Cystic fibrosis survival outcomes following second lung transplant: The north American experience
Bibliographic record
Abstract
INTRODUCTION: Re-transplant is an option for those who develop end-stage lung disease due to rejection; however, little data exist following re-transplantation in cystic fibrosis (CF). METHODS: Data from the Canadian CF Registry and US CF Foundation Patient Registry supplemented with data from United Network for Organ Sharing were used. Individuals who underwent a 2nd lung transplant between 2005 and 2019 were included. The Kaplan-Meier method was used to estimate the probability of survival post-second transplant at 1, 3, and 5-years. RESULTS: Of those people who were waitlisted for a second transplant (N = 818), a total of 254 (31%) died waiting, 395 (48%) were transplanted and 169 (21%) people were alive on the waitlist. Median survival time after 2nd lung transplant was 3.3 years (95% CI: 2.8-4.1). The 1-, 3- and 5-year survival rates were 77.4% (95% CI: 73.1-82%), 52% (95% CI: 46.7-58%) and 39.4% (95% CI: 34.1-45.6%). CONCLUSIONS: Survival following second lung transplant in CF patients is lower than estimates following the first transplant. Over half of subjects who are potentially eligible for a second transplant die without receiving a second organ. This warrants further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".