The Recipient Epidemiology and Donor Evaluation Study‐IV‐Pediatric (REDS‐IV‐P): A research program striving to improve blood donor safety and optimize transfusion outcomes across the lifespan

Abstract

Background The Recipient Epidemiology and Donor Evaluation Study‐IV‐Pediatric (REDS‐IV‐P) is a new iteration of prior National Heart, Lung, and Blood Institute (NHLBI) REDS programs that focus on improving transfusion recipient outcomes across the lifespan as well as the safety and availability of the blood supply. Study Design and Methods The US program includes blood centers and hospitals (22 including 6 free‐standing Children's hospitals) in four geographic regions. The Brazilian program has 5 participating hemocenters. A Center for Transfusion Laboratory Studies (CTLS) and a Data Coordinating Center (DCC) support synergistic studies and activities over the 7‐year REDS‐IV‐P program. Results The US is building a centralized, vein‐to‐vein (V2V) database, linking information collected from blood donors, their donations, the resulting manufactured components, and data extracts from hospital electronic medical records of transfused and non‐transfused patients. Simultaneously, the Brazilian program is building a donor, donation, and component database. The databases will serve as the backbone for retrospective and prospective observational studies in transfusion epidemiology, transfusion recipient outcomes, blood component quality, and emerging blood safety issues. Special focus will be on preterm infants, patients with sickle cell disease, thalassemia or cancer, and the effect of donor biologic variability and component manufacturing on recipient outcomes. A rapid response capability to emerging safety threats has resulted in timely studies related to Severe Acute Respiratory Syndrome Corona Virus‐2 (SARS‐CoV‐2). Conclusions The REDS‐IV‐P program endeavors to improve donor‐recipient‐linked research with a focus on children and special populations while also maintaining the flexibility to address emerging blood safety issues.

Common Data Model-based Analysis of Selective Leukoreduction Protocol Compliance at Three Hospitals

“…To evaluate SLPC of several groups, including patients not yet recognized as having an indication of SLP requirement, we analyzed the medical records of 166,641 patients from three institutions over 20 years, which would be impossible without CDM analysis. Our findings confirm the applicability of CDM analysis to transfusion safety and suggest the possibility of future CDMbased distributed network research using transfusion prescription data [14,15].…”

Blood donor, component, and recipient‐specific factors associated with venous thromboembolism in transfused hospitalized adult patients: Data from the recipient epidemiology and donor evaluation Study‐III (REDS‐III)

“…To further evaluate potential mechanisms of the above findings, studies are being carried out to link donor-specific genetic, hemolytic, and metabolomic data from the REDS-III RBC-Omics study, to RBC transfusion outcomes as part of the REDS-III linked donor-component-recipient database. [21][22][23][24]…”

“…The risk for VTE could be further accentuated with transfusion of uncommon RBC units from donors with genetic polymorphisms or social behaviors that have been associated with hemolysis or other measures of reduced RBC quality. To further evaluate potential mechanisms of the above findings, studies are being carried out to link donor‐specific genetic, hemolytic, and metabolomic data from the REDS‐III RBC‐Omics study, to RBC transfusion outcomes as part of the REDS‐III linked donor‐component‐recipient database 21–24 …”

Proceedings of the 2022 NHLBI and OASH state of the science in transfusion medicine symposium

“…Comprehensive V2V databases containing linked information on donors, components produced from the donations, and transfusion recipients can be curated and utilized to answer research questions in transfusion medicine and support analysis of various populations of interest and/or rare exposures and outcomes. 56 Utilizing a widely adopted data format such as the observational medical outcomes partnership (OMOP) common data model may allow for ease of combining multiple V2V databases, dramatically increasing sample sizes and scale and thus power of available datasets. In addition, advanced real-time data visualization can further facilitate understanding of PBM practices and intra-and interinstitutional benchmarking of performance.…”