Evidence map›Paper›PMID 29675950›Full record

ArticleBritish journal of haematology2018

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

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 and 1 more

Open access · bronzeAbstract readEvaluation StudyMulticenter Study
In one paragraph

Article in British journal of haematology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 122 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. The Immunology of Transfusion Medicine: Past, Present, and Future.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  6. Use of Microbial Microarrays to Define Antibody Specificity.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Erythrocyte Alloimmunization and Autoimmunization in the Pediatric Population: A Multicenter, Cross-Sectional Study in Central China.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 7 institutions in 2 countries.

Matthew S KarafinBlood Center of Wisconsin, Milwaukee, WI, USA.
Matt WestlakeRTI International, Rockville, MD, USA.
Ronald G HauserDepartment of Laboratory Medicine, Yale University, New Haven, CT, USA.
Christopher A TormeyDepartment of Laboratory Medicine, Yale University, New Haven, CT, USA.ORCID 0000-0003-1785-2245
Philip J NorrisUniversity of California, San Francisco, CA, USA.
Nareg H RoubinianUniversity of California, San Francisco, CA, USA.
Yanyun WuDepartment of Laboratory Medicine, Yale University, New Haven, CT, USA.
Darrell J TriulziUniversity of Pittsburgh and Institute of Transfusion Medicine, Pittsburgh, PA, USA.
Steve KleinmanUniversity of British Columbia, Vancouver, British Columbia, Canada.
Jeanne E HendricksonDepartment of Laboratory Medicine, Yale University, New Haven, CT, USA.ORCID 0000-0002-7928-3132
NHLBI Recipient Epidemiology and Donor Evaluation Study-III (REDS-III)
Yale University · USUniversity of California, San Francisco · USBloodworks Northwest · USRTI International · USUniversity of British Columbia · CAUniversity of Pittsburgh · USVersiti Blood Center of Wisconsin · US

Funding

NHLBI NIH HHS HHSN268201100004INHLBI NIH HHS HHSN268201100005CNHLBI NIH HHS HHSN268201100005GNHLBI NIH HHS HHSN268201100005IWHI NIH HHS HHSN268201100004C
6 · The paper itself

Abstract

Despite the significance of red blood cell (RBC) alloimmunization, the lack of standardized registries in the US has prevented the completion of large studies. Data from 3·5 years of the Recipient Epidemiology and Donor Evaluation Study-III (REDS-III) recipient database, containing information from 12 hospitals, were studied. A RBC alloantibody responder had an antibody identified at any point during the study, and a non-responder had a negative antibody screen at least 15 days post-RBC transfusion. Demographics, blood type, ICD9/10 codes, and other potential correlates were evaluated. Of 319 177 (2·07%) screened patients, 6597 had a total of 8892 clinically significant RBC alloantibodies identified, with 75% being in the Rh or Kell families. Alloimmunization was more common in females (2·38%) than males (1·68%), and in RhD negative (2·82%) than RhD positive (1·94%) patients. Age, sex, RhD status and race were associated with being a responder, and certain diagnoses (including sickle cell disease or trait, systemic lupus erythematosus, rheumatoid arthritis and myelodysplastic syndrome) were more common among responders than non-responders. Data collected in this multi-centre recipient database provide the largest RBC alloimmunized patient cohort studied in the US, with previously known demographic and disease associations of responder status confirmed, and new associations identified.

Indexed as

Blood DonorsDatabases, FactualErythrocyte TransfusionImmunizationTransfusion ReactionAdolescentAdultAgedAged, 80 and overAnemia, Sickle CellArthritis, RheumatoidBlood Group AntigensChildChild, PreschoolFemaleHumansBlood Group AntigensIsoantibodiesalloimmunizationantibodiesred blood cellstransfusion

Identifiers

PMID29675950
PMCPMC5991618
OpenAlexW2801066337

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.