Bibliographic record
Abstract
We evaluated aspects of the pathogenesis, diagnosis, and prognosis of antibody-mediated injury secondary to anti-human leaukocyte antigen (HLA) antibodies in kidney transplant recipients and candidates. In a nested case-control study from a cohort of adult kidney transplant recipients, we found an increase in the odds of transplant glomerulopathy, a finding on kidney transplant biopsies suggestive of chronic antibody-mediated rejection, as a function of structural donor and recipient HLA class II incompatibility. We also re-evaluated the diagnostic schema of acute antibody-mediated rejection, and found that C4d, a complement degradation product suggestive of antibody-mediated injury to kidney allografts, exhibited modest agreement and sensitivity against histopathological features of acute antibody-mediated rejection and donor-specific anti-HLA antibody (DSA) assays. Prognostically, C4d was associated with inferior allograft survival compared with DSA or histopathology alone. Finally, we conducted a retrospective cohort study using the Scientific Registry of Transplant Recipients and found that the breadth of sensitization against anti-HLA antigens, measured as panel reactive antibodies (PRA), was an independent predictor of mortality in wait-listed kidney transplant candidates. These findings underscore the importance of anti-HLA antibodies to the outcomes of kidney transplant recipients and candidates, and suggest that anti-HLA antibodies may give rise to complement dependent and complement independent phenotypes of antibody-mediated injury. Whether avoidance of structural HLA incompatibility between donors and kidney transplant candidates and minimization of immune sensitization in wait-listed patients will improve outcomes of kidney transplant candidates and recipients, warrants further study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".