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3.  Ethnicity, sex, and age are determinants of red blood cell storage and stress hemolysis: results of the REDS-III RBC-Omics study.

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Journal:  Blood Adv       Date:  2017-06-27

4.  Association of Donor Age and Sex With Survival of Patients Receiving Transfusions.

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8.  The National Heart, Lung, and Blood Institute Recipient Epidemiology and Donor Evaluation Study (REDS-III): a research program striving to improve blood donor and transfusion recipient outcomes.

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Review 10.  Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion.

Authors:  Jeffrey L Carson; Simon J Stanworth; Nareg Roubinian; Dean A Fergusson; Darrell Triulzi; Carolyn Doree; Paul C Hebert
Journal:  Cochrane Database Syst Rev       Date:  2016-10-12
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7.  A rose is a rose is a rose, or not.

Authors:  Steven L Spitalnik
Journal:  Blood       Date:  2019-09-26       Impact factor: 22.113

8.  Rapid clearance of storage-induced microerythrocytes alters transfusion recovery.

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9.  Fatty acid desaturase activity in mature red blood cells and implications for blood storage quality.

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10.  Additive effects of blood donor smoking and gamma irradiation on outcome measures of red blood cell transfusion.

Authors:  Robert A DeSimone; Colleen Plimier; Catherine Lee; Tamir Kanias; Melissa M Cushing; Bruce S Sachais; Steven Kleinman; Michael P Busch; Nareg H Roubinian
Journal:  Transfusion       Date:  2020-05-01       Impact factor: 3.337

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