Re-exposure to Mismatched HLA Class I Is a Significant Risk Factor for Graft Loss: Multivariable Analysis of 259 Kidney Retransplants
Bibliographic record
Abstract
BACKGROUND: Kidney retransplants carry increased immunologic risk. One possible contributor to this risk may be re-exposure to human leukocyte antigens (HLA) common to a previous donor but foreign to the recipient. Conflicting publications have assessed this risk, so to examine our experience 259 kidney retransplants were analyzed. METHODS: A retrospective cohort of retransplant patients from 1973 to 2005 with minimum 12 months follow up was examined. Using multivariable modeling, important confounders were controlled for identifying factors significantly affecting graft survival. RESULTS: Re-exposure to HLA class I (HLA-A or B) antigens, peak panel reactive antibodies and donor source were the most important determinants of allograft survival, despite a negative conventional or anti-human globulin-augmented T cell crossmatch. We failed to demonstrate that recipient re-exposure to HLA class II (HLA-DR) or positive B cell crossmatch were associated with adverse outcomes. Sample size and molecular versus serologic methods may have influenced the former, while inability to determine antibody specificities may have influenced the latter. Controlling for other variables, the adjusted risk of graft loss associated with re-exposure to HLA class I increased by 71% (P=0.006) and occurred early, consistent with recall of memory cytotoxic T lymphocyte or antibody responses. CONCLUSIONS: Kidney recipients re-exposed to mismatched HLA class I antigens appear to be at heightened risk of early graft loss. Such patients may benefit from pretransplant identification of donor specific antibodies using solid phase methods and heightened vigilance for acute rejection. Future studies may indicate whether more intensive immunosuppression for these patients is warranted.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".