Impact of donor and recipient cytomegalovirus serology on long‐term survival of lung transplant recipients
Bibliographic record
Abstract
BACKGROUND: Pre-transplant cytomegalovirus (CMV) serostatus has been associated with lung transplant patient survival. We retrospectively analyzed the relationship between pre-transplant donor/recipient CMV serostatus and long-term mortality in a cohort of lung transplant recipients at our center. METHOD: Adult (Age >17 years) lung 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 652 lung recipients were analyzed. Twenty percent were CMV mismatched pre-transplant and 45% had CMV infection within 2 years post-transplant. Survival at 10 years appeared worse in D+ transplants (P = 0.027). D-/R- lungs did not have significantly different survival across eras (P = 0.76), but survival of D-/R+, D+/R+, D+/R- lungs improved (P < 0.001). Cox regression revealed that transplantation in the valganciclovir era reduced risk of death in lung transplants by an estimated 52% (P < 0.001) compared to transplantation in the pre-ganciclovir era after controlling for age at transplant, D/R CMV serostatus and CMV infection. Age at transplant and CMV infection were also significant predictors of mortality in lung transplants (P < 0.001 and 0.033 respectively). CONCLUSION: Our review of the impact of CMV managed differently across eras suggests in lung transplantation there is no independent 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".