Donor Graft Cytomegalovirus Serostatus and the Risk of Arterial and Venous Thrombotic Events in Seronegative Recipients After Non-Thoracic Solid Organ Transplantation
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is the most common opportunistic pathogen, following solid organ transplantation (SOT), that leads to direct and indirect effects. The aim of this study was to assess the impact of CMV exposure at transplantation on the rate of posttransplant thrombotic events (TEs). METHODS: We conducted a retrospective cohort study of patients transplanted at the University of Alberta Hospital between July 2005 and January 2018. We included adult SOT CMV-seronegative recipients at transplantation who received an allograft from either a seropositive donor (D+/R-) or a seronegative donor (D-/R-). RESULTS: A total of 392 SOT recipients were included: 151 (39%) liver, 188 (48%) kidney, 45 (11%) pancreas, and 8 (2%) other transplants. The mean age was 47 years, 297 (76%) were males, and 181 (46%) had a CMV D+/R- donor. Patients in the CMV D+/R- cohort were slightly older (51 years versus 48 years in the D-/R- cohort; P = .036), while other variables, including cardiovascular risk factors and pretransplant TEs, were not different between groups. Overall, TEs occurred in 35 (19%) patients in the CMV D+/R- group, versus 21 (10%) in the CMV D-/R- group, at 5 years of follow-up (P = .008); the incidence rates per 100 transplant months were 5.12 and 1.02 in the CMV D+/R- and CMV D-/R- groups, respectively (P = .003). After adjusting for potential confounders with a Cox regression model, a CMV D+/R- transplantation was independently associated with an increased risk of a TE over 5 years (adjusted hazard ratio, 3.027; 95% confidence interval, 1.669-5.488). CONCLUSIONS: A CMV D+/R- transplantation is associated with an increased risk of a TE posttransplantation.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".