Evidence map›Paper›PMID 40251842›Full record

ArticleTransfusion2025

Evaluation of nonspecific reactivity rates across three immunohematology testing platforms with assessment of subsequent specific alloantibody development.

Nalan Yurtsever, Gabrielle Carmichael, Ryan Malonis, Matthew Z Madden, Numan Isik, Muhammad U Ahmed, Laurie Bizzario, Bhushan Shah, Christopher A Tormey, Edward S Lee

Abstract read
In one paragraph

Article in Transfusion, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

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

1 citing paper in PubMed.

  1. 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

10 authors.

Nalan YurtseverDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0001-7807-6046
Gabrielle CarmichaelDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
Ryan MalonisDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
Matthew Z MaddenDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0003-4062-4427
Numan IsikMassachusetts General Physician Organization Dermatopathology Associates, Newton, Massachusetts, USA.ORCID https://orcid.org/0009-0009-2627-6308
Muhammad U AhmedDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
Laurie BizzarioDepartment of Laboratory Medicine, Yale New Haven Hospital, New Haven, Connecticut, USA.
Bhushan ShahDepartment of Laboratory Medicine, Yale New Haven Hospital, New Haven, Connecticut, USA.
Christopher A TormeyDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0003-1785-2245
Edward S LeeDepartment of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0003-1723-4463

Funding

IMMUNOHEMATOLOGY/TRANSFUSION MEDICINE RESEARCH TRAININGT32HL007974 · NHLBI · YALE UNIVERSITY · PI JEANNE E HENDRICKSON, Diane S Krause · 2001 to 2026
$8.1M
NHLBI NIH HHS T32 HL007974NHLBI NIH HHS T32HL007974-23
6 · The paper itself

Abstract

backgroundGel and solid-phase testing platforms are commonly used for pretransfusion testing but are also prone to nonspecific reactivities (NSP) compared to tube testing. This study aims to characterize the features of NSPs in these platforms and how frequently NSPs precede specific antibody detection.

methodsAll antibody screens and identification panels performed between 5/2021-4/2023 by two automated and one manual platforms at a single institution were analyzed with IRB approval: solid-phase (Immucor, Norcross, GA), automated gel (Grifols, Los Angeles, CA), and manual gel (Ortho Diagnostics, Raritan, NJ). Testing platform, antibody identification, strength of reactivity, number of reactive reagent red cells, and RBC antibody history were extracted from chart review. Differences in reactivity strength were compared using the Kruskal-Wallis test, and differences in the number of cells used to establish diagnoses of NSPs were compared using two-way ANOVA.

resultsDuring the 24-month study period, a total of 156,247 antibody screens were performed with 5491 positive screens, and NSP was identified on 358/5491 panels (6.6%). 271/5491 (4.9%) panels had NSP detected on non-tube platforms: 95 on solid-phase, 123 on automated gel, and 53 on manual gel. The mean strength of reactivity by agglutination for NSP was 1.7, 0.5, and 1.4, respectively (p < .001). In addition, 9/271 (3.3%) of all panels with NSP on gel or solid-phase were associated with the detection of specific alloantibodies in subsequent panels.

conclusionNonspecific reactions differ by platforms in specificity and strength. Solid-phase shows stronger reactivity, while automated gel has higher rates of positivity.

Indexed as

Blood Grouping and CrossmatchingIsoantibodiesHumansIsoantibodiesautomated immunohematology testingnonspecific antibodynonspecific reactivityred blood cell antibody

Identifiers

PMID40251842
PMCPMC12092180

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Registered trials

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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.