Literature DB >> 29067705

Demographic and epidemiologic characterization of transfusion recipients from four US regions: evidence from the REDS-III recipient database.

Matthew S Karafin1, Roberta Bruhn2, Matt Westlake3,4, Marian T Sullivan3,4, Walter Bialkowski1, Gustaf Edgren5,6, Nareg H Roubinian2, Ronald G Hauser7, Daryl J Kor8, Debra Fleischmann3,4, Jerome L Gottschall1, Edward L Murphy2, Darrell J Triulzi9.   

Abstract

BACKGROUND: Blood transfusion is one of the most common medical procedures during hospitalization in the United States. To understand the benefits of transfusion while mitigating potential risks, a multicenter database containing detailed information on transfusion incidence and recipient outcomes would facilitate research. STUDY DESIGN AND METHODS: The Recipient Epidemiology and Donor Evaluation Study-III (REDS-III) program has developed a comprehensive transfusion recipient database utilizing data from hospital electronic health records at 12 participating hospitals in four geographic regions. Inpatient and outpatient data on transfusion recipients from January 1, 2013 to December 31, 2014 included patient age, sex, ethnicity, primary diagnosis, type of blood product provided, issue location, pretransfusion and post-transfusion hemoglobin (Hgb), and hospital outcomes. Transfusion incidence per encounter was calculated by blood product and various patient characteristics.
RESULTS: During the 2-year study period, 80,362 (12.5%) inpatient encounters involved transfusion. Among inpatients, the most commonly transfused blood products were red blood cells (RBCs; 10.9% of encounters), followed by platelets (3.2%) and plasma (2.9%). Among patients who received transfusions, the median number of RBC units was one, the pretransfusion Hgb level was 7.6 g/dL, and the Hgb increment per unit was 1.4 g/dL. Encounter mortality increased with patient age, the number of units transfused, and the use of platelet or plasma products. The most commonly reported transfusion reaction was febrile nonhemolytic.
CONCLUSION: The database contains comprehensive data regarding transfusion use and patient outcomes. The current report describes an evaluation of the first 2 years of a planned, 4-year, linked blood donor-component-recipient database, which represents a critical new resource for transfusion medicine researchers.
© 2017 AABB.

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Year:  2017        PMID: 29067705      PMCID: PMC5758361          DOI: 10.1111/trf.14370

Source DB:  PubMed          Journal:  Transfusion        ISSN: 0041-1132            Impact factor:   3.157


  32 in total

1.  Liberal or restrictive transfusion in high-risk patients after hip surgery.

Authors:  Jeffrey L Carson; Michael L Terrin; Helaine Noveck; David W Sanders; Bernard R Chaitman; George G Rhoads; George Nemo; Karen Dragert; Lauren Beaupre; Kevin Hildebrand; William Macaulay; Courtland Lewis; Donald Richard Cook; Gwendolyn Dobbin; Khwaja J Zakriya; Fred S Apple; Rebecca A Horney; Jay Magaziner
Journal:  N Engl J Med       Date:  2011-12-14       Impact factor: 91.245

Review 2.  The rise of big clinical databases.

Authors:  J A Cook; G S Collins
Journal:  Br J Surg       Date:  2015-01       Impact factor: 6.939

3.  A novel method of data analysis for utilization of red blood cell transfusion.

Authors:  Steven M Frank; Linda M S Resar; James A Rothschild; Elizabeth A Dackiw; Will J Savage; Paul M Ness
Journal:  Transfusion       Date:  2013-04-29       Impact factor: 3.157

4.  Wide variations in blood product transfusion practices among providers who care for patients with acute leukemia in the United States.

