Flow Cytometric Crossmatching in Primary Renal Transplant Recipients with a Negative Anti-Human Globulin Enhanced Cytotoxicity Crossmatch
Bibliographic record
Abstract
Flow cytometric crossmatching (FCXM) and panel reactive antibody (PRA) screening techniques are more sensitive than anti-human globulin enhanced cytotoxicity (AHG-CDC) techniques at detecting anti-HLA antibodies. The clinical significance of a positive FCXM in primary renal transplant recipients with a negative AHG-CDC crossmatch is unclear. We performed retrospective FCXM and flow cytometric panel reactive antibody (FlowPRA) determinations in primary renal transplant recipients with a negative T cell AHG-CDC crossmatch and a negative B cell CDC crossmatch pretransplant. Eighteen (13%) of 143 patients exhibited a positive retrospective T cell FCXM. Of these patients, six (33%) experienced early graft loss with explant histology, demonstrating antibody-mediated rejection in five of six cases. The 12 patients with positive T cell FCXM who maintained their grafts experienced more adverse events posttransplant, including more early, steroid-resistant, and recurrent rejection. Furthermore, in a subgroup of patients undergoing protocol biopsies, those with a positive T cell FCXM exhibited more subclinical rejection. Anti-HLA antibodies were detected by FlowPRA in all 18 patients with a positive T cell FCXM, whereas AHG-CDC PRA detected antibodies in only 8 of 18 patients. Therefore, flow cytometric techniques identify sensitized primary renal transplant recipients undetected by AHG-CDC techniques. In those patients, a positive T cell FCXM is associated with an increased risk of early graft loss due to antibody-mediated rejection and may represent a relative contraindication to transplantation. Moreover, those patients are also at increased risk of severe and recurrent rejection, which may carry implications for long-term graft outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".