Seeking Standardized Definitions for HLA-incompatible Kidney Transplants: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: There is no standard definition for "HLA incompatible" transplants. For the first time, we systematically assessed how HLA incompatibility was defined in contemporary peer-reviewed publications and its prognostic implication to transplant outcomes. METHODS: We combined 2 independent searches of MEDLINE, EMBASE, and the Cochrane Library from 2015 to 2019. Content-expert reviewers screened for original research on outcomes of HLA-incompatible transplants (defined as allele or molecular mismatch and solid-phase or cell-based assays). We ascertained the completeness of reporting on a predefined set of variables assessing HLA incompatibility, therapies, and outcomes. Given significant heterogeneity, we conducted narrative synthesis and assessed risk of bias in studies examining the association between death-censored graft failure and HLA incompatibility. RESULTS: Of 6656 screened articles, 163 evaluated transplant outcomes by HLA incompatibility. Most articles reported on cytotoxic/flow T-cell crossmatches (n = 98). Molecular genotypes were reported for selected loci at the allele-group level. Sixteen articles reported on epitope compatibility. Pretransplant donor-specific HLA antibodies were often considered (n = 143); yet there was heterogeneity in sample handling, assay procedure, and incomplete reporting on donor-specific HLA antibodies assignment. Induction (n = 129) and maintenance immunosuppression (n = 140) were frequently mentioned but less so rejection treatment (n = 72) and desensitization (n = 70). Studies assessing death-censored graft failure risk by HLA incompatibility were vulnerable to bias in the participant, predictor, and analysis domains. CONCLUSIONS: Optimization of transplant outcomes and personalized care depends on accurate HLA compatibility assessment. Reporting on a standard set of variables will help assess generalizability of research, allow knowledge synthesis, and facilitate international collaboration in clinical trials.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".