Evidence map›Paper›PMID 31350268›Full record

ArticleBlood2019

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

Nareg H Roubinian, Colleen Plimier, Jennifer P Woo, Catherine Lee, Roberta Bruhn, Vincent X Liu, Gabriel J Escobar, Steven H Kleinman, Darrell J Triulzi, Edward L Murphy and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in Blood, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06840756 (Effects of Donor-recipient Sex-matched Versus Sex-mismatched Red Blood Cell Transfusion on Outcomes in Critically Ill Adult Patients), which is not on this map. Cited by 91 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT06840756 phase4recruitingnot on this mapstarted 2025, after this paper: background citation

Effects of Donor-recipient Sex-matched Versus Sex-mismatched Red Blood Cell Transfusion on Outcomes in Critically Ill Adult Patients

TypeinterventionalSponsorMichelle ZellerRan2025 to 2029Enrolled11,082ConditionsRed Blood Cell Transfusions, Sex Differences, Health Services, Critically Ill Intensive Care Unit PatientsArmsSex-mismatched red blood cell transfusions, Sex-matched red blood cell transfusions
3 · Its place in the literature

Who cites it

91 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  8. Analysis of the Efficacy of Red Blood Cell Transfusion in Very Low Birth Weight Infants and Construction of a Prediction Model.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2026
    Article
  9. Review
  10. Review
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  14. Review
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  17. Red Blood Cell Storage and Post-transfusion Recovery.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  18. Article
  19. High-Throughput Metabolomics in Transfusion Medicine.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  20. HypomorphicHemaSphere · 2026
    Article

31 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Nareg H RoubinianKaiser Permanente Northern California Division of Research, Oakland, CA.ORCID 0000-0002-1063-6155
Colleen PlimierKaiser Permanente Northern California Division of Research, Oakland, CA.
Jennifer P WooDepartment of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA.
Catherine LeeKaiser Permanente Northern California Division of Research, Oakland, CA.ORCID 0000-0003-0008-9052
Roberta BruhnVitalant Research Institute, San Francisco, CA.ORCID 0000-0002-5898-8168
Vincent X LiuKaiser Permanente Northern California Division of Research, Oakland, CA.
Gabriel J EscobarKaiser Permanente Northern California Division of Research, Oakland, CA.ORCID 0000-0003-2540-3327
Steven H KleinmanDepartment of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada; and.
Darrell J TriulziDepartment of Pathology, University of Pittsburgh, Pittsburgh, PA.
Edward L MurphyDepartment of Laboratory Medicine, University of California, San Francisco, San Francisco, CA.
Michael P BuschVitalant Research Institute, San Francisco, CA.

Funding

Effects of blood conservation and donor characteristics on transfused patient outcomes in a large community hospital networkR01HL126130 · NHLBI · VITALANT · PI ROUBINIAN, NAREG · 2016 to 2019
$1.9M
NHLBI NIH HHS R01 HL126130
6 · The paper itself

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 (

Indexed as

Erythrocyte TransfusionAdultAgedAged, 80 and overAge FactorsBlood DonorsBlood PreservationBlood Specimen CollectionFemaleHemoglobinsHumansMaleMiddle AgedRetrospective StudiesSex FactorsHemoglobins

Identifiers

PMID31350268
PMCPMC6764268

What OpenQuestion holds

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Registered trials

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.