Impact of donor and recipient cytomegalovirus serology on long‐term survival of heart transplant recipients
Bibliographic record
Abstract
Abstract Background Some studies have shown that pre‐transplant cytomegalovirus (CMV) serostatus is associated with heart transplant patient survival while others have not. We analyzed the relationship between pre‐transplant donor/recipient CMV serostatus and long‐term mortality in a retrospective cohort of heart transplant recipients at our center. Methods Adult (Age >17 years) heart recipients transplanted between July 1985‐December 2015 were analyzed. Variables included age, sex, pre‐transplant donor (D)/recipient (R) serostatus [D−/R−, D−/R+, D+/R+, D+/R−], CMV infection within 2 years of transplant and transplant eras divided by changes in CMV prevention strategies: Era 1 (Pre‐ganciclovir, July 1985‐April 1998), Era 2 (Oral ganciclovir, May 1998‐December 2004), Era 3 (Valganciclovir, January 2005‐December 2015). Survival analysis and Cox regression were performed at 10 years. Results A total of 620 heart transplants were included in our analysis; 20% were CMV mismatched pre‐transplant. Thirty‐eight percent of patients were infected with CMV within the first two post‐transplant years. Survival analysis showed D/R CMV serostatus did not significantly impact survival of heart recipients at 10 years (P = 0.11). Survival was significantly different across eras for D−/R+, D+/R+, and D+/R+ (P = 0.043) but not D−/R− patients (P = 0.8). Cox regression revealed that patients transplanted in the valganciclovir era have an estimated 29% reduced risk of death (P = 0.047) compared to patients transplanted in the pre‐ganciclovir era after controlling for age at transplantation, D/R CMV serostatus and CMV infection. Conclusion Our review of the impact of CMV managed differently across eras suggests in heart transplantation there is no influence of D/R CMV serostatus on 10 year survival.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".