Association between cytomegalovirus viremia and long-term outcomes in lung transplant recipients
Bibliographic record
Abstract
Although cytomegalovirus (CMV) viremia/DNAemia has been associated with reduced survival after lung transplantation, its association with chronic lung allograft dysfunction (CLAD) and its phenotypes is unclear. We hypothesized that, in a modern era of CMV prophylaxis, CMV DNAemia would still remain associated with death, but also represent a risk factor for CLAD and specifically restrictive allograft syndrome (RAS)/mixed phenotype. This was a single-center retrospective cohort study of all consecutive adult, first, bilateral-/single-lung transplants done between 2010-2016, consisting of 668 patients. Risks for death/retransplantation, CLAD, or RAS/mixed, were assessed by adjusted cause-specific Cox proportional-hazards models. CMV viral load (VL) was primarily modeled as a categorical variable: undetectable, detectable to 999, 1000 to 9999, and ≥10 000 IU/mL. In multivariable models, CMV VL was significantly associated with death/retransplantation (≥10 000 IU/mL: HR = 2.65 [1.78-3.94]; P < .01), but was not associated with CLAD, whereas CMV serostatus mismatch was (D+R-: HR = 2.04 [1.30-3.21]; P < .01). CMV VL was not associated with RAS/mixed in univariable analysis. Secondary analyses with a 7-level categorical or 4-level ordinal CMV VL confirmed similar results. In conclusion, CMV DNAemia is a significant risk factor for death/retransplantation, but not for CLAD or RAS/mixed. CMV serostatus mismatch may have an impact on CLAD through a pathway independent of DNAemia.
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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 | 0.003 |
| 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 | 0.001 |
| 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".