#1523 Two cases of hyperacute rejection after AB0 incompatible kidney transplantation – unexpected antibodies
Bibliographic record
Abstract
Abstract Background and Aims Although ABO-incompatible (ABOi) living donor kidney transplantation is currently performed on a routine basis, it remains a procedure with a high immunologic risk requiring both immunosuppression aimed at diminishing antibody production and removal of circulating antibodies from the recipient's blood. Method We describe two cases of kidney transplant recipients (KTR) who experienced hyperacute antibody-mediated rejection after ABOi transplantation and further testing was performed on their sera using a novel bead-based ABO antibody assay to understand the cause of such unfortunate outcomes. Results Both patients were ABO-O recipients who received ABO-A grafts; neither had donor-specific anti-HLA antibodies (DSA). Both received rituximab >4 weeks and standard immunosuppression according to the Swiss ABOi protocol, starting 10–25 days before transplantation; basiliximab was used for induction at time of transplant. Immunoadsorption was performed before transplant with a nonselective Therasorb column; immunoadsorption effectiveness was analyzed by measuring the anti-A-IgG titer and anti-A-IgM titer by gel column agglutination technique. Case 1: Transplantation was performed after 17 immunoadsorption runs (prolonged due to postponed date of surgery for non-immunological reasons); post-adsorption anti-A titres were negative IgG and <1:8 IgM. After an initial diuresis, the patient became anuric within 24 hours. Biopsy histology revealed hyperacute rejection. Graft nephrectomy was performed two days post-transplant. Case 2: transplantation was performed after 11 immunoadsorption runs; post-adsorption anti-A titres were negative IgG and 1:1 IgM. After an initial diuresis urine output decreased within hours. Biopsy histology showed hyperacute rejection. Plasmapheresis was started empirically approximately 15 hours after transplant despite negative anti-A titer and no anti-HLA DSA, and treatment with high dose steroids, IVIG and eculizumab was administered. Graft nephrectomy was performed seven days post-transplant. Analysis of the original sera with a novel single antigen bead assay for anti-A subtype-specific antibodies showed an initial drop in MFIs of IgG and IgM for both patients. However, at time of transplant, despite acceptable anti-A titers with our standard hemagglutination methods, patient 1 and 2 MFI were still 17200 and 9300, respectively for anti-A-IgG isotype antibodies (II, III and IV averaged) and 3300 and 3800 for anti-A-IgM isotype IgM (II, III and IV averaged). Analysis of sera from the days immediately after transplantation showed a rebound for these subtype-specific anti-A antibodies in Case 1, with an MFI up to 26000 (anti-A-IgG) and 5000 (anti-A-IgM). In Case 2 (where samples were drawn after plasmapheresis) the MFIs of the anti-A-II/III/IV further dropped to 2100 (IgG) and 1200 (IgM). Refer to Fig. 1 for antibody data. Conclusion Hyperacute AMR in these two ABO-A-incompatible kidney transplant cases was likely due to insufficient removal of anti-A antibodies. Whether this is due to insufficient removal of anti-A antibodies by the nonselective Therasorb column needs to be further investigated. These results suggest that for such an immunological high-risk procedure, a switch from titer-based diagnostics to single bead Luminex diagnostics should be considered. Of further note, transcriptome diagnostics might support the histology, but it is not yet established in ABOi graft biopsies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".