Authors:  Alexander B Pine; Eun-Ju Lee; Mikkael Sekeres; David P Steensma; Daniel Zelterman; Thomas Prebet; Amy DeZern; Rami Komrokji; Mark Litzow; Selina Luger; Richard Stone; Harry P Erba; Guillermo Garcia-Manero; Alfred I Lee; Nikolai A Podoltsev; Lisa Barbarotta; Stephanie Kasberg; Jeanne E Hendrickson; Steven D Gore; Amer M Zeidan
Journal:  Transfusion       Date:  2016-11-22       Impact factor: 3.157

5.  Trends in red blood cell transfusion and 30-day mortality among hospitalized patients.

Authors:  Nareg H Roubinian; Gabriel J Escobar; Vincent Liu; Bix E Swain; Marla N Gardner; Patricia Kipnis; Darrell J Triulzi; Jerome L Gottschall; Yan Wu; Jeffrey L Carson; Steven H Kleinman; Edward L Murphy
Journal:  Transfusion       Date:  2014-08-18       Impact factor: 3.157

6.  Transfusion-related adverse reactions reported to the National Healthcare Safety Network Hemovigilance Module, United States, 2010 to 2012.

Authors:  Alexis R Harvey; Sridhar V Basavaraju; Koo-Whang Chung; Matthew J Kuehnert
Journal:  Transfusion       Date:  2014-11-05       Impact factor: 3.157

7.  Blood donation and blood donor mortality after adjustment for a healthy donor effect.

Authors:  Henrik Ullum; Klaus Rostgaard; Mads Kamper-Jørgensen; Marie Reilly; Mads Melbye; Olof Nyrén; Rut Norda; Gustaf Edgren; Henrik Hjalgrim
Journal:  Transfusion       Date:  2015-06-22       Impact factor: 3.157

8.  Length of Storage of Red Blood Cells and Patient Survival After Blood Transfusion: A Binational Cohort Study.

Authors:  Märit Halmin; Klaus Rostgaard; Brian K Lee; Agneta Wikman; Rut Norda; Kaspar René Nielsen; Ole B Pedersen; Jacob Holmqvist; Henrik Hjalgrim; Gustaf Edgren
Journal:  Ann Intern Med       Date:  2016-12-20       Impact factor: 25.391

9.  Clinical effects of blood donor characteristics in transfusion recipients: protocol of a framework to study the blood donor-recipient continuum.

Authors:  Michaël Chassé; Lauralyn McIntyre; Alan Tinmouth; Jason Acker; Shane W English; Greg Knoll; Alan Forster; Nadine Shehata; Kumanan Wilson; Carl van Walraven; Robin Ducharme; Dean A Fergusson
Journal:  BMJ Open       Date:  2015-01-19       Impact factor: 2.692

10.  Predicting red blood cell transfusion in hospitalized patients: role of hemoglobin level, comorbidities, and illness severity.

Authors:  Nareg H Roubinian; Edward L Murphy; Bix E Swain; Marla N Gardner; Vincent Liu; Gabriel J Escobar
Journal:  BMC Health Serv Res       Date:  2014-05-10       Impact factor: 2.655

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  25 in total

1.  Intradonor reproducibility and changes in hemolytic variables during red blood cell storage: results of recall phase of the REDS-III RBC-Omics study.

Authors:  Marion C Lanteri; Tamir Kanias; Sheila Keating; Mars Stone; Yuelong Guo; Grier P Page; Donald J Brambilla; Stacy M Endres-Dighe; Alan E Mast; Walter Bialkowski; Pam D'Andrea; Ritchard G Cable; Bryan R Spencer; Darrell J Triulzi; Edward L Murphy; Steven Kleinman; Mark T Gladwin; Michael P Busch
Journal:  Transfusion       Date:  2018-11-08       Impact factor: 3.157

2.  Diversity in a blood bag: application of omics technologies to inform precision Transfusion Medicine.

Authors:  Tamir Kanias; Michael P Busch
Journal:  Blood Transfus       Date:  2019-06-05       Impact factor: 3.443

Review 3.  Protect, repair, destroy or sacrifice: a role of oxidative stress biology in inter-donor variability of blood storage?

