Association of BKV viremia and nephropathy with adverse alloimmune outcomes in kidney transplant recipients
Bibliographic record
Abstract
BACKGROUND: Immunosuppression reduction for BK polyoma virus (BKV) must be balanced against risk of adverse alloimmune outcomes. We sought to characterize risk of alloimmune events after BKV within context of HLA-DR/DQ molecular mismatch (mMM) risk score. METHODS: This single-center study evaluated 460 kidney transplant patients on tacrolimus-mycophenolate-prednisone from 2010-2021. BKV status was classified at 6-months post-transplant as "BKV" or "no BKV" in landmark analysis. Primary outcome was T-cell mediated rejection (TCMR). Secondary outcomes included all-cause graft failure (ACGF), death-censored graft failure (DCGF), de novo donor specific antibody (dnDSA), and antibody-mediated rejection (ABMR). Predictors of outcomes were assessed in Cox proportional hazards models including BKV status and alloimmune risk defined by recipient age and molecular mismatch (RAMM) groups. RESULTS: At 6-months post-transplant, 72 patients had BKV and 388 had no BKV. TCMR occurred in 86 recipients, including 27.8% with BKV and 17% with no BKV (p = .05). TCMR risk was increased in recipients with BKV (HR 1.90, (95% CI 1.14, 3.17); p = .01) and high vs. low-risk RAMM group risk (HR 2.26 (95% CI 1.02, 4.98); p = .02) in multivariable analyses; but not HLA serological MM in sensitivity analysis. Recipients with BKV experienced increased dnDSA in univariable analysis, and there was no association with ABMR, DCGF, or ACGF. CONCLUSIONS: Recipients with BKV had increased risk of TCMR independent of induction immunosuppression and conventional alloimmune risk measures. Recipients with high-risk RAMM experienced increased TCMR risk. Future studies on optimizing immunosuppression for BKV should explore nuanced risk stratification and may consider novel measures of alloimmune risk.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".