De Novo Donor-Specific Antibody at the Time of Kidney Transplant Biopsy Associates with Microvascular Pathology and Late Graft Failure
Bibliographic record
Abstract
We studied whether de novo donor-specific antibodies (DSA) in sera from patients undergoing kidney transplant biopsies associate with specific histologic lesions in the biopsy and prognosis. DSA were assessed in 145 patients at the time of biopsy between 7 days to 31 years posttransplant. DSA was detected in 54 patients (37%), of which 32 represented de novo DSA. De novo DSA was more frequent in patients having late biopsies (34%) versus early biopsies (4%), and was usually either against class II alone or class I and II but rarely against class I alone. Microcirculation inflammation (glomerulitis, capillaritis) and damage (glomuerulopathy, capillary basement membrane multilayering), and C4d staining were associated with de novo DSA. However, the degree of scarring, arterial fibrosis and tubulo-interstitial inflammation did not correlate with the presence of de novo DSA. De novo DSA correlated with reduced graft survival after the biopsy. Thus, de novo DSA at the time of a late biopsy for clinical indication is primarily against class II, and associates with microcirculation changes in the biopsy and subsequent graft failure. We propose careful assessment of de novo DSA, particularly against class II, be performed in all late kidney transplant biopsies.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".