Late-onset cytomegalovirus disease in patients with solid organ transplant
Bibliographic record
Abstract
PURPOSE OF REVIEW: To review existing data regarding late cytomegalovirus disease occurring after antiviral prophylaxis. RECENT FINDINGS: There is a continued debate as to the respective merits of the preemptive and the prophylactic approach to prevent cytomegalovirus disease after transplantation. Arguably, by allowing some infection, the preemptive approach helps build immunity in contrast to prophylaxis, explaining the occurrence of late cytomegalovirus disease in the latter approach. No study comparing directly both approaches is large enough to definitely determine whether the preemptive approach leads to a faster development of immune response protective from late disease nor whether late disease is clinically different after prophylaxis compared to early cytomegalovirus diseases. While risk factors for late cytomegalovirus disease all point to a delay in mounting immune responses, there are no identified markers that would help predict the risk for late disease at the time of prophylaxis discontinuation. Various approaches to prevent late cytomegalovirus disease have been developed: prolonged prophylaxis, microbiological surveillance and preemptive treatment after prophylaxis discontinuation. Considering the identifying risk factors for late disease, it would also make sense to envision vaccinating cytomegalovirus-seronegative recipients. SUMMARY: The best approach to prevent or manage late cytomegalovirus disease associated with cytomegalovirus prophylaxis remains to be defined.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".