Evidence map›Paper›PMID 42374985›Full record

ArticleHLA2026

A Flow Cytometry Crossmatch With Combined Cytotoxicity and IgG Detection: Ten Years of Use in Deceased Donor Kidney Allocation.

Mats Alheim, Torsten Eich

Abstract read
In one paragraph

Article in HLA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Mats AlheimDepartment of Laboratory Medicine, Division of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden.ORCID https://orcid.org/0009-0004-9169-4155
Torsten EichDepartment of Laboratory Medicine, Division of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virtual crossmatch (VXM) is increasingly used in deceased-donor kidney allocation, raising questions about the added value of a physical crossmatch (PXM) when donor-specific antibody (DSA) are absent. We applied our previously described flow cytometry-based assay (FCtox), combining complement-mediated cytotoxicity and IgG binding, across 3236 routine crossmatches performed between 2018 and 2024. All donor offers underwent VXM followed by prospective PXM. Among 704 patients, 95% of FCtox assays were performed in VXM- cases. FCtox positivity was uncommon in VXM- cases (9%), and overall concordance between VXM and FCtox was high (89%). Further analyses indicated that isolated FCtox abnormalities in VXM- cases primarily reflect patient-specific background reactivity, including non-HLA or IgM-mediated effects. Among transplanted VXM- patients with FCtox positivity (n = 12), no early antibody-mediated rejection occurred. In VXM+ patients, DSA mean fluorescence intensity (MFI) values above 5000 were associated with increased likelihood of FCtox IgG positivity, although overlap between groups limited the ability of MFI alone to predict FCtox IgG reactivity. Overall, VXM reliably identified clinically meaningful immunologic risk, while FCtox added little value in VXM- candidates but remained useful in selected VXM+ or discordant scenarios. These findings support a VXM-driven allocation strategy with selective rather than routine use of PXM.

Indexed as

Flow CytometryGraft RejectionHistocompatibility TestingImmunoglobulin GIsoantibodiesKidney TransplantationAdultFemaleHLA AntigensHumansMaleMiddle AgedTissue DonorsHLA AntigensImmunoglobulin GIsoantibodiesdonor‐specific antibodiesflow cytometry crossmatchHLA antibodieskidney transplantationvirtual crossmatch

Identifiers

PMID42374985
PMCPMC13349705

What OpenQuestion holds

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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.