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Record W4367623796 · doi:10.53855/bjt.v26i1.500_eng

The Halifax flow Crossmatch Protocol Results According to the HLA Class and MFI of the DSA

2023· article· en· W4367623796 on OpenAlexaffabout
Tiago Schiavo, Juliana Montagner, Elizete Keitel, Anna L. Greenshields, Robert Liwski, Jorge Neumann

Bibliographic record

VenueBrazilian Journal of Transplantation · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHuman leukocyte antigenDonor specific antibodiesMedicineImmunogenicityProtocol (science)AntibodyImmunologyInternal medicineAntigenPathology

Abstract

fetched live from OpenAlex

Introduction: The main strategy to reduce the immunogenicity of transplanted grafts is to seek maximum compatibility between alloantigens in the donor-recipient pair. It is understood that the virtual crossmatch (VXM) can be a good tool in the evaluation of the donor / recipient pair and that a broader application of these protocols will improve the pre-transplant immunological risk assessment. The aim of this study was to correlate the physical flow crossmatches results, looking at different mean fluorescence intensity (MFI) values of the donor specific antibodies (DSA), and the probability of a positive crossmatch. We also aimed to validate this tool using a well standardized flow crossmatch protocol. Methods: We performed a total of 15,217 FCXM between 2015 and 2019. All were tested by the Halifax Flow Cytometer Crossmatch (FCXM) protocol, with cells from deceased donors and serum from renal recipients. For this analysis we selected only samples that had one or two DSA per locus (N = 1,081), when the MFI was above 1,000, and they were divided according to the allelic group recognized by the antibody (anti-HLA-A, B, C, DR or DQ) looking at the probability of a positive crossmatch with different MFI values of the DSAs. Combinations among them were also analyzed in the same way (N=175). Results: In the presence of an exclusive DSA against the allelic groups A, B and DR, with an index MFI above 5,000, all the FCXM were positives. With exclusively antibodies against groups C or DQ, all cases with DSAs above 15,000 MFIs were positives. With two or more DSAs anti A and/or B, and/or DR, when their MFIs sums exceeded 5,000, all FCXM results against B cells were positive. The presence of anti-Class I DSAs (A, B and A+B), regardless of the MFI value, was responsible for 71% (N=424 of 601) of the T cell positivity and 77% (N=460 of 661) in the B cell crossmatches. The presence of only anti-Class II DSAs (DR and DQ) accounted for 55% (N=168 of 303) of FCXM positivity in B cells. The overall mean of the MFI of the DSAs was higher in the FCXM positive group when compared to negative crossmatch. The group with sum of DSAs A (N=217) showed that when the sum was 4,000 MFI or higher, there was a 24 times higher probability for a positive B cell crossmatch when compared with lowers MFIs. Conclusions: Our results show a strong association between the DSA MFI and the FCXM result. The data here presented confirm the results of our previous studies, justifying the VXM standard used by our center, proving to be a good tool to streamline the selection of transplant recipients and facilitate the sharing of organs from national donors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.328
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes2
Has abstractyes

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