Pretransplant screening for infections in lung and heart transplant candidates
Bibliographic record
Abstract
Solid organ transplantation (SOT) is the definitive treatment for end-stage organ disease but also introduces a heightened risk of infection in the post-transplant period. In heart and lung transplantation, unique factors predisposing to infection include exposure of the lungs to the external environment, alteration of airway anatomy, pretransplant infection and colonization with difficult-to-treat organisms, and pretransplant presence of infected devices. This is in addition to risks common to all SOT leading, including immunosuppression. The aim of pretransplant infectious disease screening in SOT recipients is to prospectively identify infectious risks through careful history taking, examination, and laboratory testing, as well as mitigating these risks through vaccination, treatment, prophylaxis, and counseling on safe living. In this article, we review infectious risks in heart and lung transplant candidates and discuss recommendations for screening before 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 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".