Authors:  Angelo D'Alessandro; Kirk C Hansen; Elan Z Eisenmesser; James C Zimring
Journal:  Blood Transfus       Date:  2019-06-06       Impact factor: 3.443

4.  Frequent blood donations alter susceptibility of red blood cells to storage- and stress-induced hemolysis.

Authors:  Tamir Kanias; Mars Stone; Grier P Page; Yuelong Guo; Stacy M Endres-Dighe; Marion C Lanteri; Bryan R Spencer; Ritchard G Cable; Darrell J Triulzi; Joseph E Kiss; Edward L Murphy; Steve Kleinman; Mark T Gladwin; Michael P Busch; Alan E Mast
Journal:  Transfusion       Date:  2018-11-26       Impact factor: 3.157

5.  Therapeutic impact of red blood cell transfusion on anemic outpatients: the RETRO study.

Authors:  Elizabeth St Lezin; Matthew S Karafin; Roberta Bruhn; Dhuly Chowdhury; Lirong Qu; Walter Bialkowski; Scott Merenda; Pamela D'Andrea; Anne-Lyne McCalla; Lisa Anderson; Sheila M Keating; Mars Stone; Edward L Snyder; Donald Brambilla; Edward L Murphy; Philip J Norris; Joan F Hilton; Bryan R Spencer; Steven Kleinman; Jeffrey L Carson
Journal:  Transfusion       Date:  2019-03-18       Impact factor: 3.157

6.  Association of Blood Donor Sex and Prior Pregnancy With Mortality Among Red Blood Cell Transfusion Recipients.

Authors:  Gustaf Edgren; Edward L Murphy; Don J Brambilla; Matt Westlake; Klaus Rostgaard; Catherine Lee; Ritchard G Cable; Darrell Triulzi; Roberta Bruhn; Elizabeth M St Lezin; Christian Erikstrup; Henrik Ullum; Simone A Glynn; Steve Kleinman; Henrik Hjalgrim; Nareg H Roubinian
Journal:  JAMA       Date:  2019-06-11       Impact factor: 56.272

7.  Association of donor age, body mass index, hemoglobin, and smoking status with in-hospital mortality and length of stay among red blood cell-transfused recipients.

Authors:  Nareg H Roubinian; Matt Westlake; Elizabeth M St Lezin; Gustaf Edgren; Don J Brambilla; Catherine Lee; Roberta Bruhn; Ritchard G Cable; Darrell J Triulzi; Simone A Glynn; Steve Kleinman; Edward L Murphy
Journal:  Transfusion       Date:  2019-10-11       Impact factor: 3.157

8.  Clinical and genetic ancestry profile of a large multi-centre sickle cell disease cohort in Brazil.

Authors:  Anna B F Carneiro-Proietti; Shannon Kelly; Carolina Miranda Teixeira; Ester C Sabino; Cecilia S Alencar; Ligia Capuani; Tassila P Salomon Silva; Aderson Araujo; Paula Loureiro; Cláudia Máximo; Clarisse Lobo; Miriam V Flor-Park; Daniela O W Rodrigues; Rosimere A Mota; Thelma T Gonçalez; Carolyn Hoppe; João E Ferreira; Mina Ozahata; Grier P Page; Yuelong Guo; Liliana R Preiss; Donald Brambilla; Michael P Busch; Brian Custer
Journal:  Br J Haematol       Date:  2018-07-19       Impact factor: 6.998

9.  Risk factors for red blood cell alloimmunization in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) database.

Authors:  Matthew S Karafin; Matt Westlake; Ronald G Hauser; Christopher A Tormey; Philip J Norris; Nareg H Roubinian; Yanyun Wu; Darrell J Triulzi; Steve Kleinman; Jeanne E Hendrickson
Journal:  Br J Haematol       Date:  2018-04-19       Impact factor: 6.998

Review 10.  Banking with precision: transfusion medicine as a potential universal application in clinical genomics.

Authors:  Celina Montemayor; Patricia A R Brunker; Margaret A Keller
Journal:  Curr Opin Hematol       Date:  2019-11       Impact factor: 3.284

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