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Record W4406967329 · doi:10.1093/ofid/ofae631.2428

P-2275. Impact of Epstein-Barr Virus (EBV) Donor Serostatus on Post-transplant Mortality and Post-Transplant Lymphoproliferative Disorder in Thoracic Organ Transplant EBV-Seropositive Recipients: Data from the Organ Procurement and Transplantation Network

2025· article· en· W4406967329 on OpenAlexaff
Khuloud Aldhaheri, Allison Mah, Stephen Lee, Sara Belga

Bibliographic record

VenueOpen Forum Infectious Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
Fundersnot available
KeywordsSerostatusMedicinePost-transplant lymphoproliferative disorderOrgan procurementOrgan transplantationEpstein–Barr virusSolid organImmunologyTransplantationPathologyVirusInternal medicineViral load

Abstract

fetched live from OpenAlex

Abstract Background Epstein Barr Virus (EBV) donor positive (D+) serostatus is a risk factor for Post-Transplant Lymphoproliferative Disorder (PTLD) in EBV-seronegative recipients. The impact of donor EBV serostatus on mortality and PTLD in EBV-seropositive recipients (R+) in thoracic organ transplant (TOT) is unknown.Table 1.Baseline demographic and clinical characteristics of EBV D-/R+ and EBV D+/R+ TOT recipients Methods Using the Organ Procurement and Transplantation Network database, we identified 47,201 EBV R+ TOT recipients between 01/2004 – 12/2021. The primary exposure was EBV D+ and the primary outcomes were death and PTLD. Multivariable Cox regression models were used to assess the relationship between donor EBV serostatus and the outcome of death and PTLD.Figure 1.Kaplan-Meier survival plots for EBV D-/R+ (solid line) versus EBV D+/R+ (dashed line) post heart (red line) and lung (blue line) transplantation Results Of 47,201 EBV R+ TOT recipients, 48.5% were lung and 51% were heart transplant recipients. The majority (93.4%) were EBV D+/R+, with median age of 59 years and 66.8% males. EBV D-/R+ and D+/R+ TOT recipients differed in CMV donor and recipient status, donor median age, sex, and graft failure (Table 1). The incidence rate of death was 7.2 per 100 person-years in EBV D+/R+ compared to 6.9 per 100 person-years in EBV D-/R+, p=0.156. Survival did not differ by EBV donor status, but it was lower in lung transplant (Figure 1). The incidence rate of PTLD was 0.26 per 100-person years in EBV D+/R+ compared to 0.33 per 100-person years in EBV D-/R+, p= 0.073. EBV D+ status was not associated with increased hazard of death in both univariable (crude hazard ratio [HR] of 1.05; confidence interval [CI], 0.98-1.11; p=0.15) and multivariable analyses (adjusted HR of 0.96; 95% CI, 0.90-1.02; p=0.14), after controlling for donor age, CMV D+ status, and the following recipient factors: age, sex, race, insurance, pre-transplant life support, pre-transplant malignancy, rejection, and graft failure. EBV D+ status was associated with decreased hazard of PTLD when adjusting for recipient age and graft failure (adjusted HR of 0.74; 95% CI, 0.56-0.98; p=0.03). In subgroup analyses by organ, EBV D+ status was associated with decreased hazard of PTLD in lung (adjusted HR of 0.56; 95% CI, 0.40-0.78; p=0.001) but not in heart transplant recipients (adjusted HR of 1.18; 95% CI, 0.71-1.96; p =0.50) (Figure 2).Figure 2.Kaplan-Meier PTLD-free survival plots for EBV D-/R+ (solid line) versus EBV D+/R+ (dashed line) post heart (red line) and lung (blue line) transplantation Conclusion Among EBV-seropositive TOT recipients, EBV D- status may be associated with increased risk of PTLD, particularly in lung transplant recipients. Disclosures Alissa J. Inc, MD, MSc, Takeda: Honoraria Sara Belga, MD, MPH, Takeda, Moderna, AstraZeneca, GSK: Advisor/Consultant|Takeda, Moderna, AstraZeneca, GSK: Grant/Research Support|Takeda, Moderna, AstraZeneca, GSK: Honoraria

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0400.003

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.

Opus teacher head0.027
GPT teacher head0.361
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
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