Transfusion‐related Epstein‐Barr virus infection among stem cell transplant recipients: a retrospective cohort study in children
Bibliographic record
Abstract
BACKGROUND: Blood safety warrants strict screening measures to minimize the risk of transmitting blood-borne pathogens. However, transfusion-transmitted infections for which testing is not currently performed continue to be a concern. Among these untested agents is Epstein-Barr virus (EBV) which, in the transplant setting, is associated with lymphoproliferative disease, a potentially fatal cancer. The aim of this study was to analyze the incidence of posttransplant EBV infection and its association with administration of blood products in children receiving a hematopoietic stem cell (HSC) graft. STUDY DESIGN AND METHODS: This retrospective cohort study sought to review charts of pediatric recipients of HSC grafts to collect information on the presence of EBV antibodies in the recipients' pretransplant sera and in HSC donor sera, incidence of posttransplant EBV infection, and patients' transfusion history. Cumulative incidence of posttransplant EBV infection was estimated by Kaplan-Meier methods according to pretransplant serology. The association between blood products and EBV infection was measured by Cox regression models. RESULTS: The pretransplant EBV seroprevalence was 77.9% for recipients and 61.8% for graft donors. Virtually, all recipients received blood products during the peritransplant period. Among seronegative recipients, the 30- and 60-day cumulative incidences of posttransplant EBV infection were 4.6 (95% confidence interval [CI], 1.2-17.3) and 13.4% (95% CI, 5.8%-29.4%), respectively. The 60-day cumulative incidence was 8.3% (95% CI, 2.2%-29.4%) when restricting the analysis to seronegative recipients of cord blood grafts. Importantly, there was a clear positive trend associating EBV infection to transfusion volume. CONCLUSION: This study suggests an association between transfusions and posttransplant EBV infection in HSC transplant recipients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".