The <scp>IPTA</scp> Nashville consensus conference on <scp>post‐transplant</scp> lymphoproliferative disorders after solid organ transplantation in children: <scp>IV</scp>‐consensus guidelines for the management of <scp>post‐transplant</scp> lymphoproliferative disorders in children and adolescents
Bibliographic record
Abstract
The International Pediatric Transplant Association convened an expert consensus conference to assess current evidence and develop recommendations for various aspects of care relating to post-transplant lymphoproliferative disorders (PTLD) after pediatric solid organ transplantation. This report addresses the outcomes of deliberations by the PTLD Management Working Group. A strong recommendation was made for reduction in immunosuppression as the first step in management. Similarly, strong recommendations were made for the use of the anti-CD20 monoclonal antibody (rituximab) as was the case for chemotherapy in selected scenarios. In some scenarios, there is uncoupling of the strength of the recommendations from the available evidence in situations where such evidence is lacking but collective clinical experiences drive decision-making. Of note, there are no large, randomized phase III trials of any treatment for PTLD in the pediatric age group. Current gaps and future research priorities 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.
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 | 0.051 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".