Infections among pediatric transplant candidates: An approach to decision‐making
Bibliographic record
Abstract
INTRODUCTION: The presence of infections in the immediate pretransplant period poses challenges in decision-making. Delaying transplantation because of these infections may be required, but is associated with a risk to the potential recipient. The aim of this project was to develop a structured framework based on expert opinion to guide decision-making regarding the safety of transplantation for candidates with infection immediately before transplant, and to show how this framework can be applied to clinical scenarios. METHODS: Categories were created as follows: Category A: no delay; Category B: brief delay (≤1 week); Category C: intermediate delay (>1 week); and Category D: more prolonged or indefinite delay. A survey containing 59 clinical scenarios was sent to members of the IPTA ID CARE committee. Answers were reviewed, and the level of agreement was characterized as follows: Level 1: ≥75% agreement; Level 2:51%-74% agreement; and Level 3: ≤50% agreement. 95% CIs were calculated for the mean overall agreement across 59 scenarios. RESULTS: Among the panel, the agreement level ranged from 33% to 92% with the mean overall agreement across the 59 scenarios being 61%. For 7/59 scenarios, the lower bound of 95% CI was greater than 50%, indicating a difference at the 5% level of significance between the observed proportion and the chance level of 0.5. SUMMARY: The document provides expert opinion regarding the need to delay transplantation in the setting of different infections. The most important points in the decision to proceed to SOT included the urgency of transplantation and the severity of infection.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".