Clinical relevance of HLA-DQ eplet mismatch and maintenance immunosuppression with risk of allosensitization after kidney transplant failure
Bibliographic record
Abstract
The optimal immunosuppression management in patients with a failed kidney transplant remains uncertain. This study analyzed the association of class II HLA eplet mismatches and maintenance immunosuppression with allosensitization after graft failure in a well characterized cohort of 21 patients who failed a first kidney transplant. A clinically meaningful increase in cPRA in this study was defined as the cPRA that resulted in 50% reduction in the compatible donor pool measured from the time of transplant failure until the time of repeat transplantation, death, or end of study. The median cPRA at the time of failure was 12.13% (interquartile ranges = 0.00%, 83.72%) which increased to 62.76% (IQR = 4.34%, 99.18%) during the median follow-up of 27 (IQR = 18, 39) months. High HLA-DQ eplet mismatches were significantly associated with an increased risk of developing a clinically meaningful increase in cPRA ( p = 0.02) and de novo DQ donor-specific antibody against the failed allograft ( p = 0.02). We did not observe these associations in patients with high HLA-DR eplet mismatches. Most of the patients (88%) with a clinically meaningful increase in cPRA had both a high DQ eplet mismatch and a reduction in their immunosuppression, suggesting the association is modified by immunosuppression. The findings suggest HLA-DQ eplet mismatch analysis may serve as a useful tool to guide future clinical studies and trials which assess the management of immunosuppression in transplant failure patients who are repeat transplant candidates.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".