Hodgkin Lymphoma Post-Transplant Lymphoproliferative Disorder Following Pediatric Renal Transplant
Bibliographic record
Abstract
Post-transplant lymphoproliferative disorder (PTLD) occurs in 1.2% of pediatric renal transplant patients, and is frequently Epstein-Barr Virus mediated. Hodgkin Lymphoma PTLD is the rarest of the 4 types of PTLDs recognized by the World Health Organization, with an incidence of <4% of all PTLD patients. It has a distinct clinical course and treatment from all other types of PTLD. This is a case of a 16-year-old girl who had a renal transplant in 2000 due to Moya Moya disease. Her first F-18 FDG PET/CT done in 2006 showed mildly FDG-avid mediastinal adenopathy (histologically nonspecific reactive nodes), however in 2009, after presenting with fevers, a repeat PET/CT showed extensive intensely FDG-avid disease. Biopsy of a supraclavicular node identified Hodgkin Lymphoma PTLD. The patient was treated with chemotherapy and reimaged, showing excellent response to therapy. In contrast, classic PTLD is treated by withdrawal of immunosuppression and administration of Rituximab. F-18 FDG PET/CT is known to be very useful in the staging and monitoring of response to therapy in the setting of classic PTLD. In this case, serial F-18 FDG PET/CT scans proved very useful in the evaluation and follow-up of the rare and distinct Hodgkin Lymphoma PTLD subtype.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".