Lung transplantation for late-onset non-infectious chronic pulmonary complications of allogenic hematopoietic stem cell transplant
Bibliographic record
Abstract
BACKGROUND: Late onset non-infectious pulmonary complications (LONIPCs) following allogenic hematopoietic stem cell transplantation (allo-HSCT) confer a significant mortality risk. Lung transplantation (LTx) has the potential to provide survival benefit but the impact of prior allo-HSCT on post-LTx outcomes is not well studied. METHODS: This retrospective, single-centre cohort study assessed the post-LTx outcomes of adults with LONIPCs of allo-HSCT. Outcomes of LTx for LONIPCs were compared to propensity-score matched LTx controls (n = 38, non-HSCT) and recipients of re-LTx (n = 70) for chronic lung allograft dysfunction (CLAD). RESULTS: Nineteen patients underwent DLTx for LONIPCs of allo-HSCT between 2003 and 2019. Post-LTx survival was 50% at 5-years. Survival to 1-year post-LTx was similar to matched controls (p = 0.473). Survival, conditional on 1-year survival, was lower in the allo-HSCT cohort (p = 0.034). An increased risk of death due to infection was identified in the allo-HSCT cohort compared to matched controls (p = 0.003). Compared to re-LTx recipients, the allo-HSCT cohort had superior survival to 1-year post-LTx (p = 0.034) but conditional 1-year survival was similar (p = 0.145). CONCLUSION: This study identifies an increased risk of post-LTx mortality in recipients with previous allo-HSCT, associated with infection. It supports the hypothesis that allo-HSCT LTx recipients are relatively more immunosuppressed than patients undergoing LTx for other indications. Optimisation of post-LTx immunosuppressive and antimicrobial strategies to account for this finding should be considered.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".