Identifying the patient at risk for post‐transplant lymphoproliferative disorder
Bibliographic record
Abstract
Post-transplant lymphoproliferative disorders (PTLD) are a recognized complication of the immunosuppression required to prevent allograft rejection, occurring in 1-20% of recipients of solid organ transplants. Several factors greatly increase the risk of developing PTLD early post-transplant in any individual recipient. Epstein-Barr virus (EBV) infection is critical in the pathogenesis of the majority of these cases. Pre-transplant EBV seronegativity increases the incidence of PTLD 10- to 75-fold over that of EBV-seropositive recipients. Other risk factors include very young recipient age, cytomegalovirus infection or mismatching (donor positive-recipient negative), aggressive immunosuppression with conventional biologic agents, and the type of organ transplanted. In contrast, the risk of developing PTLD late in the post-transplant course does not appear to be influenced by the type of immunosuppressive agents employed, but rather by the duration of any immunosuppression. The role of EBV in late PTLD is also less certain, as a greater proportion of lesions are not associated with evidence of EBV infection. As the understanding of these risk factors has expanded, opportunities exist to target those populations at highest risk for the development of PTLD for aggressive monitoring and pre-emptive or prophylactic therapy. It is hoped that implementation of such strategies will render early PTLD a preventable complication of transplantation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".