Epidemiology of Epstein-Barr Virus Chronic High Viral Load in Kidney Transplant Recipients
Bibliographic record
Abstract
Background. Epstein-Barr virus (EBV) chronic high viral load (CHVL) may be defined by >16 000 copies/mL whole blood or >200 copies/105 peripheral blood mononuclear cells in >50% samples exceeding 6 mo. EBV CHVL has only been characterized in a few small pediatric studies, with heterogeneous results and unclear clinical significance. Methods. This single-center observational study evaluated adult and pediatric kidney transplant recipients transplanted between 2010 and 2021 on tacrolimus/mycophenolate-based/prednisone immunosuppression. The primary outcome was EBV CHVL prevalence. Secondary outcomes included recipient characteristics, DNAemia kinetics, and posttransplant lymphoproliferative disorder (PTLD) in recipients with EBV CHVL versus low-grade DNAemia or no DNAemia. Results. Five hundred forty-one recipients had a mean follow-up of 4.6 y. Fourteen recipients (2.6%) developed EBV CHVL, 70 (12.9%) had low-grade EBV DNAemia, and 457 (84.5%) had no EBV DNAemia. EBV CHVL was more common in recipients who were Caucasian (P = 0.04), younger (P = 0.04), received induction immunosuppression (P = 0.02), and had high-risk donor–recipient EBV serologic mismatch (P < 0.0001). CHVL patients had a higher first viral load (P = 0.03), longer time to maximum viral load (P = 0.02), and did not achieve sustained DNAemia clearance versus low-grade DNAemia. Three EBV-positive PTLD cases occurred in recipients with a history of EBV DNAemia. PTLD was present in 7.1% (1/14) CHVL versus 2.9% (2/70) low-grade DNAemia patients (P = 0.002). EBV DNAemia developed in 32 EBV seronegative recipients (32/59; 54%); clearance was achieved in 70% (14/20) with low-grade DNAemia but no CHVL (0/12; P = 0.0001). Conclusions. CHVL was uncommon and appeared to occur after primary EBV infection. Future studies should explore other potentially modifiable risk factors for PTLD, including optimal management of EBV DNAemia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".