Post‐transplant lymphoproliferative disorders, Epstein‐Barr virus infection, and disease in solid organ transplantation: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract These updated guidelines from the American Society of Transplantation Infectious Diseases Community of Practice review the diagnosis, management, and prevention of post‐transplant lymphoproliferative disorders (PTLD) and other Epstein‐Barr virus (EBV) syndromes after solid organ transplantation. PTLD are a heterogeneous spectrum of predominantly B‐cell disorders, often extra‐nodal, with complex distinct pathogeneses and variable clinical presentations determined by pathologic subtype. Recent epidemiologic studies report a decrease in early EBV‐positive (+) PTLD and an increase in late EBV‐negative (−) PTLD. Pre‐transplant EBV‐seronegativity and primary EBV infection, often from donor‐transmitted infection, are an important risk factors for EBV syndromes and early EBV + PTLD. Low‐quality evidence supports preemptive prevention strategies for early EBV + PTLD in EBV‐seronegative recipients that involve EBV DNA measurement in peripheral blood using assays requiring further result harmonization, combined with interventions to lower viral load. Reduction in immunosuppression (RIS) is the best validated intervention. WHO pathology classification of a tissue biopsy remains the gold standard for PTLD diagnosis; optimal staging procedures are uncertain. Treatment of CD20 + PTLD with the response‐dependent sequential use of RIS, rituximab, and cytotoxic chemotherapy is recommended. Evidence gaps requiring future research and alternate treatment strategies including immunotherapy are highlighted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it