International survey of human herpes virus 8 screening and management in solid organ transplantation
Bibliographic record
Abstract
BACKGROUND: HHV-8/Kaposi Sarcoma herpesvirus has been associated with a broad spectrum of diseases in solid organ transplant (SOT) recipients. Primary donor-derived infection can be associated with severe and rapidly fatal non-neoplastic disease, and diagnosis is made with high HHV-8 DNAemia. METHODS: We carried out an international survey to investigate the current approach to HHV-8 screening, and management in SOT since a protocol has not been established by international guidelines. RESULTS: A total of 51 transplant centers from 15 countries filled out the survey. HHV-8-associated diseases in SOT have been diagnosed during the previous 5 years in 67% of centers. Pretransplant serological screening is performed in 17 centers (33%), and posttransplant HHV-8 nucleic acid testing (NAT) monitoring is performed in 21 centers (41%). Performing HHV-8 NAT monitoring and serological screening were found associated with having diagnosed in the previous 5 years a non-malignant HHV-8-associated disease. CONCLUSIONS: Serological pretransplant screening of donors and recipients and post-transplant HHV-8 NAT monitoring recommendations should be standardized. Even though serological assays are not optimal, they could contribute to increasing knowledge on epidemiology and management of HHV-8-associated diseases after SOT.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".