High Risk of Sensitization After Failed Islet Transplantation
Bibliographic record
Abstract
Human Leukocyte Antigen (HLA) antibodies posttransplant have been associated with an increased risk of early graft failure in kidney transplants. Whether this also applies to islet transplantation is not clear. To achieve insulin independence after islet transplants multiple donor infusions may be required. Hence, islet transplant recipients are at risk of sensitization after transplantation. Islet transplant recipients were screened for HLA antibodies posttransplant by flow-based methods. A total of 98 patients were studied. Twenty-nine patients (31%) developed de novo donor specific antibodies (DSA) posttransplant. Twenty-three patients developed DSA while on immunosuppression (IS). Among recipients who have discontinued IS, 10/14 (71%) are broadly sensitized with panel reactive antibody (PRA) >or=50%. The risk of becoming broadly sensitized after transplant was 11/69 (16%) if the recipient was unsensitized prior to transplant. The majority of these antibodies have persisted over time. Appearance of HLA antibodies posttransplant is concerning, and the incidence rises abruptly in subjects weaned completely from IS. This may negatively impact the ability of these individuals to undergo further islet, pancreas or kidney transplantation and should be discussed upfront during evaluation of candidates for islet transplantation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".