Outcomes of Lung Transplantation in Recipients With Hepatitis C Virus Infection
Bibliographic record
Abstract
Hepatitis C virus (HCV) infection negatively impacts patient and graft survival following nonhepatic solid organ transplantation. Most data, however, are in kidney transplant, where despite modest impact on outcomes, transplantation is recommended for those with mild to moderate hepatic fibrosis given overall benefit compared to remaining on dialysis. In lung transplantation (LuTx), there is little data on outcomes and international guidelines are vague on the criteria under which transplant should be considered. The University of Alberta Lung Transplant Program routinely considers patients with HCV for lung transplant based on criteria extrapolated from the kidney transplant literature. Here we describe the outcomes of 27 HCV-positive, compared to 443 HCV-negative LuTx recipients. Prior to transplant, five patients were treated for HCV and cured. At the time of transplant, 14 patients remained HCV RNA positive. The 1-, 3-, and 5-year survival were similar in HCV RNA-positive versus -negative recipients at 93%, 77%, and 77% versus 86%, 75%, and 66% (p = 0.93), respectively. Long-term follow-up in eight patients demonstrated no significant progression of fibrosis. In our cohort, HCV did not impact LuTx outcomes and in the era of interferon-free HCV therapies this should not be a barrier to LuTx.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".