Renal Failure Five Years After Lung Transplantation Due to Polyomavirus BK‐Associated Nephropathy
Bibliographic record
Abstract
Polyomavirus-associated nephropathy (PyVAN) is rare in nonrenal solid organ transplantation and only limited information is available from single cases. We describe a 67-year-old female presenting with hypertension and progressive kidney failure due to PyVAN 60 months after lung transplantation. Plasma BK virus (BKV) loads were 4.85 log¹⁰ copies/mL at diagnosis and cleared slowly over 14 months after switching from tacrolimus, mycophenolate and prednisone to low-dose tacrolimus, sirolimus and leflunomide, the latter being discontinued for anemia and diarrhea. BKV- and JC virus-specific immunoglobulins were detectable prior to transplantation. Only BKV-specific IgG and IgM increased during follow-up. BKV-specific T cells were detectable in blood following in vitro expansion, but cleared with reincreased sirolimus, yet BKV viremia remained undetectable. We identified eight other cases of PyVAN in nonrenal solid organ transplantation including lung (n = 1), heart (n = 6) and pancreas (n = 1). Overall, diagnosis was later than commonly seen in kidney transplants (median 18 months, interquartile range 10-29). Seven patients were male, five received triple immunosuppression consisting of tacrolimus, mycophenolate, prednisone. Immunosuppression was reduced in four cases and cidofovir and/or leflunomide administered in five and two cases, respectively. Renal function deteriorated in five requiring hemodialysis in four. We discuss mTOR inhibitors versus cidofovir and leflunomide as potential PyVAN rescue therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".